Video Analytics Archives - Interface Systems

Video Monitoring Use Cases

Matt Smitheman — Fri, 29 Mar 2024 10:18:44 +0000

Video Analytics

Matt Smitheman

Senior Solutions Consultant

Business Security Remote Video Monitoring Video Analytics

8 Video Monitoring Use Cases for Retail and Restaurant Chains

Video monitoring has become the first line of defense for asset protection and loss prevention teams at retail and restaurant chains. Use cases for video monitoring are already well understood and they cover the most common threats – burglary, robbery, shoplifting, vandalism, and internal theft.

However, what is not understood is to what extent video monitoring addresses these risks and what else can be accomplished by video monitoring in the context of current technology innovations.

This blog post offers loss prevention or asset protection teams insights on how a combination of advanced video monitoring technology along with a well-trained monitoring team can not only deliver a wide range of business security services but also offer advanced operational insights, and improve employee morale.

1. Stop Shoplifting

After the brief, COVID closure-induced lull, shoplifting is now a growing threat for retailers. According to the Council on Criminal Justice, shoplifting incidents rose 22% between 2022 and 2023. For a habitual shoplifter, the presence of video cameras is just a speed bump and they find ways to cleverly hide their deeds and identities with Covid hold over masking or meticulously plan their act. Hence, traditional video monitoring solutions have limited applications other than identifying perpetrators if the camera device choices and installations are properly set up.

However, if video monitoring by a remote monitoring team is enhanced with the ability to issue voice-down commands, shoplifters can be stopped in their tracks even before they commit shoplifting and, in many cases, force them to rethink their choices even after they pocket the merchandise.

Shoplifting is a crime of opportunity and it ends the moment the shoplifter realizes someone is watching them. The overt security presence in the form of a voice-down commend either recorded or live has a significantly better impact on shoplifters who are accustomed to video surveillance.
When live video monitoring can be requested on-demand by a store employee who has direct access to a remote command center via a security phone, suspicious actions by anyone at the store can be spotted and acted upon. Remote security staff can then deliver targeted voice-downs that can sometimes describe the person committing a crime or issue a general command about the security presence.
Remote video monitoring and voice-downs can also be timed to align with key moments of the day when shoplifting spikes. For example, convenience stores near schools see a spike in security incidents when the school ends for the day in the afternoon. That’s when “gangs” of teens walk into a store and start pocketing merchandise.

Issues in Combating Shoplifting

How Video Monitoring Can Help

Shoplifters are no longer deterred by passive surveillance.
Live 24/7 video monitoring may still require action on the ground when a shoplifter is caught in the act.
Involving employees in confronting or stopping shoplifters is risky and often not encouraged by the store operators.
The presence of security guards increases the risk of confrontation, life threat, and liability claims exposure.

Periodic virtual tours with live voice-down commands can demonstrate “active” security presence and deter shoplifters.
Using security phones or concealed panic buttons, employees at the store can request live monitoring and voice-down anytime they see suspicious activity.

2. Deter Smash and Grab

Smash-and-grab incidents have become a serious threat for many retailers and even restaurants. Some of the worst affected states like California have increased spending on law enforcement to combat smash-and-grab incidents in the state that’s forcing retailers and restaurant chains to close down operations in high-risk areas.

In situations where smash and grab is already in progress, the standard operating procedure at most retailers is for employees to back off and not confront the criminals. If a security guard is present on site, the situation can become more challenging as the guard may be targeted by the gang as they seek to subdue any potential threat to their plan.

Remote video monitoring with interactive capabilities can make a difference in minimizing losses and providing a greater chance for law enforcement to apprehend smash-and-grab perpetrators.

Remote surveillance with periodic voice-downs announces active security presence to those casing a location. With interactive monitoring, employees can request active monitoring using the security phone if they suspect anyone at the store acting suspiciously such as asking where the most expensive items are kept.
When remote monitoring is combined with live voice-downs, criminals know they are under surveillance and law enforcement is probably on their way. This can help minimize damage and loss as the perpetrators look to leave the premises quickly.
Remote video monitoring enables faster information dissemination to internal loss prevention teams, mall security, and law enforcement. This can be valuable in securing nearby locations proactively or improving the chances of apprehending criminals.

Issues in Combating Smash and Grab

How Video Monitoring Can Help

Gangs operate with impunity as SOPs in most consumer-facing establishments focus on employees stepping aside and directing customers away from gangs.
There is no way to stop gangs from casing the location.
The presence of security guards increases the risk of confrontation, life threat, and liability claims exposure.
Real-time information about gangs is usually not available for law enforcement or mall security to take action.

Alert the central station to seek active surveillance assistance or initiate voice-downs based on the situation that’s unfolding while staying away from harm’s way.
Deter casing with frequent remote virtual tours accompanied by voice-downs.
Gain complete situational awareness and pass on valuable information to security teams and law enforcement.

3. Prevent Vandalism and Loitering

Retail and restaurant chains across the US are battling incidents of smash-and-grab, break-ins, and vandalism. Brands with downtown locations are facing additional headwinds in the form of fewer footfalls, homelessness, vandalism, and vagrancy. With retailers cutting back on hiring, more retail employees are working alone in high-risk situations.

While retailers and restaurant brands have complete control inside the four walls of their stores, they have little or no control over what happens outside and in the perimeter. In downtown locations abetting back alleys, potential troublemakers can find hidden spots to congregate or engage in nefarious activities.

While remote video monitoring can offer 24/7 surveillance inside and outside the store, its effectiveness can improve exponentially with AI-enabled cameras that can accurately detect people or vehicles. Automated detection of unauthorized presence of vehicles or people can be augmented by automated voice-downs, strobes, and lights to ensure prompt action is taken to mitigate risks.

An intelligent voice-down solution that plays out pre-recorded messages when the AI camera flags a security threat can deliver a wide range of security outcomes:

Detects threats autonomously and plays appropriate pre-recorded messages, optional strobes, and/or lights.
Customizable for diverse use cases - after-hour drop-offs, loitering, vagrancy or illegal encampments, vandalism, and unauthorized parking.
Plays a sequence of follow-up messages based on the subject’s compliance with warning messages. Helps in shortening any undesirable activity before it causes major damage.
Handles non-security tasks too - welcome greetings for customers during business hours or remind employees about operating procedures.
Can be integrated with the command center for live video monitoring and voice-downs and give store employees the means to contact the command center for real-time monitoring or voice-down.

Difficulty in Securing the Perimeter

How Video Monitoring Can Help

Monitoring the entire perimeter of a store or restaurant for potential security threats such as loitering, vandalism, and casing is not always foolproof as it requires either a security guard on-site to make frequent rounds or have remote monitoring teams review live video feeds at all times.
Human monitoring for large perimeters (both onsite and offsite) is prone to errors and lapses.
Employees may end up confronting loiterers or vandals. This might escalate the situation or put them in harm’s way.

Offer continuous and proactive security presence with AI-enabled video monitoring augmented with voice-downs and lights.
Trigger voice-downs to announce security presence based on automated threat detection or alarm events such as glass-break alarms.
Deploy 360-degree, always-on monitoring with no gaps.
Eliminate the need for employees to directly interact with troublemakers.
Benefit from versatile applications that go beyond securing the premises.

Find out how Interface uses AI-enabled cameras to deliver autonomous video monitoring that stops crime before it happens.

Learn More

4. Enhance Post-Incident Response

Consumer-facing businesses with retail locations bear the brunt of social or civil unrest. Way back in 2020, when the country was swept by widespread social unrest, thousands of store locations were looted or vandalized.

While there are several ways to proactively deal with the safety and security of people and merchandise in the event of social unrest, how can retailers, restaurants, and other consumer-facing businesses deal with the aftermath of unrest? The same question applies to more frequently occurring incidents such as robberies, floods, or smash-and-grab attacks.

“While we cannot always control what happens outside of our stores and facilities, we can shape the culture within”, remarked the then-CEO of Macy’s speaking about the 2020 race riots.

At a time when employees are on the edge and customers are apprehensive about visiting stores that are recovering from recent attacks, video surveillance coupled with interactive monitoring capabilities such as voice-downs, can mitigate anxiety among employees and customers.

For example, remote business security service providers like Interface help customers address this issue by adopting the following protocols:

Demonstrating live security presence 24/7 using a combination of video and interactive monitoring greatly improves the work environment and customer experience, especially in the aftermath of violent incidents.

Aftermath of a Security Incident

How Video Monitoring Can Help

Employee anxiety about safety at the location.
Higher perceived risks when opening or closing the store.
Diminish customer footfall and reduce time spent at the store.

Demonstrate security presence by increasing the frequency of virtual walkthroughs and conducting live voice-downs to reassure employees and customers.
Act as eyes and ears for employees opening the store or closing the location.

5. Boost Employee Retention

A recent survey conducted by Motorola found that 2 out of 3 retail workers had expressed concerns about their safety at work. In another survey by Verkada that included all consumer-facing businesses, 50% of those surveyed declared they were considering leaving the employer if they did not improve safety.

At a time when retail and restaurant businesses are already reeling from high employee turnover, increasing incidents of crime and violence at the workplace only make this problem acute. Boosting safety by deploying security guards is expensive, unreliable, and often negatively impacts the perceived safety as new customers may see guards as a sign of trouble.

Remote video monitoring with interactive capabilities can address these challenges.

Remote video monitoring augmented with periodic voice-downs reassures employees and customers about a constant security presence.
Offering employees multiple options to immediately seek attention overtly or discreetly (such as using security phones and hidden panic buttons) greatly alleviates security concerns.
Interactive video monitoring services like on-demand security escorts during store opening, closing, or trash runs add to the sense of safety among employees who may be operating alone.

Employees feel safer when they can interact with a live security professional on demand or notice that someone is proactively checking in on them. It’s a “warm safety blanket” that boosts morale and improves employee retention.

Challenges in Employee Retention

How Video Monitoring Can Help

Increasing incidents of disruptive customers, vandalism, vagrancy, and violent crimes force frontline employees to quit.
Employees fear for their safety when working alone during night shifts when there is no one available to seek help.

Offer continuous and proactive security presence with remote video monitoring.
Augment video monitoring with periodic voice-downs or on-demand voice-downs to announce security presence.
Give employees the option to virtually summon security presence for carrying out high-risk tasks.

6. Monitor Overnight Construction or Renovation

Retailers and even restaurant chains understand the importance of customer experience in bringing back customers and increasing the basket size. For example, Walmart spent about $9 billion in the last two years to renovate over 1400 stores. Restaurants too are revamping their locations with expanded drive-thrus and streamlined dining areas.

The bottom line is that consumer-facing multi-site businesses will have to deal with periodic overnight construction activity at some of their locations. Securing the locations when you have a third-party construction crew on the premises is a tricky challenge especially when you have valuable merchandise, equipment, or inventory at the same location.

Just deploying a security guard to watch the construction crew is expensive and has several drawbacks. Security guards may not be able to maintain vigil and ensure compliance all the time, they may show up late or need to schedule their breaks properly.

If remote video monitoring capabilities are already available at locations where overnight construction is scheduled, it throws open a variety of options for the business to monitor if the construction crew is compliant and everything in the location remains intact.

With remote video monitoring and interactive monitoring capabilities, businesses can:

Schedule temporary remote virtual tours when the crew is working on-site to ensure the crew is not violating any policy (leaning against a display unit, not covering up their boots, to name a few).
Make available interactive monitoring capabilities for the construction crews to check in on a need basis such as when leaving the site for a break or coming back in.
Check if all the entry and exit points are secured at all times.
Deliver live voice-downs on a need basis to ensure compliance.
Record videos of compliance and policy violations to create an audit report for the business which can also be shared with the construction company to ensure better compliance and safety at the location.

Remote video monitoring allows multi-site businesses to track and monitor construction safety at hundreds of locations at a time at a fraction of the cost of hiring security guards. In addition, the recorded video serves as a powerful audit and training tool for the construction crew and the loss prevention or asset protection teams.

Issues in Monitoring Overnight Construction

How Video Monitoring Can Help

Need for deploying expensive security guards at every location.
Last-minute guard replacement challenges or no-shows.
No tangible value in terms of learning or best practices is possible.

Replace security guards with an advanced solution at a fraction of the cost for the duration of the overnight construction project at any number of locations.
Service is always available as per the construction schedule.
Intervene in real-time with voice-downs to address safety issues or policy violations.
Audit locations for compliance or policy violations by construction workers. Share audit reports with stakeholders for remediation.

7. Manage Unattended Direct Store Deliveries

Unattended Direct Store Deliveries (DSD) is a popular restocking model in several retail categories like grocery, beverages, and large restaurant chains. This delivery model involves a supplier or distributor to ship the products directly to the store every night for restocking the location.

The DSD model is cost-effective for the business provided it’s managed properly. Because deliveries are unattended and made by third-party drivers when the restaurant or store is closed or running with a skeletal staff, there is an increased risk of theft, liability claims, or accidents.

A video monitoring solution that’s integrated with access control and intrusion alarms at the location can address these risks comprehensively.

Assign specified time slots for 3rd-party drivers to access the backdoors for restocking.
Track all instances of backdoor opening and closing and record video evidence every time the door is opened.
Track exceptions such as door open outside scheduled delivery slots, open doors, and movement of delivery personnel outside designated areas.
Minimize fraudulent liability claims by 3rd-party drivers.
Minimize the need for expensive security guards.

Challenges in Monitoring Unattended Deliveries

How Video Monitoring Can Help

Completely reliant on 3rd-party drivers to ensure every delivery is done as per the rules and policies governing unattended deliveries.
Absence of irrefutable evidence in case of injuries, theft, property damage, or inventory damage.

Enforce access to the facility only at predefined time slots and capture evidence of compliance by integrating video monitoring with access and alarm systems.
Record exceptions and use video evidence for training, claim management, or process improvement.

8. Audit Business Operations

Monitoring store or restaurant operations is a complex challenge for brands, especially for those with numerous locations and diverse formats. To ensure compliance with corporate standards and brand guidelines, retailers and restaurant chains deploy on-site auditors who may conduct planned or even unscheduled audits at different locations.

Onsite audits, while being effective, have inherent limitations. It’s expensive to deploy auditors on-site when there are thousands of locations to manage. The auditors can’t observe what’s happening while remaining discreet in areas where customers are out of bounds.

Video monitoring can address these issues. Because almost all parts of the store or restaurant are under video surveillance for security purposes, it makes a lot of sense to start auditing the location by observing the security footage.

Some of the areas that can be easily audited using video monitoring include:

Safety and Security: Store opening or closing procedures, delivery management, bank runs, cash movement.
Customer Experience: Employee uniform compliance, clearing shopping carts, clearing spillages and debris, cleaning tables and surfaces.
Merchandising: Stock-outs, display guidelines, promotions compliance.
Staffing: Queue lengths, dwell times, staff on the floor.

Did you know? Interface offers advanced business analytics solutions (including remote audits) for retail and restaurant chains. Find out how your security cameras can do a lot more than what you thought was possible.

Learn More

Challenges in On-Site Audits

How Video Monitoring Can Help

Site audits are expensive.
On-site auditors may not be able to perform discreet audits at all times.
It is difficult to deploy auditors at all locations.
Site audits can be disrupted due to external factors such as poor weather, transport disruptions, or pandemics.

Leverage existing security camera infrastructure and minimize the need to deploy on-site auditors to dramatically reduce costs.
Conduct discreet audits at scale for any number of locations or schedule audits based on operational cadence.
Audit any location at any time of the day or week and under any circumstance.
Capture screenshots screenshots from the video recording or live video to go with the audit reports.
Extend the use of security cameras beyond the core security use cases to accelerate ROI from any camera hardware upgrade that may be needed.

Make Your Security Cameras Work for You

Schedule a free business security consultation to find out how Interface can help you discover what loss prevention teams have always been missing.

Get a Free Consultation

Share this article

About the author

Matt Smitheman

Senior Solutions Consultant

Matt Smitheman is a veteran in the remote video monitoring and physical security industry, He is a trusted advisor for large multi location retail and restaurant businesses on their comprehensive security strategies. He has enabled companies to enhance their customer and employee safety, maintain compliance, and mitigate risk.

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

Steve Womer — Mon, 09 Jan 2023 14:43:26 +0000

Video Analytics

Steve Womer

SVP, Engineering

Business Intelligence Restaurants Video Analytics

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

Introduction

What’s Propelling Restaurant Drive-Thru Innovations?

The first-ever restaurant drive-thru concept was launched way back in 1947. Red’s Giant Hamburg drive-thru allowed customers to drive up to a window to place orders and receive their food. Since then drive-thrus have consistently delivered a significant chunk of the revenue in the QSR (Quick Service Restaurant) category.

COVID-19 has accelerated the need for restaurants to have a comprehensive drive-thru strategy in place and focus on drive-thru innovation. This was primarily driven by:

Heightened anxiety about health and safety
Need for greater convenience and flexibility to order food

By the end of 2021, every major restaurant brand reported significant drive-through sales growth and drive-thru accounted for 52% of the customer traffic share for QSRs.

This trend is not just restricted to QSRs. Even full-service chains, cafes, and pizzerias that have traditionally invested in dine-in spaces are expanding drive-thru options for customers. Recently, Applebees revealed that they are planning to aggressively roll out drive-thrus to strengthen off-premise service capability.

Restaurant brands are now investing in a suite of technology solutions and drive-thru concepts that delivers an amazing customer experience across the customer engagement lifecycle for the drive-thru channel.

Upgraded online and mobile ordering
AI-driven digital menu and order confirmation boards
Bluetooth sensors and mobile apps for personalized drive-thru experience
Diverse mobile and online payment options
Dynamic menu and menu rationalization based on complexity and inventory
Kitchen automation

Gamification to improve employee engagement
Video management systems to access customer interaction videos for training
POS with forced prompts or modifiers to upsell related items or premium toppings
Automated check-in alerts for employees to serve customers with pre-orders

Computervision to track order assembly and packaging
Advanced speakers and microphones with noise suppression technology
Secure identity validation at drive-thru pickup window

In 2024, having a drive-thru is no longer a secondary growth strategy. QSRs that had already bet big on drive-thru services are now accelerating drive-thru automation to tackle one of the biggest challenges to running a profitable restaurant – wage and commodity inflation.

1. Expanded Drive-Thru Lanes

In June 2022, Taco Bell launched the Taco Bell Defy which boasts of four drive-thru lanes, food delivery lifts that eliminate direct contact between customers and employees, and interactive audio-video technology for customer service. Separate drive-thru lanes for app pre-orders, drive-in customers, and third-party delivery agents allow Taco Bell to maximize the speed of service and minimize wait times.

Brands like Panera, McDonald’s, Burger King, and KFC are rolling out updated restaurant designs with increased drive-thru capacity and smaller dine-in areas.

Adding additional lanes is not the only option to increase drive-thru throughput. Tim Hortons has launched tandem drive-thrus that come with two sets of digital menu boards and intercom in a single lane designed to take orders from two cars at a time.

Adding additional drive-thru lanes can be challenging as restaurants have to proactively address points of customer friction, manage traffic volumes, and enable seamless integration with POS systems.

Here is an extract from an article that summarizes the real-world challenges that Schlotzsky’s experienced when they piloted a double-drive-thru, with one drive-thru on each side of the restaurant.

“When you have two menu boards where you’re taking orders at the same time, we really had to figure out how that flows through into our kitchen. And when two menu boards are taking orders at the same time, we had to equip our drive-thru make station with a headset so that they could listen to both the first drive-thru lane and the second drive-thru lane, and start the production of those products before the guests finished ordering.”

“In the early days of launching this double drive-thru, Schlotzsky’s employees had to train customers that were going to the pickup lane because the service counter is now on the passenger side, which is not what customers are used to. The store needed to go back and modify signage and striping on the asphalt to make directional flow clear to customers and improve traffic confusion.”

2. Intelligent Outdoor Digital Menu Boards (ODMBs)

Outdoor digital menu boards play a critical role in helping drive-thru customers make an informed choice of what to order and speed up the drive-thru experience. The latest generation of digital menu boards are connected to the cloud and have the ability to dynamically change the menu and pricing based on diverse input from other restaurant applications.

Some of the recent innovations in personalizing the drive-thru experience include

Digital menu boards linked to mobile apps that rely on the phone’s location data to trigger menu board personalization when the customer drives up to the restaurant location.
Speciality Bluetooth devices integrated with the drive-thru speaker post to trigger menu board personalization, enable the customer to redeem reward points, and make payments using their mobile phone.
Machine learning-driven menu boards not only suggest a personalized menu based on the purchase history, external factors (such as the weather), or daypart, but also optimize the menu to eliminate order processing complexity.

McDonald’s implemented Dynamic Yield’s personalization platform to offer a dynamic menu at their drive-thrus. In the US, McDonald’s is able to show menu items based on factors such as time of day, real-time restaurant traffic information, and popularity to help provide an enhanced customer experience.

Restaurant Brands International, the parent company of QSR brands such as Burger King, Tim Hortons, and Popeyes had already started rolling out personalized ODMBs in 2021 across thousands of locations.

3. Gamification for Drive-Thru Employees

Serving customers at the drive-thru can get monotonous for employees. Critical performance metrics such as average speed of service and order value are reviewed periodically by the manager or supervisor and employees get to hear about it only when they fall short of the productivity benchmarks or for training purposes. Gamification of drive-thru tasks addresses this problem and significantly improves employee participation and engagement.

HME’s ZOOM Nitro’s drive-thru optimization system allows restaurants to gamify drive-thru service for engaging employees.

Source

Here are some of the ways gamification can improve employee engagement and productivity:

Drive-thru leader boards can show where employees stand compared to their colleagues and introduce a positive competitive spirit at work.
Restaurant chains can conduct friendly contests between locations with bragging rights and offer rewards as an upside for top-performing locations.
As critical metrics are now transparent and available for all employees in real-time, employees readily take ownership of performance improvement plans.

I3 International’s drive-thru leaderboards offer real-time performance snapshots of drive-thru employees giving employees and restaurant managers a live drive-thru customer service performance update.

4. Computer Vision and Video Analytics at the Drive-Thru

Video feeds from the cameras in the drive-thru area can be analyzed by computer vision algorithms in real-time to improve sales, improve order accuracy, reduce chargeback claims, flag food safety issues, and track line dropouts before purchase.

Computer vision can read license plates of cars and even identify the age profile of the occupants inside the car. This data is useful to recognize repeat customers and show a personalized menu or offer exclusive perks as the customer pulls into the drive-thru digital menu post.

I3 Internation’s video analytics platform can recognize repeat customers by reading the number plates of cars at the drive-thru. Once a repeat customer is identified, the platform will automatically display relevant information to the employees at the drive-thru to recommend favorite products and offer a personalized guest experience.

Video cameras can identify repeat customers at the drive-thru by reading the registration plates

Source: i3 International

2. Ensuring order accuracy has a direct impact on sales performance and customer loyalty. Computer vision and AI applications connected to cameras in the kitchen can pinpoint mismatches in order assembly before the items are delivered to the customer.

3. In addition to identifying customers, computer vision can track drive-thru line dropout data. This information when mapped to dayparts, locations, weather, and day of the week can uncover valuable insights for QSRs. These insights can help restaurants optimize menu complexity and staffing, or even re-design the drive-thru lanes.

Presto Vision’s software allows restaurants to improve drive-thru sales and delight customers.

Source

4. A Deloitte study has found that customers are willing to pay a premium if they can see evidence of cleanliness and safe food handling practices. Computer vision and AI applications can spot instances when prescribed food preparation and handling processes are not followed so restaurants can train their employees better and ensure complete safety compliance.

5. AI-Based Voice Assistance

Voice is a critical component of the drive-thru customer experience, and hence more QSRs are investing in installing advanced two-way audio communication systems at the drive-thrus that are designed to

Reduce outbound (kitchen noise) and inbound noise (traffic or engine sounds), to improve order accuracy and eliminate delays due to miscommunication or poorly understood order details.
Use automated audio alerts for employees to manage customers at the drive-thru, curbside pickup slots, or 3rd-party delivery pickups.

With AI-enabled voice technology, voice can now go beyond just improving communication. It can potentially reduce the need for employees to handle all the drive-thru transactions. This is especially useful in a tough labor market where staffing and retention are significant challenges confronting QSRs. Here are the various ways AI-enabled voice automation is being used by QSRs and fast-casual restaurants.

Chipotle had already rolled-out Amazon Alexa reordering skill way back in 2019 for Chipotle customers who are already a part of the loyalty program. They later expanded AI-based voice ordering for phone orders as well. With the recent roll-out of dedicated drive-thru pick-up windows (aka Chipotlanes), Chipotle customers who order ahead using voice or app can drive up to the pickup window and drive out in under 12 seconds.
In 2019, McDonald’s acquired Apprente, an AI-based technology that can engage in conversations with humans to improve drive-thru order accuracy. McDonald’s piloted the technology in 2021 at 24 drive-thrus in the Chicago area and reported about an 80% success rate. The technology is being further tested and upgraded with the help of IBM before a system-wide roll-out.
Wendy’s is leveraging Google Cloud to roll out a combination of AI-enabled voice technology along with computer vision that’s designed to take orders at the drive-thrus and send the transcribed order details directly to the kitchen and POS.

Presto claims to offer AI-enabled conversational technology that can only take drive-thru orders but also upsell, recommend items with shorter preparation time, and recommend items based on past orders. The Presto voice solution has diverse applications that go beyond drive-thru. These include inventory management, phone orders, tableside ordering, and staff training.

6. Automated Drive-Thru For App Orders

“McDonald’s is piloting a drive-thru concept that completely eliminates the need to have any customer-facing staff. Customers who choose to dine in, place orders via self-service kiosks, and robots bring the order from the kitchen. For those who want to use the drive-thru, the only option available is by ordering ahead via the app.

When customers order ahead via the McDonald’s app with push notifications enabled and location access turned on, food preparation is timed to the customer’s estimated pick-up time. Once the customer reaches the restaurant, they pull into the order ahead drive-thru lane to pick up their order that’s delivered via conveyor belt.

McDonald’s is piloting an automated order ahead drive-thru lane at one of their Texas locations.

Source: McDonald’s

The concept of ordering ahead and picking up at a special lane at the drive-thru is not a new concept. What’s novel with the McDonald’s location is the absence of customer-facing employees. As hiring for restaurant jobs and retaining employees becomes tougher, and wage inflation going through the roof, a conveyor belt bringing the order directly from the kitchen to the drive-through pickup point could probably become a mainstream solution.

7. Restaurant Robotics & Future Contactless Drive-Thru

The National Restaurant Association (NRA) paints a grim view of the labor shortages that continue to plague the restaurant industry in the US. According to NRA, “Despite the steady employment gains during the last 2 years, eating and drinking places are still 450,000 jobs (or 3.6%) below their pre-pandemic staffing levels. That’s the largest employment deficit among all U.S. industries.” To combat this challenge, some restaurants have already started deploying robots not only for kitchen automation but also for customer service. It’s just a matter of time before drive-thru customers have an entirely contactless experience when kitchen automation and service automation technologies mature.

A new crop of restaurant robot companies have all graduated their products from the design or prototyping phase to deployment at restaurants.

Robotic Arms – Ally, Nala, Miso
Bartender Robots – Makr Shakr, Cecilia.ai
Bowls and Salad Maker Robots – Chowbotics, Spice, Beastro, Autec
Food Delivery Robots – Starship, Neuro, Kiwibot
Robot Waiters – Bellabot, Matradee, Servirobot
Pizza Robots – Picnic, Piestro, Zume
Coffee Shops – Cafex, Rozum, Artly, CookRight

Prominent restaurant brands are piloting robots or have already deployed them in the first set of locations.

Sweetgreen launched its Infinite Kitchen technology at its Naperville, Illinois restaurant which leverages automation to dispense greens and other ingredients precisely in bowls moving along in an assembly line.

Other established restaurant brands such as Chipotle, White Castle, and Wing Zone have all deployed Flippy, a kitchen robot that automates fast food preparation.

New restaurant brands are launching in 2024 that have embraced an automation-first strategy. For example, Steve Ells, the former CEO of Chipotle is launching a new chain named “Kernel” in the New York area in 2024. Every location will have just 3 employees supported by robots.

We expect these technologies to find a way to the drive-thru in late 2024 or in 2025 as the technology is perfected and real-world ROI is established.

Groundwork Needed for Drive-Thru Innovation

There are some critical issues in the QSR industry that can potentially derail new drive-thru initiatives. Interface recommends restaurant brands to carefully consider some of these challenges proactively before expanding drive-thru operations.

1. Network Capacity

Designing the physical space and logistics of managing the traffic often takes center stage in drive-thru design while the network side of the solution may take a backseat. Network design and capacity to support mobile POS transactions, sophisticated IP cameras with edge computing capabilities, intelligent ODMBs, order confirmation systems, and perimeter security sensors (such as alarm systems) play a critical role in the successful implementation of cutting-edge drive-thru concepts.

2. Network Security

Personalized drive-thru experiences are enabled only when customers share personal data and convenience is possible only when diverse payment options are supported. As a result, drive-thru concepts have opened up a world of network security vulnerabilities that need to be addressed upfront.

3. Accidents and Claims

Even successful drive-thru concepts have a problem – too many drive-thru customers and spill-over vehicle queues that potentially disrupt neighboring businesses or cause ‘drive-thru rage’. Collisions, liability claims, and employee injury (especially when walking up to cars in the drive-thru lane as done by some QSRs like Chick-fil-A) are potential issues to watch for.

4. Backend Bottlenecks

Considering the success of a drive-thru implementation is contingent on the speed of service and order accuracy, getting the kitchen operations right is an absolute necessity. Integrated kitchen display systems that are connected to the POS and inventory management system can help QSRs handle the increased order volume reliably.

5. Operational Complexity

According to the Franchising Economic Outlook report, the US will have about 192,000 franchise QSR establishments by the end of 2022. While the franchising model offers a proven brand and template for growth, key network and security infrastructure are managed by the franchise owners. This creates operational complexity as standards of implementation and solutions may vary across the chain which imposes barriers to innovation.

Share this article

Innovate Fearlessly and Change Gears with Confidence

Interface experts are ready to help you streamline drive-thru operations.

Schedule a Free Consultation

About the author

Steve Womer

SVP, Engineering

Steve has a passion for simplifying the complex. He has been designing and supporting secure network infrastructure solutions for distributed enterprise brands for the past 17 years. His current mission at Interface Security Systems is to ensure customer solutions are built with the highest levels of security and performance with an overarching theme of standardization and scalability. 

Explore more blog articles

Business Security Video Analytics

Business Video Surveillance Insights for Loss Prevention Teams

Learn how enterprise loss prevention teams should choose cameras for video surveillance.

Read Blog Post

Business Intelligence Restaurants Video Analytics

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

What’s Propelling Restaurant Drive-Thru Innovations?

Read Blog Post

Managed Network & Voice Retail

Retail Network Transformational Insights

Infographic that explains how COVID-19 is driving network transformation among retail chains.

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

6 Game-Changing Retail Technology Trends in 2024

Bud Homeyer — Sun, 08 Jan 2023 18:04:49 +0000

Video Analytics

Bud Homeyer

Chief Operations Officer

Business Intelligence Retail Video Analytics

6 Game-Changing Retail Technology Trends in 2024

Digital Transformation in the Retail Industry

Introduction

The retail industry has already undergone significant transformation in the last decade as prominent retail brands invested heavily in digital transformation underpinned by cloud computing advances and widespread acceptance of e-commerce.

The pandemic in 2020 and the subsequent reopening of the economy have further accelerated changes driven by changing customer expectations and non-traditional demands of Millenials and Gen Z customers. Retailers have no option, but to continue investing in new technologies and stay ahead of the curve.

We look at six emerging yet important retail technology trends that retailers should evaluate in 2023.

1. Contactless Stores

What are contactless stores

Contactless stores refer to a suite of technologies and customer experiences that retail chains have implemented to minimize friction or delays experienced by customers at various touchpoints and minimize human contact in the entire buying experience.

Technologies and processes that enable a contactless buying experience include e-commerce, buy online and pick up in-store (BOPIS), self-service checkout kiosks, NFC-based payment cards, mobile wallets, and cashier-less checkout experiences such as Amazon’s Just Walk Out.

What are the key drivers for contactless stores?

While e-commerce, BOPIS/Curbside, and contactless buying experiences are not new, COVID-19 accelerated the roll-out of contactless technologies and delivery models as customers and retailers pivoted to overcome social distancing norms and safety concerns.

According to Visa, tap to pay transactions in everyday segments in the US, including grocery and pharmacy, have grown more than 100% over the last year (2019). 31 million Americans tapped a Visa contactless card or digital wallet in March 2020, up from 25 million in November, with overall contactless usage in the US growing 150% since March 2019.

According to Square, “Mobile wallets have accelerated in popularity due to the low- or no-touch interactions customers can make in order to complete transactions. And for businesses, the tap-to-pay technology can reduce wait times at checkout.”

eMarketer estimated that BOPIS sales revenue in the United States grew 107% in 2020 and will continue to grow upwards of 15% till 2024.

Technology implications of implementing contactless stores for retailers

Depending on the extent and scope of contactless store implementation, retailers may have to review bandwidth availability, LAN/WAN/Wi-Fi capabilities, network security, and security camera coverage at the store.

Cashierless stores require a bevy of technologies to work together. Computer vision, artificial intelligence-enabled cameras, RFID strips, infrared lead sensors, microphones, and mobile apps work together to offer the convenience of walking in and leaving the store without checking out.

POS system may need an upgrade to offer additional payment options and integrate POS with sensors. In some implementations (such as Amazon’s Just Walk Out), the concept of POS, as we know it today, may not even exist as a virtual shopping cart is updated in real-time as the customer adds items into the basket.

Self-checkout, digital wallets, and BOPIS require a recalibrated approach to loss prevention to address theft and online frauds. According to Visa, “Unlike conventional online orders, a BOPIS transaction may contain less information to leverage in assessing the risk of the order (for example, a BOPIS order may not contain a shipping address). Unlike conventional in-store transactions, a BOPIS transaction doesn’t benefit from the secure capture of the payment, like chip-on-chip or tap-to-pay methods.”

Customer privacy concerns can become an issue when every customer is uniquely identified and tracked throughout the store. While mobile loyalty apps and guest wifi systems are already tracking customer behavior in-store, advanced contactless stores rely on enhanced customer movement tracking which may raise uncomfortable questions regarding customer privacy.

2. Artificial Intelligence (AI) Enabled Security Cameras

What Are AI-Enabled Cameras?

AI cameras use artificial intelligence to make sense of the videos being recorded. They can be programmed to detect certain types of objects or human activity, movement, removal of objects, read license plates or even recognize faces.

AI-enabled security cameras can boost the effectiveness of remote video monitoring or surveillance.

Security operators monitoring the feeds can get real-time alerts when the camera detects any of the anomalies the AI program is trained for thereby allowing security teams to act before a crime is committed.

AI-enabled security camera systems offer a searchable footage library making it easy to quickly find footage of relevance and doing away with the need sift through hours of recorded footage during investigations.

Advanced AI-enabled security cameras have deep learning capability and can become progressively good at recognizing patterns and detecting anomalies in the video being recorded.

Interface’s autonomous Anti-Loitering System includes an intelligent IP camera that uses artificial intelligence to detect people or vehicles and play customizable pre-recorded warning messages.

What Are the Key Drivers for AI-Enabled Cameras?

A recent market study concluded that the global AI camera market was worth $7.4 billion in 2020 and is further projected to reach $33.3 billion by the year 2027, growing at a CAGR of 24.0%.

A combination of factors is driving up demand and use for AI-enabled cameras.

A study conducted by PwC showed that US companies accelerated investments in AI technologies in the wake of the COVID crisis. According to PwC, “AI leaders are building a virtuous cycle, sometimes called a flywheel: AI leads to better products, increased productivity, and superior customer experiences.”

AI technology has matured in the last few years to a point where anyone can access AI frameworks and pre-built solution components on popular public clouds like AWS, Azure, and Google Cloud Platform. The ROI of implementing AI-enabled cameras is now compelling resulting in increased adoption.

The U.S Bureau of Labor Statistics estimates that the labor market for investigation and security services is expected to grow by 6.5%. However, security monitoring service providers are finding it challenging to hire and retain security professionals. AI-enabled cameras can address this issue by delivering increased productivity and improving the quality of monitoring jobs by eliminating monotonous tasks.

5G rollout is turning out to be a catalyst for the growth of sensors with edge computing capabilities. Sophisticated cameras with AI capabilities on 5G networks can push more high-quality video streams faster for further processing and analysis resulting in superior monitoring outcomes.

Technology Implications of Implementing AI-Enabled Cameras for Retailers

Enterprises looking to upgrade analog cameras can take one of the below approaches to executing the transition.

Replace analog cameras with IP cameras (with AI capabilities) along with the cabling. This is a “rip and replace approach” and the investment needed will depend on the number of sites and number of cameras that need to be replaced.

Replace the cameras without replacing the coaxial cables is an option worth considering if the cable runs are complex. In this case, IP to coaxial cabling adapters can push the videos into a video management system.

Start with proven AI security solutions before advancing to solving complex problems that might require additional sensors and sensor fusion. AI use cases such as intruder detection during off-business hours, and loitering in the perimeter area is proven and can deliver ROI faster.

AI security cameras can improve productivity and enhance the effectiveness of the monitoring team and cannot necessarily replace human monitoring. AI solutions do not understand the context of the visuals being recorded and require human review to take vital decisions.

3. Retail Video Analytics

What Is Retail Video Analytics?

Retail video analytics is a relatively new category of retail applications that leverages technologies such as computer vision and AI to capture real-time information from security camera footage.

Most retail chains have installed security cameras at all their stores. These security cameras record vital information that can be used to gain valuable operational insights about retail operations and customer behavior inside the store.

Data that can be captured with video analytics include – customer movement or flow, customer engagement with products and shelves, the effectiveness of the store layout, the impact of online promotions on foot traffic, customer service experience at the checkout, and compliance issues related to product display, spills, and cleanliness.

What Are the Key Drivers for Retail Video Analytics?

There are three primary factors driving the adoption of retail video analytics.

There was a massive shift in retail consumer behavior due to COVID-19. Retailers that had the capability to predict and react to these changes fared better than those that were too slow to respond. Retail video analytics can help retail chains move beyond descriptive analytics and implement predictive analytics to answer questions in real-time such as “What window display unit maximizes footfall conversion for a specific store format?” or “How many checkout counters should be opened between 5 pm to 7 pm on a Friday for a particular location to minimize checkout times?”
According to PwC, “Success at the shelf is no longer about the depth and breadth of inventory, but rather creating engaging experiences for customers.” Creating engaging customer experiences calls for real-time access to customer behavior data in the context of the store design or layout, time, and a slew of external contextual factors.
Profit margins are tight even as retailers retool their operations to cater to changing customer expectations. The only way retailers can find the right business model is to release products in the shortest time possible, gain tactical insights in real-time, and validate the success or failure based on measurable customer actions. Retail video analytics allows retailers to rapidly identify correlations (For example, “what’s the impact of a new layout on sales?”), validate the hypothesis (For example, does a new layout increase sales at all locations or at all store formats?), and consistently implement changes across all locations (For example, are all locations implementing the new layout as per the specifications?”).

Technology Implications of Implementing Video Analytics for Retailers

Implementing a retail video analytics solution is not a complex initiative. However, the real challenge is in identifying the right metrics to track and having the capability to draw meaningful inferences. From a retail IT organization perspective, here are the top considerations when implementing retail video analytics.

The primary sensor for gathering data from a video is the security camera. Security cameras are installed with loss prevention as the primary use case and the installed cameras may not necessarily meet the data gathering requirements for a video analytics project. Camera upgrades and new installations may become a necessity.

The ROI of a retail video analytics implementation is directly dependent on the ability to fuse data from multiple data sources to identify correlations and frame hypotheses about customer behavior. Solutions with well-documented API and integration capabilities should be preferred.

Video analytics solutions can track customer movement, product interactions, and behavior inside the store. When used in conjunction with AI-enabled cameras with facial recognition capabilities, retailers can run the risk of violating customer privacy.

Retail video analytics can be used by diverse departments or teams in a retail organization. Loss prevention, marketing, operations, human resources, compliance, legal, and merchandising teams have compelling use cases for reviewing customer as well as employee activities within the store. A robust system to regulate access to video analytics data is a critical requirement for IT teams.

4. Metaverse

What Is Metaverse?

According to Merriam-Webster, “In its current meaning, metaverse generally refers to the concept of a highly immersive virtual world where people gather to socialize, play, and work.”

Metaverse is still an emerging concept with bits and pieces of the building blocks being assembled and considered work-in-progress.

The following table breaks down the building blocks that together will eventually make up the metaverse (Source).

Metaverse building blocks

Vendors

Experience – What we experience in the metaverse in the form of games, events, or live music.

Meta, Activision Blizzard, Nintendo

Discover – How people find about the existence of experiences in the metaverse.

Facebook, Discord, Unity, App Store, Google Play

Creator Economy – Everything that’s used to create and monetize assets on the metaverse.

Unity, Roblox

Spatial Computing – 3D engine, gesture recognition, spatial mapping, and AI.

Unity, Google AI, OpenAI, Unreal Engine, Matterport

Decentralization – Making everything in the metaverse accessible to all participants and decentralized.

OpenAR, Etherium, Polygon, Ready Player Me

Human Interface – Mobile devices, VR headsets, haptics, and smart glasses.

Oculus, Apple, Playstation, Samsung

Infrastructure– Cloud computing, semiconductor, telecom/bandwidth.

GCP, AWS, Azure Intel, NVIDIA, AMD, Qualcomm, Intel, ATT

The Gucci Gardone on Roblox. Source – Roblox

What Are the Key Drivers for Metaverse Adoption?

A diverse set of factors are forcing retailers to take notice of the metaverse and some retail brands have already invested in creating a presence in the metaverse.

The shift to work from a home model and travel restrictions on account of the pandemic has also brought about a decisive shift to “shop from home” or “shop from anywhere”. For example, as people are more comfortable shopping for clothes online, apparel stores are losing footfall steadily. With e-commerce registering rapid growth, the metaverse can potentially become a competitive advantage in the future as retail brands are looking to create amazing customer experiences.

Retail chains are discovering the value of immersive training experiences that metaverse can provide. For example, Walmart rolled out a comprehensive virtual training program for all their US stores using the Oculus VR headsets. Walmart associates are trained on customer service, store operations, security threats, and BOPIS management through immersive, real-world experiences. Walmart claims immersive training has reduced training duration, improved knowledge retention, and enabled consistent implementation of customer service best practices.

Luxury retail brands such as Louis Vuitton are betting on getting a headstart with metaverse for brand building. In 2021, Louis Vuitton launched Louis The Game, a mobile game with 30 embedded NFTs (non-fungible tokens) that can be found only by playing the game. Balenciaga has launched a division in the company that’s focused on building a presence in the metaverse. Gucci’s Garden Experience on Roblox offers people the opportunity to experience themed rooms to experience the virtual gardens, share their experiences with others and win virtuals prizes. Through metaverse, luxury brands want to get in front of young audiences who may otherwise not otherwise interact with their brands.

Technology Implications of Implementing Metaverse Presence for Retailers

The metaverse is a nascent concept and making any investments in the metaverse has to be carefully calibrated with a clear focus on outcomes. Here are some of the considerations for retail CIOs and management teams looking to join the metaverse bandwagon.

Investing in the metaverse is likely to be a risky venture in terms of meeting business objectives. The metaverse as we have it today falls well short of the seamless interoperability that it aims to provide in the future. Any investments made now on a vendor platform may become irrelevant in the future as industry standards and solution frameworks are still evolving.

According to Gartner, the current maturity of metaverse solutions is collectively called the “Emerging Metaverse”. The emerging metaverse is likely to morph into an “Advanced Metaverse” by 2025 and later into a “Mature Metaverse” by 2028. With time, the technology risks are likely to come down and the ROI of metaverse initiatives will be much clearer for retailers.

Metaverse initiatives are spawning legal challenges and roadblocks for retail brands. StockX, a reseller for sneakers and other items, launched Nike shoes NFTs that can be purchased and traded online. Nike filed a trademark infringement suit. This is an example of some of the potential roadblocks retailers may face when creating a presence in the metaverse.

While there are risks in investing scarce Dollars in a metaverse initiative, being left behind is also not an option for retailers. A better strategy would be to make small bets on a wide variety of metaverse platforms to see what’s working and what’s not.

- Creating a presence on metaverse will require new IT skills either in-house or with the vendors closely aligned to the IT organization. When Home Depot implemented blockchain technology to track vendor supply chain and invoicing issues, they relied on IBM to support the implementation. Another scenario would be when retailers decide to accept cryptocurrency, They need to evaluate not only the technical challenges of integrating a crypto payment gateway but also figure out the most suitable cryptocurrency exchange to encash the payments.

5. Retail Demand Planning

What Is Retail Demand Planning?

Retail demand planning is the process of forecasting demand for products across all channels (in-store, e-commerce, BOPIS, ship from store) taking into consideration historical demand patterns, business decisions and external factors such as competitor offers.

Demand planning helps retailers navigate complex challenges across all aspects of retail operations.

Streamlined store and distribution center replenishment
Better workforce planning and optimization
Optimized product promotions and discounts
Optimized assortment planning
Better space planning and optimization
Improved budgeting and cash flow management

What Are the Key Drivers for Retail Demand Planning?

The pandemic forced retail chains to go through years of growth in just a few months! e-Commerce and new fulfillment channels are no longer seen as a differentiator as customers expect to find the products they want no matter where and how they shop.

The only way retailers can meet these expectations is by upgrading to a data-driven, real-time demand planning approach. Retailers are already upgrading their demand planning capabilities to process more data or variables in the planning process at scale while relying on human planners for qualitative input and exception management.

Here are some of the key drivers driving demand planning innovation in the retail industry.

Trust depends on retailers’ ability to deliver value and excellence in managing the inventory. Having the right product and getting it to their hands in their preferred channel is a great strategy to rebuild trust, According to Walter Robb, Former Co-CEO of Whole Foods, “Some customers say they want to be served in certain ways, such as grocery customers saying they want to pick up items in-store or have certain things delivered. It’s up to brands to develop the capabilities to serve customers how and when they want to be served. Brands earn trust when they listen to customers and are willing to meet their needs.”

Fulfillment complexity is increasing with new channels graduating from a fad to becoming mainstream. In addition to e-Commerce and BOPIS, grocery retailers will soon have one more fulfillment center, i.e the customer’s home. According to Gartner, by 2025, ‘at-home replenishment as a service’ will surge to 5% of multi-channel grocery retailers’ total revenues. Amazon and Walmart are already piloting smart refrigerators and coolers that can be automatically tracked and restocked.

Customer consumption patterns are also evolving and the pandemic created distinct consumption patterns that impacted demand planning for retailers. McKinsey identified four distinct consumption patterns during and after the COVID-19 pandemic:

Pantry load and consume (consumption expands). Example: Cleaning supplies, vitamins, and supplements. Consumption increased during the pandemic and continues to hold ground even after the pandemic.

Pantry load and preserve (consumption does not change). Example: Pet food and toilet paper. Consumption did not actually increase during the crisis, resulting in post-crisis volume declines.

Now at home (consumption shifts). Work-from-home and shelter-in-place policies force consumers to shift on-the-go occasions for products such as coffee and alcohol from in-person food-service outlets to online retailers.

Not now (consumption declines). Declining consumer confidence and a focus on essential categories lead to a decrease in purchasing certain goods during the crisis—for example, beauty, food, and beverages for immediate use. Purchasing levels for these categories are returning to normal after the crisis.

While most retailers have a lot of valuable data, many of them still lag behind in their ability to extract meaningful business insights from the data on time. Considering the retail market is going through a dynamic growth phase driven by changing customer preferences, there is a need for innovative approaches to demand planning. According to Relex, a retail demand planning platform, retailers can bridge the data utilization gap by combining artificial intelligence and machine learning with statistical modeling and optimization, simulation, classification, as well as rules, and heuristics.

Better demand planning requires an ability to crunch data at scale. Advances in in-memory computing, hybrid analytical/transactional data processing, and cloud computing infrastructure that can scale processing on-demand have allowed demand planning vendors to deliver innovative products for realistic scenario simulations.

Reducing food waste is becoming a key challenge for grocery retailers. Increasingly socially conscious customers are looking to spend their money with retailers aligned with similar values. California’s SB1383 legislation mandates grocery retailers to follow specific guidelines to dispose of unsold produce. The goal of this legislation is to minimize produce being dumped in landfills (which contributes to pollution) and instead divert the produce to non-profit organizations. Retailers failing to meet the norms are liable to pay penalties.

Technology Implications of Implementing Retail Demand Planning

The following are some of the factors CIOs and IT organizations should consider when choosing to implement sophisticated demand planning applications.

Among the several critical features required in a retail demand planning platform, Forrester has identified segmenting and clustering, demand management, inventory planning and operational effectiveness, and agile merchandising as core features to be evaluated when choosing a retail demand planning application.

Any plans for a unified demand planning software implementation should take into consideration organizational bottlenecks. If the retailer has planning teams working in silos with each team responsible for specific channels, implementing a demand planning solution that requires closer collaboration and joint decision-making on a daily basis will cause friction and turf wars. Implementing a demand planning software will involve some level of organizational restructuring to leverage all the benefits associated with a collaborative approach to demand forecasting cutting across channels.

Considering the intensive compute requirements for running machine learning and AI algorithms to create demand forecasts, retailers need to budget for cloud computing cost escalations along with fund allocations for backup and disaster recovery.

Any retail demand planning implementation should take into consideration robust data-sharing protocols with suppliers. The applications should have the ability to automatically share demand data at the right level of granularity that the suppliers can then use to plan their deliveries and manufacturing. A feedback loop may also be needed from the supplier end to plan for any variation between demand and supply.

Data quality and data governance are critical to the successful implementation of any demand planning software. Retail chains that have grown through acquisitions and saddled with diverse systems with inefficient data collection or data centralization processes can find it challenging to implement a unified demand planning solution. A focused approach to solving data collection and data quality issues should be in every retail CIO’s roadmap.

6. Generative AI

What Is Generative AI?

Generative AI creates new content, such as images, videos, music, text, or other forms of data. Unlike traditional AI models used by retailers that are primarily focused on classification or prediction tasks based on large data sets, generative AI models are designed to produce original and creative outputs.

Retail chains can leverage generative AI in various ways to enhance their operations, customer experiences, and decision-making processes. Here are a few examples of how generative AI can be used in the retail industry:

Generative AI models can be employed to create realistic product images or videos for e-commerce and catalogs even for items not yet photographed. This accelerates product development and testing without having to invest in manufacturing expensive samples that will never be sold. Merchandising teams can accelerate the process for new product development and display formats.
Generative AI can power virtual try-on applications, enabling customers to virtually “try on” clothing, accessories, eyewear, or cosmetics. By using computer vision and generative models, retailers can overlay virtual representations of products onto real-time video or images of customers, allowing them to see how items would look on them before making a purchase decision.
Retail chains can create virtual assistants and chatbots that can interact with customers, answer inquiries, provide product recommendations, and assist with the purchasing process using natural language responses, making customer interactions more conversational and personalized.

According to McKinsey, In the next three to five years, generative AI could add $150 billion, conservatively, and up to $275 billion to the apparel, fashion, and luxury sectors’ operating profits.

What Are the Key Drivers for Generative AI

Generative AI has rocketed to prominence on the back of several enabling factors that allow this advanced technology to find its way out of research to the mainstream. Here are some of these factors propelling the growing adoption of Generative AI.

Retailers have been grappling with labor shortages. In 2022, we saw the “great resignation” wave and the industry hasn’t recovered from the trend yet. According to the US Chamber of Commerce, the quit rate for the retail trade industry is hovering around 3.3 percent so far in 2023 against a falling national average of 2.6 percent. Generative AI offers a credible solution as retailers find ways to mitigate labor shortages and improve employee productivity.
The cost of AI model training has been coming down making AI accessible to enterprises and startups. According to a report from ARK Investment Management, “AI training cost declines continued at an annual rate of 70%, the cost to train a large language model to GPT-3 level performance collapsing from $4.6 million in 2020 to $450,000 in 2022. We expect cost declines to continue at a 70% rate through 2030.”
Microsoft invested over $10 billion in OpenAI in January 2023 as the company laid out a plan to integrate OpenAI’s ChatGPT with Azure to enable customers to build enterprise-grade AI applications. The speed with which ChatGPT has found traction among consumers has also created a credible proof-point for retailers to embrace Generative AI.
CIOs are already investing in building AI applications. According to this report from Databricks, 60% of CIOs surveyed planned to deploy AI-based solutions across all departments by 2025.

Technology Implications of Implementing Generative AI Applications for Retailers

According to the World Economic Forum, “Many organizations are underprepared for AI, lacking the proper oversight and expertise from key decision-makers to manage risk.” The truly transformational nature of Generative AI comes with the risks associated with venturing into a relatively new territory for retailers. Here are some of the technology implications for retailers planning on implementing Generative AI applications:

Generative AI models often require large amounts of data for training. Retail chains need to ensure they have the necessary data infrastructure to collect, store, and process the data efficiently. This may involve implementing data management systems, data pipelines, and scalable storage solutions.
Training and running generative AI models can be computationally intensive. Retail chains may need to invest in powerful hardware or leverage cloud computing services to handle the computational requirements. According to Tirias Research, Generative AI’s data center costs are projected to surpass $76 billion by 2028, potentially impacting the profitability of services like search, content creation, and business automation.
Developing and training generative AI models requires expertise in machine learning and deep learning techniques. Retail chains may need to hire or collaborate with data scientists and AI specialists to build and fine-tune these models. They also need to allocate time and resources for model training and experimentation.
Generative AI solutions need to be integrated with existing retail systems and workflows. This may involve connecting with inventory management systems, point-of-sale systems, customer databases, and other relevant systems. Integration may require developing APIs or middleware to facilitate data exchange and communication.
Generative AI can raise ethical concerns, such as the potential for bias or misuse of generated content. Retail chains need to be aware of these considerations and establish guidelines and frameworks to ensure fairness, transparency, and responsible use of the technology.
Once the generative AI solution is deployed, it requires ongoing monitoring and maintenance. This includes monitoring the model’s performance, addressing any issues or errors, retraining the model periodically to improve its output quality, and staying up to date with the latest advancements in generative AI research.

Share this article

Transform retail operations with Interface

Find out how retailers can uncover valuable customer behavior insights to create an amazing in-store experience.

Schedule a Free Consultation

About the author

Bud Homeyer

Chief Operations Officer

Bud Homeyer is the Chief Operations Officer at Interface Systems. Having worked as an IT and security leader for leading consumer-facing brands like Michaels, Brinker, and Bank of America, Homeyer has a proven track record of solving complex enterprise-wide challenges to drive growth, productivity, and profitability. He spearheads Interface’s efforts to help customers embrace new technologies while minimizing risks.

Explore more blog articles

Business Security

5 Essential Steps to Create a Lone Worker Safety Policy

In-depth lone worker safety policy guide with actionable steps and templates

Read Blog Post

Restaurants Retail

Making IT Happen – The Interface Blog for Distributed Enterprises

The worldwide climate is uncertain right now. We are facing a health crisis unlike anything we’ve seen

Read Blog Post

Business Security Managed Network & Voice

5 Technology Solutions For Essential Business Services

Technologies IT and Loss Prevention Leaders Should be Adopting or Evaluating

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

Retail Store Layout Optimization with Video Analytics

Steve Womer — Fri, 06 Jan 2023 20:00:01 +0000

Video Analytics

Steve Womer

SVP, Engineering

Business Intelligence Retail Video Analytics

Retail Store Layout Optimization with Video Analytics

Introduction

What is Retail Store Layout?

Retail store layout refers to how brick-and-mortar retailers set up product displays, fixtures, and merchandise in their stores. A well-planned store layout can positively influence customer experience, a critical factor to drive product engagement, sales, and improve customer lifetime value.

Retailers have several tools to gather and analyze data to understand if the store layout is working well and identify problem areas that need optimization. Some of these tools include store audits, mystery shopping, and customer surveys or shopper feedback.

However, there are three fundamental limitations of using these measurement techniques for evaluating store layout effectiveness.

Some of the observations may be subjective or subject to interpretation.
Observations or feedback from a customer or from a store audit may or may not be consistently true across all locations or at all times.
There is no way to access real-time data on store layout performance using any of these traditional measurement methods.

Video analytics addresses these limitations as it is driven by aggregated data, captured and processed in real-time, at all locations where the store layout is being monitored.

That’s not all. Video analytics can be implemented by leveraging security cameras that the store may already have in place. Click here to learn more about video analytics.

In this blog post, we will explore how retail chains can optimize store layout using video analytics.

Types of Retail Store Layouts

Let’s explore the pros and cons of retail store layouts along with examples of prominent retail chains and categories employing these strategies.

Grid Layout

Pros:
Easy navigation for customers.
Efficient use of space, allowing for a high product density.
Simplifies inventory management and restocking.

Cons:
Lack of uniqueness in design.
Limited opportunities to create focal points or highlight specific products.
Example: Large format retailers like Walmart and Target often adopt a grid layout to streamline the shopping experience and accommodate a vast array of products.

Loop or Racetrack Layout

Pros:
Encourages exploration as customers follow a predefined path.
Promotes impulse buying with strategically placed displays.
Ideal for larger stores with a wide product range.

Cons:
Potential for congestion and bottlenecks, especially during peak hours.
Limited flexibility in creating distinct shopping zones.

Example: IKEA, a furniture and home goods retailer, utilizes a loop layout, guiding customers through various showroom sections and strategically placing smaller items in the pathway to encourage additional purchases.

Free-Flow Layout

Pros:
Offers a relaxed and casual shopping environment.
Encourages creativity in display and decor.
Allows for easy adaptation to changing merchandise or seasonal themes.

Cons:
Challenges in guiding customer flow and promoting specific product areas.
Risk of customers missing certain sections of the store

Example: Apple Stores, known for their electronics and tech products, often feature a free-flow layout, allowing customers to interact freely with products, creating a more personalized and engaging experience.

Angular Layout

Pros: Creates a visually interesting and dynamic store design. Facilitates the establishment of distinct departments or product categories. Encourages customers to explore different sections of the store.

Cons: Requires careful planning to avoid confusing navigation. May result in underutilized space in corners and angular areas.

Example: Zara, a fast-fashion retailer, often employs an angular layout to create visually striking displays and highlight specific clothing collections.

Geographic Layout

Pros: Organizes products based on their intended use or category. Provides a logical and intuitive shopping experience. Enhances the customer’s ability to find specific items easily.

Cons: Limited flexibility in adapting to changing merchandise or promotional displays. Challenges in creating a visually appealing overall store design.

Example: Best Buy, specializing in electronics and appliances, organizes its stores based on product categories, adopting a geographic layout to simplify the customer’s search for specific items.

Mixed-Use Layout

Pros:
Combines elements of different layouts for a customized approach.
Offers flexibility to cater to various product categories.
Allows for creative and innovative store design solutions.

Cons:
Requires careful planning to maintain a cohesive and harmonious overall look.
Potential for confusion if not executed seamlessly.

Example: Sephora, a beauty and cosmetics retailer, often adopts a mixed-use layout. The store seamlessly integrates grid-like shelving for a wide range of products, while also incorporating free-flowing beauty stations that encourage customers to experiment with makeup and skincare products, creating an interactive and personalized shopping experience.

Significance of retail store layout

Before we explore the various strategies to deploy video analytics for measuring store layout effectiveness, let’s understand how retail layout has a direct impact on customer satisfaction and store performance.

1. Create a great customer experience

The massive shift to ecommerce and BOPIS (Buy Online and Pickup in Store) has turned the spotlight on in-store customer experience.

Even pure-play ecommerce brands like Amazon are opening brick-and-mortar locations to offer customers the experience of traditional shopping with never-before-seen convenience.

Customer experience is probably the single most important tool that brick and mortar retailers can use to give customers enough reasons to come back to the store boosting chances for engagement and conversion.

Retail chains with the capability to measure and monitor changes in customer experience can make changes in the store layout so that product categories that are in high demand can gain prominence.

REI has created a unique in-store experience that includes a combination of interactive displays, expert sales staff, and in-store activities that give customers who enjoy the outdoor lifestyle plenty of reasons to visit an REI store.

2. Increase sales

A good store layout plus customer flow combination can increase sales of even the most underperforming product. A layout that reflects specific shopper missions and needs can help customers achieve their mission and increase sales of products that meet those mission requirements. Here is an illustration of how store design elements can help a customer accomplish their mission.

Customer Mission: I need to wrap up shopping before the meeting.

How Store Layout Can Help: Layout that places popular product categories prominently

Store map at entrance: Improved signage for all departments with popular products listed on the signage

Customer expectations, needs, and wants are dynamic and retailers with the ability to optimize and reinvent store layout can turn challenges into new sales opportunities.

For example, putting BOPIS or click-and-collect counters near the store entrance makes it more likely that customers will use this service in the future, helping retailers capture more of this market in the future. Since the click-and-collect market in the U.S. is forecast to grow to $120 billion and beyond by 2023, this type of store layout option can increase overall sales dramatically for retailers.

3. Manage stock more efficiently

Managing space optimally can maximize sales, minimize stockouts. improve employee productivity and align with the objectives of the store itself.

For example, a store that’s designed to introduce new products and carry little inventory is designed to maximize product engagement with checkout counters taking the backseat completely as employees focus on product engagement and possibly help customers place online orders at the store. A classic example of a store design that focuses on product engagement is the Apple store.

A store that’s focused on convenience and breadth of assortment such as a specialty grocery store has to be designed for easy access and having enough space for carrying all the assortments.

Trader Joe’s small format stores focus on convenience and quick access to a wide variety of specialized grocery and food items. Their design is easy to work with not only for customers but also for employees. Their inventory management and ordering is perfectly timed with demand and shelf breaches (items being placed outside the designated areas) or prolonged stockouts is never a problem as the store layout gives easy visual and physical access to all aisles.

4. Minimize theft

According to the 2020 NRF Security Survey, retail shrink is at an all-time high, accounting for 1.62% of a retailer’s bottom line — costing the industry $61.7 billion. While retailers use a variety of technology solutions such as video surveillance, protective display cases with locks, chords, EAS (electronic article surveillance), retail store layout is one of the many factors that determine the success of loss prevention efforts.

Some of the store layout and design principles that minimize theft and an assortment of inventory losses include:

A design that offers a clear line of sight for employees at the checkout counters to all parts of the store.
A layout that doesn’t obstruct camera views or signals from EAS installations.
A layout that avoids cramped spaces and allows employees to identify misplaced items quickly.
A design with well-planned exits that minimizes chances of snatch and grab thefts.

5. Improve safety and accessibility

Safe retail store design keeps employees safe from environmental and health hazards. A store layout that’s accessible ensures anyone can access the store regardless of ability.

Depending on a store location, any retail layout has to comply with regulations and policies associated with safety, security, and accessibility.

A well-designed retail store will take into consideration a number of design parameters that directly impact safety and accessibility. Here are some examples:

A store layout with aisles and customer paths wide enough to accommodate wheelchairs with adequate ramps and accessible facilities throughout the store.
Ergonomically designed display units or shelving to prevent injuries for customers or employees handling the product.
Store layout designed for proper airflow and ventilation throughout.
Stores with properly designed flooring and elevated platforms to avoid trips or falls.

Designing an accessible store layout is good business. According to the United States Department of Justice, “More than 50 million Americans with disabilities are potential customers for retail businesses across the country. These 50-million-plus customers, along with their families and friends, patronize clothing boutiques, mall outlets, grocery stores, and more, if the businesses are accessible. This market grows even larger if the 78 million baby boomers in this country – who do not always require but benefit from accessibility – are included. Accessibility makes good business sense: an accessible retail establishment brings in new customers and keeps them coming back again and again.”

Store layout optimization strategies using video analytics

1. Streamline customer flow

Video analytics is well suited to map and measure customer flows through the store. Understanding customer flow helps retailers evaluate the effectiveness of the store layout, understand the best possible placement of products, measure customer actions at every section or department, measure the impact of specialized displays, in-store promotions, or marketing campaigns, to name a few.

Video analytics, when combined with POS data, can help retailers conduct a real-time audit of the store layout to identify bottlenecks in the design, and align the layout to help customers successfully accomplish their shopping missions.

Here are some of the ways video analytics can help retailers troubleshoot store layout issues to improve customer experience and revenues:

Use pathmap metrics to understand how customers move around in the store. Redesign the store layout or make changes to problem areas in the store to drive desired customer actions such as better footfalls in previously low activity areas or reorganize the placement of products to help customers get what they want faster.
Identify and eliminate ‘dead zones’ in terms of footfall activity or engagement and take remedial actions such as better signage, lighting, or a redesigned layout.
Use traffic data at store entrance and exits or department/category entry and exits to measure overall or department/category level conversion metrics. Analyze conversion metrics together with other factors that determine conversions such as weather or seasons. Test hypothesis on reasons for conversion with a/b testing spanning layout, product placements, promotions, or in-store displays/announcements.
Track dwell time across the store to understand customer interest in specific products as well as flow bottlenecks that force customers to wait longer than expected such as in the checkout areas. Use these insights to offer more products that customers want or reorganize the checkout flow to reduce wait time.
Dwell times at entrances of different departments can measure bounce rates and call attention to better product placement, staff engagement to bring guests further into the store.

Store floor plans dictate customer flow and how customers interact with the products. Irrespective of the type of store layout or floor plan (grid layout, herringbone, free-flow, geometric, mixed, to name a few), video analytics can play an important role in uncovering real-time business intelligence on how the layout is performing. The pathmap overlay on the video stream from the overhead camera offers valuable data on how the layout is impacting customer flow through the store.

2. Delight customers with a better checkout experience

The last impression is probably the best impression for retail chains looking to provide a memorable customer experience. A long checkout queue can completely wipe out any positive experience customers might have had at the store before they wanted to checkout. In some cases, customers in a hurry can just abandon their carts and never return to the store!

Retailers have already implemented an assortment of improvements to make the checkout process efficient. These include changes in how queues are organized, self-checkout kiosks, app-based self-checkout, shelves near the checkout counters to entice impulse purchases, to keep the process predictable and customers engaged as they wait for their turn to pay.

Video analytics can help retailers use real-time data to understand what’s really happening at the checkout area.

Because video analytics offers vital video “evidence” that retailers can see first hand to understand queue efficiency and cart abandonment.
Video analytics can identify dwell times at queues to calculate the average waiting time for a customer and use the data to plan for additional checkout lanes or self-checkout counters in addition to ramping up staffing levels to meet periodic demand surges.
With video analytics, retailers have the flexibility to conduct data-driven tests when making significant changes to the checkout area design flow before rolling it out to the rest of the stores. The impact of layout changes on the average transaction value and items per transaction can help retailers take a decision on the revamped store layout.

Here is an example of a report from Interface’s video analytics solution that provides average dwell time waiting in queue and the average time at the checkout counter. This data can be viewed in the context of how effective a new checkout experience or layout is. In addition, this data can be mapped to other factors such as time of day, day of the week, holidays or staffing levels:

3. Improve product placement

Product placement is probably one of the most important factors that impact retail sales and is closely tied to the store layout.

While planograms offer the template to slot products in the shelf space, real-time data-driven decisions can help retailers maximize sales by aligning shelf space to customer preferences and other factors that drive purchases such as the weather or local events.

Video analytics can be a game-changer in giving retailers instant visibility on potential product placement issues and identifying opportunities to maximize basket size.

Some of the insights retail video analytics can uncover to improve product placements include:

Hotspots around display units and shelves to precisely identify the products that customers are looking at or interacting with. This allows the retailers to identify products that need to be relocated to boost sales or change the assortment around the hotspots to promote cross-sell.
Retailers can look at dwell time data to understand what might be causing customers to interact with the products in shelves with high dwell times and find a correlation to other factors such as time of the day, packaging, marketing campaigns (in-store or online), or any other factor that might be driving increased dwell time.

Retailers with data on the performance of shelf space across product categories and departments can optimize the store layout and display units or even change the design of the store to offer most product categories the best possible exposure to customers.

Video analytics can empower local teams to make store layout decisions based on real-time data while ensuring planogram compliance or even using data as evidence to change the planogram.

Here is a heatmap view from video analytics that precisely highlights the product displays that attracted maximum customer interactions or engagement. Using this data in conjunction with sales data or marketing campaign calendar can uncover challenges and opportunities with the product placement tactics or even store layout changes to improve performance.

4. A/B test store design or layout changes

The practice of A/B testing is a common practice to test or validate ecommerce sites and online experiences. With video analytics, retailers have the capability to conduct real-time, data-driven A/B tests to validate the effectiveness of the store layout or a specific component such as a brand new display unit measured in terms of dwell time, heatmaps, and sales conversions.

In addition, video analytics also allows retailers to A/B test the effectiveness of store design on new customer behaviors such as BOPIS. For example, video analytics can help find answers to questions like “Would it make sense to design the in-store pickup area to showcase products that are not available online?”.

Here are four different product display designs and the associated pathmaps of customers interacting with the displays generated by the Interface video analytics solution

With video analytics, retailers have the flexibility to test any number of store layout or design variations across multiple locations at a time. This is a useful feature that allows retailers to

Conduct multivariate A/B tests with the right sample size
Ensure tests run for the required duration to reach the threshold KPI uplift

5. Supercharge merchandising tactics

The merchandising function is at crossroads as retailers scramble to offer an omnichannel customer experience and stay ahead of evolving customer expectations. Technology solutions, like video analytics, can play a significant role in helping merchandising teams recalibrate their priorities, and become agile to keep pace with changes.

According to McKinsey, the merchandising function will be driven by automation and here is how video analytics can help enable the transition to agile merchandising.

Merchandising area of responsibilities

How video analytics can help

Merchandising planning

Video analytics, when combined with POS data, allows merchandising teams to get real-time visibility on customer demand for categories, assortments, sizes in addition to predictive insights on how they are impacted by geography, time, and events right down to the store level.

Pricing and promotion

With video analytics, retailers can see how pricing and promotions impact customer walk-ins, product engagement, and sales giving merchandising teams complete visibility into the sales funnel. This insight is valuable to make pricing adjustments or recalibrate promotions to drive sales.

Assortment planning

When real-time customer engagement data at the shelf level from video analytics are combined with sales data, retailers can optimize assortment planning and change shelf space allocation or placement of specific assortments to maximize sales and profits.

Space planning

Video analytics can provide real-time feedback on the effectiveness of the planogram in driving engagement and giving customers easy access to the products they want. This data can become the basis for a feedback loop to improve the planogram and use the shelf space better.

Here is an example of customer engagement data for a display unit. Merchandisers can use this insight to manage shelf-level displays or even floor layouts. In addition, inventory checks and audits can be done in real time without waiting for onsite audits.

6. Improve storefront design

Storefront design has always been a major factor in retail success. When done right, creative storefronts make new customers feel curious and existing customers satisfied with their choice.

Video analytics can help retailers gather valuable data to improve the performance of storefront design.

Heatmaps and dwell times can be used to understand which display elements are attracting attention.
Changes in display design or layout can be put through an A/B test to measure improvements in engagement and walk-ins.
Pathmaps can show how many people walk past the storefront (bounce rate) and what percentage of people walking by enter the store.
All of the above insights can be correlated to other data such as holidays, time of day, day of the week, promotions, online campaigns to name a few to give a better insight on storefront designs that encourage desired customer behavior.

Different storefront window treatments can have their effectiveness measured via customer entry counts.

7. Ensure layout and design compliance

There are three reasons why store layout and design compliance is a major operational requirement in retail chains:

One of the key promises of a brand is delivering consistency at every touchpoint. In-store design and layout is an important factor that helps retailers create a unique yet consistent experience for customers.
Layout and design compliance is also a key requirement for brands that may have paid for premium shelf space or set up special display areas. Retailers rely on physical in-store audits to verify design or layout compliance across stores.
Ensuring that the store layout does not cause unintended issues such as closed spaces, bottlenecks, or blocks access to lighting or surveillance which might contribute to poor safety or health hazards for employees and customers.

Video analytics offers retail compliance, marketing, and merchandising teams monitor store layout and design compliance at scale across a large number of locations. The screenshot below demonstrates how Interface’s video analytics solution enables a visual verification of layout and design compliance across stores.

In addition to monitoring layout compliance in real-time with no need for physical audits, store managers can use video analytics to spot maintenance issues, identify stockouts, and validate if compliance violations are fixed properly.

Share this article

Transform retail operations with video analytics

Find out how retailers can uncover valuable customer behavior insights to create an amazing in-store experience.

Schedule a Free Consultation

About the author

Steve Womer

SVP, Engineering

Explore more blog articles

Business Intelligence Retail Video Analytics

6 Game-Changing Retail Technology Trends in 2024

Retail technology trends in 2024 - Contactless Stores, AI-Enabled Security Cameras, Retail Video Analytics, Metaverse, Retail Demand Planning

Read Blog Post

Managed Network & Voice

Top SD-WAN Vendors in 2024 & How to Select One for Your Enterprise

We reviewed all the top SD-WAN vendors for 2024 and included a handy guide to help you choose a SD-WAN solution that will meet your business needs.

Read Blog Post

Business Intelligence Retail Video Analytics

Retail Store Layout Optimization with Video Analytics

Get actionable tips to leverage video analytics for retail store layout optimization to improve customer satisfaction, sales, and compliance.

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

Business Video Surveillance Insights for Loss Prevention Teams

Don Fruhwirth — Thu, 05 Jan 2023 17:17:47 +0000

Video Analytics

Don Fruhwirth

Director Product Management

Business Security Video Analytics

Business Video Surveillance Insights for Loss Prevention Teams

Introduction

The National Retail Federation reported that retailers lose about $700K for every $1 billion in sales to organized crime and theft.

Loss prevention teams in distributed enterprises and businesses such as retail and restaurant chains are ramping up investments in advanced video surveillance solutions in addition to tightening return policies, point of sale monitoring, and employee screening.

However, getting the basics right when implementing a business video surveillance system can provide a significant boost to the effectiveness of sophisticated loss prevention solutions.

In this blog post, we will cover:

How to choose CCTV cameras that can get the job done
Impact of camera technology on solution design
Camera placement best practices for video surveillance
Why vendor selection is critical for implementing the right solution

What is business video surveillance?

Business video surveillance refers to monitoring a place of business such as a retail store or office with CCTV cameras. The primary reasons for monitoring a place of business are to secure the business, gather evidence of a crime, and reduce instances of fraudulent liability claims.

There are various types of video surveillance used by businesses depending on the security needs and size of the business.

Onsite CCTV Monitoring – Small businesses such as independent stores or restaurants install CCTV (closed-circuit television) cameras with the footage being monitored and stored at the same location. The primary purpose of onsite surveillance is to dissuade crime, identify perpetrators of crime or theft, and assist law enforcement in investigations.

Remote Video Surveillance – Distributed businesses with a need to monitor security camera footage across multiple locations rely on a central monitoring location that gets direct or live Internet feeds from video surveillance systems installed at all the locations. Remote video surveillance involves the implementation of sophisticated video streaming, data storage, and video management software and provides advanced monitoring and video analysis capabilities to loss prevention teams.

Interactive Remote Video Surveillance – With remote video surveillance, the team that’s monitoring security camera feeds from a remote location can see what’s happening at all the locations but they can neither hear nor speak to the people at the store directly without picking up a phone. With Interactive video monitoring, the remote video surveillance team can hear and speak to the people being monitored via microphones and speakers installed at the location. With interactive remote video monitoring, loss prevention teams can perform additional tasks such as:

Virtual tours to monitor all corners of the store or business location and identify vagrancy or undesirable activity around the business location or store.
Voice-downs to deter shoplifting, enforce social distancing, or make announcements related to operations compliance based on specific events like a door opening or delivery personnel entering a location.
Virtual escorts to help employees with cash movement, store opening/closing, or moving between secure locations.

The following sections explore video surveillance best practices that business owners and loss prevention teams can leverage to improve security and prevent loss.

Find out how Panda Express uses Virtual Guards and Virtual Escorts to proactively secure their operations.

Read the Case Study

1. Choosing the right camera for the job

Security cameras used by businesses for video surveillance come in many shapes with different feature sets, technology, and applications. Choosing the right camera for meeting a specific objective is critical for loss prevention teams.

Indoor Vs Outdoor Cameras

Broadly, there are two types of cameras depending on where they are deployed – Indoor cameras and outdoor cameras. For commercial video surveillance applications, cameras rated for outdoor deployment are preferred for three key reasons.

Indoor environments in businesses such as restaurants and industrial units have smoke, dust, and grease. For example, deploying indoor-rated cameras in a fast food joint may be a bad idea as cameras can be coated with grime or grease. Indoor-rated cameras become unserviceable in such environments whereas outdoor-rated cameras can remain functional as they are designed to keep dust and grease out.
The price differential between indoor and outdoor cameras has come down over the years and outdoor cameras have a minimal cost differential to an indoor camera. The higher cost for outdoor cameras can be easily justified as they outlive indoor cameras and offer greater ROI for businesses.
Outdoor cameras are designed to withstand heat, moisture, snow and work well in commercial establishments where perimeter security requirements such as in drive-through areas and parking lots are as important as security inside the premises.

Some businesses, such as car wash centers, have unique monitoring requirements. For example, cameras inside the car wash tunnel should be able to withstand water and moisture without fogging the lens. In addition, camera feeds need to be integrated with tunnel optimization software. Find out how Mister Car Wash tackled these challenges.

Read the Case Study

Camera types and applications

Mini Dome Cameras

What are mini-dome cameras?
Mini-dome cameras are compact, versatile cameras that are cosmetically appealing and come with a wide variety of features that make them suitable for a wide range of applications.

What are the features of a mini-dome camera?
Mini-dome cameras have a mid-size form factor. The lens in these cameras is not clearly visible making it difficult to see where the camera is aimed thereby improving its overall effectiveness as a surveillance tool.

Mini-dome cameras are available with fixed and variable focal length lens options, remote-focus controls, wide dynamic range (WDR) capabilities that improve overall image quality when looking out doors or windows by creating a balance between the dark and bright areas of an image.

Some of them have infra-red (IR) illuminators and sensors for visibility in low/no light conditions, and built-in analytics capabilities, such as line-crossing detection, making them useful for a variety of monitoring requirements.

What are the use cases for mini-dome cameras?
Because they are both indoor and outdoor rated, mini-dome cameras can be used almost anywhere for a multitude of applications – lobbies, hallways, production floors, parking areas, entries/doors, sales areas. Outdoor versions are often used in indoor applications such as in kitchens and in freezers or coolers due to their weather-resistant capabilities.

Outdoor applications require proper planning as a poor choice of installation locations can expose the camera and internal parts to direct sunlight often resulting in overheating and a shorter life span.

Micro Dome Cameras

What are micro-dome cameras and how are they different from mini-dome cameras?
Micro-dome cameras are similar to mini-dome cameras but are smaller, thinner, often surface-mounted and less obtrusive. They have similar features as mini-domes but due to their smaller size may not have variable-focus lens options typically available with a mini-dome camera.

What are the features of a micro-dome camera?Micro-dome cameras have a similar set of features as a mini-dome but are generally available only with fixed-focal-length lenses.

What are the use cases for micro-dome cameras?Typical use cases for micro-dome cameras include observing checkout areas in retail and quick-service restaurants, ATMs, hallways, or walkways or anywhere a smaller size, less obtrusive camera may be desirable.

Turret Cameras

What are turret cameras?
Turret cameras are often called a flat-faced dome or eyeball camera resembling a sliced sphere in a ball-and-socket joint design which can be swiveled around in its “socket” once the base of the camera has been mounted. A turret camera has compact dimensions with the lens inside a housing as opposed to a dome.

What are the features of a turret camera?
Turret cameras have most of the features of mini-domes (fixed/varifocal, WDR, IR). Some turret cameras may have an IR feature known as EXIR, or extended infrared, a design where the camera lens and IR LEDs (light-emitting diode) are housed behind two separate windows which can eliminate infrared glare that is sometimes encountered in mini- and micro-dome cameras.

They are easy to install on a flat surface such as a ceiling or wall, rated for outdoor applications, and have a hardening rating to resist tampering or vandalism. The lens and internal components are better protected from environmental factors such as sunlight and moisture making them well suited to outdoor installations.

What are the use cases for turret cameras?
Turret cameras are used for observing sidewalks, entries, exits, drive-up lanes, or parking lots. They can also be used for indoor applications such as in kitchens as they are resistant to smoke, grease, and dust. However, unlike dome cameras, people being observed know where the turret camera is aimed at.

Bullet Cameras

What are bullet cameras?
Bullet cameras have a cylindrical shape, come in different lengths and sizes, are capable of observing long distances, and can be fairly noticeable. At a glance, anyone can see where bullet cameras are aimed and focused. Bullet cameras are most commonly used in outdoor applications, so their cases are made resistant to water, dust, and dirt.

What are the features of bullet cameras?
Bullet cameras have most of the features of other cameras (fixed/vari-focal, WDR, IR/EXIR) and while designed for both indoor and outdoor applications, are well suited to outdoor as their design protects the lens and internal components from direct sunlight and the elements.

They are well-built and outdoor cameras are designed to be vandal resistant. Bullet cameras are highly visible so they can also be used to act as a deterrent.

What are the typical use cases for bullet cameras?
They are suitable for outdoor applications such as parking areas, the entry and exit of people or vehicles to a facility. Due to their conspicuous design, they clearly indicate your premises are under video surveillance. They can be easily installed on a flat wall and they have the ability to withstand harsh environmental elements such as sunlight and storms.

Small-sized bullet cameras can be used for indoor applications where discreet monitoring may be needed from a distance, such as in a high-end boutique where a camera directly over the sales counter may not be desirable

PTZ Cameras

What are PTZ Cameras?
PTZ stands for pan, tilt, zoom. PTZ cameras are also called pendant cameras. PTZ or pendant cameras not only contain the lens, but they also let you rotate the camera to get up to 360 degrees of camera rotation when the installation allows for it.

What are the features of a PTZ camera?
PTZ cameras give operators the flexibility to focus and zoom on any object in its field of view.

Some PTZ cameras can be programmed to perform a tour of the area being monitored. The program can also include additional actions such as automatically focussing on specific events such as the opening of a gate or door. Once the area of interest or activity is recorded, the camera can resume the routine tour.

What are the typical use cases for PTZ cameras?
PTZ cameras are designed to monitor a large area, such as a big parking lot or a large indoor space. It is generally advisable to consider using other camera types if the objects being monitored are either fixed or if the area being monitored is relatively small as PTZ cameras are expensive and probably require more maintenance as they have moving parts

Box Cameras

What are box cameras?
Box cameras house the camera lens in a box and have a similar construction found in a bullet camera. Box cameras are among the oldest camera models but continue to be used even today.

What are the features of a box camera?
Box-type cameras allow loss prevention teams to design the camera capabilities needed for video surveillance depending on the application.

For example, if the requirement is for a specific lens type and specification to observe an object of interest, a box camera can be designed to perform just the task.

What are the use cases of a box camera?
Box cameras are typically used for indoor applications. For outdoor applications, a box camera will need suitable housing to protect from heat, dust, and cold.

Box cameras may also be not suitable for recording in the dark or at night as most of them don’t have built-in IR capabilities and rely on a separate IR lighting system.

Box cameras require mounting hardware for all applications and this can add to the cost of installation or deployment when compared to other camera types

Fisheye Cameras

What are fisheye cameras?
Fisheye cameras utilize ultra-wide-angle lenses that are intended to create a wide panoramic or hemispherical image and achieve extremely wide angles of view.

Instead of producing images with straight lines of perspective, fisheye lenses use a special mapping, which gives images a characteristic convex appearance.

A common type of fisheye camera is known as a 360-degree camera which has an extremely wide-angle view of a large area, and produces a circular image. 360-degree cameras are typically mounted on the ceiling.

What are the features of a fisheye camera?
Fisheye cameras are designed to offer a general overview of where things are and what’s happening in a fairly large area under observation. They are not designed to capture the facial features needed to identify specific individuals.

Some fisheye camera models offer image de-warping features designed to remove the distortion associated with a wide-angled view of the video or image. While the de-warping feature generates multiple panoramic views, it is still not suitable for identifying faces.

What are the use cases for a fisheye camera?
Fisheye cameras are well suited for video analytics applications such as tracking the movement of people within a store, engagement with products or displays and creating heatmaps of activity in a particular area of the store

A fisheye camera shown here is used to generate a pathmap of customers who visit the store. A pathmap helps visualize and quantify how customers move within the store to help make decisions on store layout or determine display effectiveness at various parts of the store. Click here to learn more about how security cameras can uncover business insights in retail chains.

2. Implications of camera technology on security solution design

Camera technology has been rapidly evolving and businesses or enterprises looking to set up a video surveillance system at new locations or upgrading their legacy analog cameras now have to grapple with the plethora of technology choices and features.

Loss prevention teams looking to maximize ROI from security investments must tread carefully when designing CCTV upgrades or new installations.

This section provides an overview of the various camera technology options available along with a handy reference table that showcases practical applications of myriad camera features.

Camera types based on technology

In general, cameras can be classified on the basis of the technology that goes into the components and how videos from the camera are processed and stored. Each of these camera technologies has their advantages and disadvantages as outlined in the table below.

Analog Cameras

The original video recording method that stores continuous (analog) waves of red, green and blue intensities.

Traditional analog cameras measure resolution by the number of horizontal lines called TVL (TV Lines). A higher number of lines in an image means better resolution.

Advantages
Has been around for over 30 years. “Tried and true” and total TVL resolution has increased significantly over the years.

Disadvantages
Limited resolution (<720P).

HD Analog Cameras

HD Analog video security cameras deliver megapixel resolution video over coaxial cabling (HD over coax) and use digital vs. analog signals to transmit video.

Advantages
HD analog technology allows you to record megapixel resolution video (1080p, 4K) over standard coax cabling, which is often already installed in your location.

Some benefits of HD analog include lower camera costs when compared to other technologies, simpler installations using the same process already in place for standard analog cameras, and the ability to upgrade or add HD analog cameras while retaining existing cameras.

HD analog cameras come in a wide range of features, styles and form factors, making them easy to fit into any location.

Disadvantages
You will likely need to upgrade your video recorder to be able to add HD Analog cameras. Older analog recorders do not support the HD analog standards.

There are multiple HD Analog formats (HD-TVI, HD-SDI, HD-CVI and AHD) with HD-TVI being the most prevalent. Hence, you must choose cameras and recorders that use the same standard.

IP Cameras

Internet Protocol (IP) cameras are a type of digital video camera that connects to your Ethernet local area network (LAN) and uses TCP/IP signaling to transmit video in a digital format.

Advantages
IP cameras come in a large variety of resolutions (720p to >8MP), form factors, and features giving you great flexibility when designing your surveillance system.

These cameras use the same category wiring (Cat5/5e/6) used for your computer network and can use Power over Ethernet (PoE) to power the cameras.

Many IP camera models support local storage using memory cards and have advanced analytical and AI capabilities available out-of-the-box.

Disadvantages
Often even “compatible” cameras and video recorders have exacting requirements to support the desired functionality.

When using IP cameras, it is considered a best practice to use video recorders from the same camera manufacturer to ensure full compatibility and access to advanced camera features.

IP cameras require ongoing maintenance to keep their operating system (firmware) up to date to prevent these devices, and potentially your network, from being compromised due to security vulnerabilities.

Thermal Cameras

A thermal camera detects infrared (IR) energy (heat) emitted from the object and converts it into a visual image. The resulting image (i.e. a person) is displayed with various colors representing the approximate temperatures on the object.

Advantages
Thermal cameras are specialty cameras designed for very specific applications. Applications include the oil/gas/chemical industry where monitoring for non-visible objects (fire/heat/people) is required.

Most recent applications have been as supplemental devices to assist in monitoring people for higher body temperatures.

Disadvantages
Thermal cameras for monitoring temperature extremes are often application-specific and are often very expensive. Most commercial customers do not have applications requiring these cameras.

Using thermal cameras to monitor body temperatures is often unreliable as ambient temperature and other factors can create issues in accurately measuring body temperature.

Mapping security camera features to applications

The table below offers a comprehensive view of the various security camera features and how these features can be leveraged by loss prevention teams when designing a video monitoring solution.

Security Camera Features Design

Implications for Video Surveillance

Fixed Lens
Fixed lens cameras come with fixed lens focus. They do not have sophisticated moving parts or digital focus adjustment capabilities.

Fixed lens cameras generally cost less. However, they are typically not usable for multiple applications in a design other than what they were originally chosen for due to the fixed focus and limited view.

Varifocal Lens
Cameras with adjustable lens focus that can be calibrated after installation to get the perfect field of view needed for the location.

Allows for one camera model to be used in multiple applications. The same camera can be placed at any location and still deliver the best possible view in each location. This feature allows loss prevention teams to optimize camera layout when needed without having to purchase new devices. Cameras with varifocal lenses have slightly higher costs when compared to fixed lens cameras.

Digital Zoom
Digital zoom crops a portion of the image and then enlarges it. This is not a feature of most cameras, rather it is a function of the video recorder or VMS software.

Digital zoom is an electronic feature of the camera. The user can “digitally zoom” into a smaller portion of the image, much like you would on a mobile phone.

Optical zoom is a mechanical feature of the camera. Cameras with optical zoom have motorized telephoto lenses, allowing the user to remotely adjust the camera lens to zoom-in the camera for a closer view.

While optical zoom magnifies without losing image quality, digital zoom degrades the quality of the image.

Camera Resolution
Typically, commercial security cameras come in 2, 3, 4, 5 or 8 megapixel resolutions. Higher resolutions are available, at significantly higher costs.

If surveillance is required for a modest-sized area to monitor general activity, a 2 megapixel camera may suffice. For high-end stores that may be selling precious jewelry or watches, a camera with higher resolution will be useful.

The higher resolution will allow the loss prevention team to use a feature like digital zoom feature to verify if a store visitor actually slipped the watch into the pocket or read a logo on a shirt or clothing or hat to identify the suspect correctly or even get a proper facial shot.

However, a high-resolution camera is not only expensive off the shelf, but will also need a higher network upload speed to remotely view the high-resolution video and more storage to record the videos resulting in higher operating costs.

When using megapixel cameras, Digital Zoom capabilities are determined by the image width at the target location. A “pixel per foot” calculation is used to ensure that higher MP camera resolutions will be of any benefit in digital zoom.

Dynamic Range
Dynamic range is the measurement of the difference between the whitest whites and the blackest blacks in an image.

Digital Wide Dynamic and True Wide Dynamic cameras offer enhanced dynamic ranges which are useful for specific surveillance scenarios, most often when capturing views of outside a building from the inside by looking through doors and windows. One specific application is capturing people coming in the entry door of your location and wanting to capture facial images.

Cameras with True Wide Dynamic feature are capable of handling highly varying light levels and even capturing images properly against a bright backdrop. For example, cameras with True Wide Dynamic capability are placed inside retail stores facing the doorway. When the door opens and the space outside is under the blazing sun, the camera can instantly adapt to this light condition and manage to capture a clear image of people walking into the store.

Digital Wide Dynamic cameras may not have the dynamic range offered by cameras with True Wide Dynamic feature, but offer a cheaper alternative for loss prevention teams.

Maximum Frame Rate
Frame rate is the speed at which images are shown and is usually expressed as “frames per second,” or FPS. Cameras and Video Recorders have both maximum and minimum frame rates.

Frame rate greatly impacts the ability to capture video effectively. Different frame rates yield different viewing experiences. It is widely accepted that 20 fps is the minimum speed needed to capture video while maintaining realistic motion. Many recorders and cameras used for general security applications have a maximum fps of 30.

More important than the maximum fps is the minimum frame rate. Settings for certain scenes (like a POS station) need to have higher frame rates.

Setting the fps too low can have adverse effects on the ability to capture video of critical events in busy, fast-paced scenes. Some higher megapixel resolution cameras or recorders may limit the maximum frame rate that can be recorded.

Designing a video surveillance solution requires a nuanced understanding of loss prevention objectives, infrastructure availability, choice of camera types, technology or features, and budgetary constraints.

Interface’s team of experienced security experts are available to assist loss prevention teams tackle complex security challenges.

Request a Free Security Risk Assessment

3. Artificial Intelligence Enabled Video Surveillance

Here are some of the ways AI-powered video surveillance is revolutionizing physical security for businesses:

AI-enabled video cameras can detect threats in real-time, enabling immediate alerts for security personnel to prevent incidents like theft or vandalism. Security teams monitoring surveillance cameras can now focus on handling alerts.
AI-enabled video surveillance systems can learn normal patterns and identify anomalies such as repeated visits to areas with high-value merchandise or a group of people congregating in one spot.
AI systems can easily tag videos with high levels of accuracy. Locating a video clip from hours of recording can be done easily to speed up investigations.?
AI solutions can crunch large volumes of historical data to anticipate potential security vulnerabilities, allowing businesses to proactively identify vulnerabilities and optimize resource allocation.

Loss prevention teams looking to install AI-enabled cameras or video management systems that leverage AI should keep in mind the following potential pitfalls:

Privacy Concerns: One of the primary drawbacks of AI-enabled video surveillance is the heightened concern over privacy. Advanced features like facial recognition can intrude on customers’ privacy, raising ethical questions about the extent of surveillance and data collection.
Ethical Dilemmas: The use of AI in video surveillance, particularly with facial recognition or license plate recognition, raises ethical dilemmas. Issues such as consent, profiling, and potential misuse of the technology can lead to public mistrust and backlash.
System Vulnerabilities: AI systems are not immune to vulnerabilities. Hacking and cybersecurity threats pose significant risks, as intruders may exploit weaknesses in the AI infrastructure, gaining unauthorized access to sensitive data or manipulating surveillance outputs.

4. Camera placement best practices for video surveillance

The number of cameras needed for effective video surveillance not only depends on the size of the location but also on what’s being monitored or protected at the location.

A jewelry store may have dense camera coverage to gain complete situational awareness of the movement or actions of people within the store and also be able to identify people. In a casual clothing store, general camera coverage may be adequate.

While there is no thumb rule that can be applied to any location to determine the placement of security cameras, loss prevention teams should consider four questions before designing camera placement:

What do they sell or what are they protecting through video surveillance?
What’s the value of the items being sold or protected?
How easy is it to steal the items being protected?
What’s the likelihood of theft?

Here are a few examples of how loss prevention teams can approach camera placements to address security threats unique to their business.

Industry

Typical Threats

Camera Placement

High-Value Retail

Casing theft
Sneak / Switch theft
Internal theft

Inside entry doors capturing high quality facial images of customers entering the store
Display cases where high-value items are displayed
Register(s) where employees handle cash transactions

Convenience & Grocery

Shoplifting
Hold-up/robbery
Internal theft

Inside entry doors capturing high-quality facial images of customers entering the store, along with Public View Monitors in higher-value goods areas such as health and beauty, baby food, and detergents
POS areas where customer cash transactions take place. Place cameras to capture the faces of customers.
Closed office areas and storage room spaces where employees are are hidden from view.

Restaurants

Hold-up/robbery
Internal theft
Casing

Areas where customer cash transactions take place (POS/Bar). Place cameras to capture the faces of customers.
Rear entry areas (inside and outside) and storage areas, freezers, and coolers where employee theft occurs.
Outside rear doors, areas where employees park, and dumpster areas, to protect employees from ambush or assault.

5. Choosing the right partner to implement a video surveillance solution

Designing a video monitoring system that’s really effective and delivers on what it’s supposed to do is a major challenge. There is a need to understand which camera to use. Camera placement, what features are critical for a customer, and make sure we get the most out of the investment that goes into building a video monitoring solution.

Some of the mistakes that enterprises and businesses make when implementing a video monitoring solution include:

Making a large-scale bet on an unproven solution: Camera technology, cloud data storage, video compression technologies are rapidly evolving. However, embracing new technologies should be carefully calibrated after understanding how a solution that incorporates a new and emerging concept will deliver on the fundamental requirements:
- Can it produce usable video footage in all conditions?
- How quickly can the loss prevention team access the content they need?
- Is it cost-efficient?
Choosing the equipment first: Solution design always comes first. Some customers choose the camera first and then try to build a solution out of it. This is a flawed approach as security requirements should dictate the choice of camera technology and not the other way around.
Stumbling on critical deficiencies after implementation: Some enterprises record videos at very low resolutions and frame rates to save on network and storage costs. However, when video evidence is needed, the recording no longer serves the purpose. For example, the recording may not conclusively show that a person may have actually slipped something into his pocket from a counter! On the other extreme, some businesses implement cameras with 8K bitstreams which is a complete waste of video storage and also reduces the number of days security video recordings can be retained.

The complexity of a video surveillance solution makes it a daunting challenge as there is a mind-boggling array of features and approaches to video surveillance implementations. Hence choosing the right implementation partner is critical for loss prevention teams.

Buyers Checklist for Business Video Surveillance

This checklist is designed to help loss prevention teams review vendor capabilities for implementing or upgrading video surveillance systems.

Video Surveillance Solution Design

Expertise in designing tailored video surveillance solutions that meet the unique requirements of each business location.
Solution design process, considering factors such as camera placement, coverage optimization, and overall system efficiency.
Experience in implementing video monitoring solutions for specific industries. For example, the solution design for monitoring jewelry chains is different from that of a restaurant chain.
The flexibility of the solution design system to adapt to the varying sizes and complexities of different locations along with differing security threats across locations.
Expertise in designing and implementing cloud-integrated solutions for video surveillance.

Camera and VMS Capabilities

Experience in deploying a wide variety of camera types and features such as night vision, smart motion detection, and pan/tilt/zoom (PTZ) to align with the unique requirements of each business location.
Experience in deploying advanced cameras with purpose-built analytics for specific security needs, such as intrusion detection or license plate recognition.
Track record of successfully implementing video management systems (VMS) for businesses of similar size and complexity.
Experience in integrating AI and analytics features seamlessly into their video management system.
Experience in scaling video surveillance solutions to handle a large number of cameras and locations concurrently.
Approach to ensuring continuous video surveillance in the event of network or hardware failures.

Remote Monitoring Capabilities

Monitoring infrastructure, technologies used for monitoring, certifications, and redundancies available at all monitoring locations.
Approach to hiring, training, and retaining remote security teams for monitoring.
Customer onboarding and escalation process alignment capabilities.

Storage, Network, and Security

Experience in designing reliable video storage systems with redundancy measures, including failover strategies and backup protocols.
Approach to managing bandwidth efficiently, especially when utilizing cloud-based storage for video footage.
Strategies for optimizing performance as the system scales, including load balancing and resource allocation./li>
Expertise in building secure networks for video surveillance, including encryption protocols and network segmentation.
Experience in protecting video storage from unauthorized access or cyber threats.
Knowledge and adherence to regulations related to network security, data storage, and NDAA compliance for video surveillance systems.
Compliance with industry-specific or location-specific regulations that may impact network design for video surveillance.

Other Considerations

Size and scale of services offered by the vendor and ability to deploy cost-effective camera hardware and networking equipment.
Partnerships with camera and network OEMs and preferential access to the latest technologies.
Ability to offer visibility on project progress and ongoing management of security hardware and assets via online customer service portals.
Support services offered and SLA guarantees.
Training provided to employees at the location being monitored and the loss prevention teams managing the program.
Ability to deploy onsite support teams at all locations where video surveillance hardware is being deployed.
Commitment to staying abreast of advancements in video surveillance, remote monitoring, networking, and storage.

Share this article

Get the next-generation video surveillance solution

Interface designs and builds video surveillance solutions to improve security and reduce costs. Our expertise spanning business security, network and business intelligence can help multi-location enterprises accelerate digital transformation with confidence.

Click to Learn More about How Interface Can Help

About the author

Don Fruhwirth

Director Product Management

Don Fruhwirth is Director of Product Management at Interface Security Systems. He brings more than 20 years of expertise in security integration strategies, next-generation networking design and wireless system architecture. Don has enabled numerous enterprises in transforming their IT and asset protection system infrastructures. Don is an industry thought leader and frequent speaker on topics such as SD-WAN, cloud video architectures, remote video surveillance and advanced network security. Prior to joining Interface, Don has held senior solution engineering positions for regional security and global cellular telecommunications companies. In addition to his security background, Don holds advanced networking certifications from Cisco, Fortinet and Cradlepoint.

Explore more blog articles

Business Intelligence Retail Video Analytics

Retail Video Analytics – 6 Insights to Transform Operations

In this blog post, learn about the key challenges addressed by retail video analytics and the insights it offers to improve sales, deliver better customer service and reduce operational costs.

Read Blog Post

Managed Network & Voice

7 Reasons to Hire a Managed Network Services Provider

Managed network services providers offer enterprises significant advantages. Find out why in-house network management is just not enough to succeed.

Read Blog Post

Business Intelligence Video Analytics

People Counting System – The Complete Guide for Enterprises

Read the comprehensive guide on how to implement a people counting solution that’s designed to meet business goals.

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

People Counting System – The Complete Guide for Enterprises

Steve Womer — Wed, 04 Jan 2023 16:21:57 +0000

Video Analytics

Steve Womer

SVP, Engineering

Business Intelligence Video Analytics

People Counting System – The Complete Guide for Enterprises

Introduction

What is a People Counting System?

Enterprises use people counting systems to track or measure how many people are in a location or space such as a retail store or office space. People counting helps enterprises make critical decisions on how to utilize the space efficiently, drive sales, improve customer experience, manage queues more efficiently or ensure safety, to name a few.

Previously, people counting was done manually by an employee stationed at entrances and exits with a people counting device (also known as footfall counters) such as a hand clicker.

With the availability of new and more modern approaches to people counting, enterprises can now choose from a variety of people counting sensors and solutions such as video cameras, thermal sensors, Wi-Fi, or Bluetooth beacon sensors.

We created this guide to help enterprises implement a robust people counting solution that’s completely aligned with the organization’s business requirements and goals.

Use Cases for People Counting Systems

In addition to offering real-time data, people counting solutions can also create a rich repository of historical data that can uncover valuable business insights. The table below highlights how different industries utilize people counting systems to optimize space, improve customer experience, monitor compliance, and increase revenues.

Customer behavior and store design
Merchandising
Marketing campaign performance
Customer service
Security or loss prevention
Compliance, health, and safety

Industry

Applications

Retail Chains

Real-time: Monitor real-time entries and exits to optimize staffing, and measure the success of marketing or promotional campaigns. Identify high-traffic areas that need extra attention from employees to keep the areas neat and enticing to shoppers.

Long-term: Evaluate main footfall and customer distribution over multiple departments or areas of interest and reallocate staff, greeters, or customer service agents to increase staff/customer engagement. Track low-traffic departments and areas of interest to uncover possible indicators for lack of interest and shape future marketing or promotional campaigns.

Convenience Stores

Real-time: Monitor occupancy for compliance regarding maximum occupancy dictated by health regulations (such as COVID-19) or fire regulations and temporarily restrict access for new customers accordingly.

Long-term: Monitor peak and slow times to adjust opening hours based on time of day, seasons, events, or other periodic events. Use path map visualizations to learn where customers go when they come in and set up displays for better marketing, product placement, or security.

Restaurant

Real-time: Use footfall count to quantify the requirement to call in more employees due to an unexpected increase in patron numbers. Compare footfall numbers against recent days to identify the possible reasons for the increase.

Long-term: Forecast staffing levels more consistently based on historical footfall traffic and identify when temporary hires might be needed. Use kitchen footfall counters to optimize chef stations usage and reduce the time needed to send out orders.

Showrooms

Real-time: Observe employee effectiveness based on traffic patterns and dwell times. Redeploy employees based on customer numbers and bottlenecks.

Long-term: Determine which items in the showroom attract more visitors, discover the popular areas of the showroom, and adjust product placement. Evaluate employee effectiveness by comparing dwell times and individual sales conversions.

Coffee Shops

Real-time: Reallocate employees from back-of-house to front-of-house based on real-time entry data and optimize the order taking/payment and barista/fulfillment balance.

Long-term: Analyze traffic, sales, and employee performance by the hour, day, week, and month to optimize opening hours and staffing allocation. Use data to increase sales, test promotions, and ensure customer satisfaction.

Shopping Malls

Real-time: Observe bottlenecks and monitor occupancy to create better traffic flow and improve customer experience. Monitor suspicious customer activity and redirect security as needed.

Long-term: Compare overall footfall counts and time of day to optimize operating hours. Compare area footfall counts to individual store entries to discover opportunities for shop diversification. Consider moving high-traffic shops to encourage shoppers to explore more of the mall. Monitor the food court usage and restaurant display count to discover which vendors are generating more sales and which new ones to consider inviting.

Car Rentals

Real-time: Prepare for large influxes of possible travelers heading to car pick-up areas based on footfall traffic numbers at a specific location in the terminal. Allocate shuttles and employees to assist customers with rentals instead of other administrative duties.

Long-term: Analyze the use of space, waiting areas, counter design, queue location, temporary luggage storage, and other areas based on historical traveler traffic data. Renovate internal customer-facing areas to allow for better customer experience and optimize back office areas for staff.

Hotels

Real-time: Monitor the influx of unexpected big parties and automate the reassignment of employees to the front desk to expedite check-ins and registrations, ensure luggage carriers and valets are ready, and mitigate any other possible guest frustration.

Long-term: Track historical patterns of hotel guests by the time of day and day of the week to forecast employee schedules and hiring needs. Observe guest amenity usage counts such as the lounge, restaurants, and pool to plan future usage, expansion, and renovation as required.

Banks

Real-time: Adjust the availability of bank employees in real-time based on customer entries and dwell times.

Long-term: Compare customer traffic numbers to opening hours and service offerings to discover insights or changes that can be made to optimize the customer experience. Analyze traffic patterns and dwell times and locations to reposition service locations internally to create better customer traffic flow.

Hospitals

Real-time: Monitor the occupancy in public-facing areas to comply with health capacity regulations. Monitor capacity of patient waiting areas to reduce overcrowding and direct employees to appropriate locations to pick up patients. E.g., If patients were directed to an overflow area, employees will know to find patients there instead of in the main waiting room.

Long-term: Evaluate the use of popular areas of interest like the entrance foyer, waiting areas per department, pharmacies, etc., and adjust space to accommodate future traffic. Monitor low-use employee areas to prioritize new expansion or conversion for high-use services or areas.

Airports

Real-time: Observe changes in traveler densities at critical pathways or bottlenecks, empower management to reroute foot traffic and staffing distribution to alleviate densities. Sensors allow minute-by-minute monitoring of traffic flow changes to ensure positive outcomes.

Long-term: Analyze historical data to efficiently forecast traffic patterns (daily, weekly, seasonal) to allow for more accurate budgeting and staffing needs. It can also support expansion proposals for heavily used access and traffic points, ensuring needs are met in anticipation of actual requirements.

Casinos

Real-time: Monitor high-use gaming areas or stations and reassign employees to better accommodate potential clients. Enforce capacity limits in high-traffic areas to ensure adherence to capacity laws and other local guidelines.

Long-term: Evaluate traffic on a seasonal or event basis, such as local holidays, trade shows, or professional sports events and redesign gaming layout and traffic patterns accordingly. Redesign gaming locations based on use and forecast future expansion/contraction of other game-play models.

Large Venues / Sport Venues

Real-time: Monitor traffic patterns at entrance gates and other areas where bottlenecks occur, such as theater or arena entry, where ushers verify patron tickets. Redeploy staff, ushers, and security to optimize flow.

Long-term: Forecast staffing and hiring levels based on past events and avoid unnecessary wait times and lower customer satisfaction. Compare overall occupancy to observed traffic at areas of interest like concession stands, retail locations, and VIP areas to determine sales and revenue conversion rates.

Museums

Real-time: Monitor sudden traffic spikes in real-time that could negatively impact environmental guidelines for the artifacts and redirect security or docents to disperse crowds or redirect people to other parts of the museum.

Long-term: Report on the overall use of space based on footfall traffic and broken down by exhibit type, artist name, or other categories. Compare footfall traffic to ticket sales and revenues to forecast exhibit success and plan for future exhibits.

Smart City / Outdoor Venues

Real-time: Monitor traffic patterns to prevent overcrowding public places by sending park employees proactively to those locations. Open/close access points to remove bottlenecks. Automatically send social media messages through corporate accounts to advise patrons of potential wait times and increase satisfaction rates.

Long-term: Track outdoor visitor trends in parks, recreational facilities, and hiking trails over time, during specific weather patterns, or outdoor events. Develop occupancy stats and trail usage to determine when to shift hiking trails or other outdoor amenities to prevent overuse. Compare footfall traffic to local retail and businesses in the area. Use data to partner with municipal and local business improvement groups to monitor business health, track engagement during special events.

In most cases, it is impractical for enterprises to hire and retain in-house teams to perform all of the above tasks.

Unlike enterprises with periodic spurts in demand for network management skills, managed network services providers are able to deploy their teams across multiple client engagements giving them the ability to hire, retain and motivate a broad group of network engineers with diverse skill sets.

Looking Back and Keeping Up

Here is how retail chains can leverage video analytics to access historical and real-time data.

Long-term data

The image shows historical footfall count data juxtaposed with data from the current week. This information can then be tied to a variety of factors such as weather, promotions, and holidays.

Real-time data

The image shows the real-time heatmap of customer interactions with various displays in a retail store. This data can be used in real-time to make adjustments to the display for better product engagement.

How to Implement a People Counting System

Implementing an enterprise-grade people counting system involves choosing the right sensor, mapping business goals to key metrics, and setting up an organization that’s designed to leverage the people counting data insights. The following sections offer an in-depth review of all the key aspects of the people counting solution implementation milestones.

1. Select the Right Type of People Counting Sensor

Every people counting sensor type is designed for specific use cases and applications. The table below outlines the pros and cons of all the major people counting sensors typically deployed by enterprises.

People Counting Sensor

Applications, Pros & Cons

Video Camera Sensor

Pro:
Gathers precise information on the movement of people within its field of view allowing for a wide range of data collection.

Tracks entry and exit data in real-time along with all other engagement metrics such as walk-in data, dwell time, hotspots, and path maps.

For most applications, existing security cameras can function as the people counting sensors reducing the cost and complexity of implementation.

Con:
For certain edge cases, existing security cameras may not be able to recognize images. For example, high contrast areas, or areas with poor ambient lighting. In such cases, expensive 3D Cameras may be needed to plug the gaps in coverage.

Best use:
Any business looking to analyze foot traffic and activity for advanced analytics requirements where people tracking accuracy is critical.

Thermal Sensor

Pro:
Low-medium cost, easy installation. Adaptable to complex entrances with multi-directional people movement. Does not capture any personally identifiable information.

Works well in darkness, bright areas as well as in places with reflective surfaces or walls.

Sensors are often discrete and can track a wide area, translating into fewer sensors.

Con:
Doesn’t allow for in-depth analytics of customers and their behaviors such as dwell times or path maps.

Sensors placed outdoors or in harsh environmental situations will deteriorate faster, requiring replacement more often.

Best use:
Any business looking to analyze foot traffic, maintain capacity limits, or those wanting to maintain the privacy of patrons and customers, such as healthcare clinics and related services.

Infrared Sensor

Pro:
Accurate even for large and fast-moving groups of people.

Relatively easy installation with one-time calibration or verification.

No personally identifiable information is captured. Can work in a wide range of lighting conditions, unaffected by shadows and busy patterns on the floors.

Con:
Requires optimal placement to be effective – ideally above the area to be tracked.

Best use:
Locations where accuracy matters, such as venues with local capacity limit laws, shopping centers, libraries, museums, parks, and outdoor leisure centers.

Wi-Fi Beacon Sensor

Pro:
Tracks customer activity based on their identity, hence it is suited for targeted communications and promotions based on where the customer may be located.

Low cost of implementation as fewer WiFi sensor devices are needed.

Con:
Accuracy is tied to customer mobile device capabilities and settings. Cannot be used for tracking product interactions as position accuracy is limited.

Reliance on working Internet connection in the location.

Privacy issues as tracking is completely based on customer identity.

Best use:
Large retailers, shopping malls, logistics warehouses, and other vast spaces where people count is needed and location inaccuracy is not an issue, and WiFi-enabled devices are generally available with most individuals.

Bluetooth Beacon Sensor

Pro:
Reasonably priced.

Easily scalable for larger locations. Easy self-installation, and battery-powered.

Can push customized messages to customer smartphones.

Con:
Accuracy depends on customer mobile device capabilities and settings.

Technology based on personally identifiable information.

Accuracy in tracking the precise location of people is limited.

Best use:
Locations with a high probability of Bluetooth-enabled devices, such as shopping malls or other retailers.

2. Identify Sensor Installation Parameters

Choosing the right hardware also depends on the individual needs of the space you want to count people in. Here are various factors that can impact the choice of the sensor, their placement and the number of sensors needed.

Installation Parameters

Considerations for the choosing sensor

The size and type of door

Is it a swing door, revolving door, or an open entrance like that’s used in a mall store?

The area where people are to be counted

Is it a doorway, open area, or aisle?

People behavior

Do people linger in the area where they’re to be counted?

Do they stand still, or are they moving? E.g., They’re mostly stationary at the checkout counter, but in the aisles, they move more.

Do they enter in groups or individually?

Sensor requirements

Is there a maximum number of sensors you can place in a location, either due to store or sensor technical limitations? E.g., Some sensors can only connect to 3 or fewer sensors, while others have no limits.

Does the sensor have a height or placement limitation? E.g., Many thermal sensors have a distance limit in which they work, such as a maximum of 12 feet away, while mono video cameras may have a camera angle limitation and must be placed in a fixed spot.

Is there a temperature issue with the sensor location? E.g., Outdoor locations will require specialized sensors that can withstand the temperature differences.

Is there enough light in the location you wish to count people? E.g., Brighter lights at a retail entrance may disrupt some sensors, while a dark corner of a stockroom may prevent accurate counts for others.

Doing More with Less

In small-sized retail stores, the fisheye camera is a great option to get a complete overview of an entire store to feed data into a video analytics application. This is a great way to minimize the number of sensors (cameras) needed to capture data needed for people counting analytics. The image below shows visitor path map analytics superimposed on the video snapshot of the store.

3. Plan for Bandwidth and Power Requirements

The technical requirements of the people counting hardware and your physical location will determine which option you choose. Each hardware type comes with requirements, such as power, bandwidth, mounting location, and more.

Video cameras, when used as people counting sensors use more power and bandwidth when compared to other types of people counting sensors. However, when you leverage existing video surveillance infrastructure, video analytics gives you a headstart as the implementation is relatively easy and the cost of maintaining the video camera network is already budgeted for by loss prevention teams.
Some thermal counting sensors run on high-energy lithium batteries, giving them a 1-2 year battery life. Thermal counters consume less bandwidth as they capture limited data and don’t require as much computing power. Like advanced security cameras, many of them have Power over Ethernet (PoE) capability.
Most sensors record data and store it locally before sending it for analysis. Several video camera sensors have various frame rate options (from 4 to unlimited frames per second), each requiring different bandwidth capabilities.
Others located in inaccessible locations such as outdoor parks or large warehouse facilities with minimal power outlets availability require larger local memory storage to store data offline until it can be transmitted.
Offline recording is also vital for hardwired sensors in the case of power or other outages. Data should still be collected and stored, ready for transmission when services are restored.
For networked sensors, wifi connectivity may be needed and the ability to connect to a cellular network will be a bonus feature. However, some building locations block wireless signals more easily than others, so this will need to be tested to ensure functionality.

4. Evaluate Data Sharing and Integration Capabilities

The true value of a people counting solution is directly related to its ability to generate data in a form that can be ingested into reports or dashboards in real-time.

While long-term data gathering and trend analysis is useful, real-time data streams can surface critical business insights that can potentially help enterprises anticipate changes.

For instance, historical data from the people counting solution in a retail chain might indicate that before a hurricane hits, dwell time and footfall stats at aisles selling canned food and beer are fivefold the median values. This is indeed valuable and can help retailers stock these products in greater quantities based on weather.

With real-time people counting data that are correlated with KPIs, a retail chain may be able to adjust pricing and product assortment on-demand and thus make inventory replenishment proactively before the demand slumps or spikes for any reason.

When choosing a people counting system, here are some of the key considerations to evaluate data analytics and integration capabilities.

Data availability: The data generated by the people counting solution should be easily available for analysis and reporting via the cloud or the LAN. In distributed enterprises such as retail chains, on-demand data availability via the browser is preferable considering the need to analyze data from multiple locations in real-time by diverse stakeholders.
Role-based access: The use cases for data generated by people counting applications cut across different departments and user roles in the enterprise. For example, a retail chain may find the people counting data being shared by marketing, merchandising, loss prevention, operations, and HR teams. Hence, role-based access, preferably through enterprise active directory integration, is a critical feature.
API integration: Accessing the data generated by people counting sensors via legacy reporting solutions, custom dashboards and ease of integrating people counting sensors directly with other applications in the enterprise directly or via an Enterprise Service Hub (ESB) are important decision points. Hence, having a well-documented API is a must for any people counting solutions.
Secure sharing: Considering the wide range of applications and use cases for leveraging data generated by people counting sensors, the option to securely share confidential data and reports with external teams (vendors, service providers) with advanced security features like password-protection and policy-based access controls are a must-have feature.

5. Map Sensor Data with KPIs

Mapping data generated by a people counting solution to key performance indicators (KPIs) allows enterprises to uncover the insights that drive business decisions and growth.

Here is an example of how this mapping can be done for a retail chain planning to implement a video analytics people counting solution for its stores.

KPIs

Business insights from people counting sensors

Sales per square foot

Power up underperforming locations
Not every store location is profitable, but it may cost more to close the underperforming ones. To power up the location, combine the Sales Per Square Foot KPI with footfall traffic numbers and Conversion Rates to identify products or services that sell well there and create targeted marketing campaigns for them

Footfalls

Understand what’s driving footfalls
A viral video or an ad campaign may drive people into stores. With people counting solutions, enterprises can combine visual paths, heat maps, and store footfalls to identify popular items along with the context for their popularity. Store managers can create new store displays, adjust pricing, and order more inventory to meet the demand.

Conversion rate

Discover which promotions work best
The 50% off sale in a store almost always does well. But what about a “buy two, get 20% off” promo? Or something even more creative? Without testing and tracking promotions, retail managers will never know what works in their location. By combining footfall traffic, Units per Transaction, and Promotion Conversion Rates, you’ll know which promo works better. Then, you’ll be able to schedule similar promotions in the future whenever you need to bump up sales. Compare item Sell Through rates for in-person and online products to see how other in-person elements affect sales numbers compared to discounts offered only online.

Shopper dwell time

Optimize store layout or design
Optimizing store layouts are hard to do without data. Set up people counters in aisles and departments to start gathering footfall traffic data and dwell times. Compare it to Item Sell Through rates to see how the sales of items from those sections compare to the rest of the store. Move merchandise to higher-converting areas to increase sales of underperforming items or try the opposite to encourage customers to visit under-performing areas of the store.

Return rates

Address gaps in the return process
Returns are never a good thing for retailers, but they’re even worse when they take employee time away from new sales. Look at the Rate of Return numbers and Shopper Dwell Times at the return counter to identify the issues in the return process. Managers can improve the return training programs for employees or review the return policy.

Checkout lane or kiosk productivity

Monitor checkout performance
Many grocery stores have added self-service checkout kiosks to reduce checkout bottlenecks. But do they work? Combine footfall traffic, time of day usage, and Units Per Transaction to discover if they are. Plus, it’ll tell you how to optimize the store layout near the kiosks, whether you can adjust staffing schedules, and more.

Similarly, the number of people completing the checkout successfully and average queue dwell time to complete the checkout can be tracked to optimize checkout staff based on time of day or day of the week.

6. Build a Data Governance Strategy

The value of data generated by people counting systems increases exponentially when data is integrated into existing dashboards that bring together data from a variety of enterprise applications such as POS (point of sale) systems, inventory management, and security systems, to name a few.

Maintaining data definition consistency and accuracy across the enterprise is critical to ensuring the success of data-driven, cross-functional programs such as a people counting implementation.

Here are some of the critical factors that define the success of a data governance strategy:

Considerations for data governance

Real-world implications

Data preparation costs & benefits

Ability to track the time and effort to identify data sources, address data errors and make a “clean” version of the data available for reporting and analysis.

An enterprise with a well defined data governance model will be able to:

Rapidly import data from a people counting solution into an existing dashboard.
Determine project success or failure early in the project.

Data quality impact on revenue and cost

A system to flag revenue leaks and costs associated with incorrect data and errors in processing data accurately.

If inventory decisions are made because of an erroneous report from a people counting sensor, it may have serious consequences for the business.

Organization structure

A matrix organizational structure with functional leads and managers working in close collaboration with product teams will result in better data quality.

Product category owners in a grocery store can collaborate with marketing as well as merchandising teams to define processes to verify data accuracy from people counting sensors or fine-tune sensor implementation to address gaps in data collection.

Data quality for critical applications

An incremental approach to addressing data governance challenges with a focus on tackling data challenges for high-priority applications has a better chance of success when compared to a big band approach.

A people counting system could be implemented to first demonstrate results for marketing and merchandising teams before leveraging data for loss prevention use cases. This approach will result in a time-bound implementation of data governance models that can then be applied for other functions.

Regulations and compliance

A clear understanding of regulatory requirements and compliance needs is critical when implementing a people counting solution. Any personally identifiable information (PII) should be masked for certain categories of users and should be made available on a need-to-know basis.

A retail chain implementing a WiFi-based people counting technology has to decide who will have access to customer details when analyzing in-store footfall traffic.

Privacy Matters

Ignite Prism’s video analytics solution has an intelligent privacy filter that ensures videos of customers are automatically masked even before they are recorded by the cameras. Users still get to see customer activity such as hot spots and dwell time with guaranteeing absolute customer privacy.

Start Your People Counting Project Here

Interface’s proven video analytics solution is the easiest way to implement a robust and scalable people counting solution. With Interface, multi-location enterprises can turn their existing security cameras (and that includes most legacy analog cameras) into a powerful business tool.

Zero installation of any sensor or hardware for most counting applications
Optimize staffing levels based on real-time customer data
Proactively plan product inventory based on real-time customer behavior trends
Evaluate the effectiveness of marketing campaigns and track in store conversion
Reduce audit and compliance costs

Share this article

Go beyond people counting

Find out what’s possible with Interface

Schedule a Free Consultation

About the author

Steve Womer

SVP, Engineering

Explore more blog articles

PCI Compliance

How Digital Transformation Can Open Doors for Retail Cybersecurity Attacks

Retail cybersecurity threats are on the rise thanks to rapid digital transformation. Find out what retail chains can do to address this threat.

Read Blog Post

Business Security

Unmasking Organized Retail Crime: Strategies for Countermeasures

Learn more about organized retail crime (ORC) and the best strategies retailers can take to combat organized theft, scams and fraud using technology & training.

Read Blog Post

Managed Network & Voice PCI Compliance Restaurants Retail

Network Modernization – A Practical Guide for Multi-Site Enterprises

Learn how multi-site businesses can implement network modernization. Includes real-world case studies and best practices to accelerate network upgrades.

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

Retail Video Analytics – 6 Insights to Transform Operations

Steve Womer — Mon, 02 Jan 2023 13:31:09 +0000

Video Analytics

Steve Womer

SVP, Engineering

Business Intelligence Retail Video Analytics

Retail Video Analytics – 6 Insights to Transform Operations

Introduction

What is Retail Video Analytics?

Retail chains leverage data from a variety of sources to identify operational gaps. Rapid strides made in technologies such as computer vision and artificial intelligence now allow retail chains to uncover meaningful business insights from cameras originally deployed for securing the stores. These developments have now spawned an entirely new class of enterprise applications called retail video analytics or video-based retail business intelligence.

Retail video analytics can uncover hidden opportunities to improve all aspects of store operations such as:

Customer behavior and store design
Merchandising
Marketing campaign performance
Customer service
Security or loss prevention
Compliance, health, and safety

In this blog post, learn about the key challenges addressed by retail video analytics and the insights it offers to improve sales, deliver better customer service, and reduce operational costs.

Why video analytics is a game-changer for retail chains?

Retail chains are facing major challenges in maintaining operating margins as consumer preferences have changed dramatically and there is a heightened awareness about health and safety.

The economic impact of the pandemic and the ever-present threat of lockdowns has forced retail chains to look for solutions that can help them rapidly identify changes in consumer behavior, spot operational gaps in real-time, and fuse data from multiple data sources to take decisions proactively. Retail video analytics offers all of these capabilities and more.

There are two primary reasons retail chains should consider implementing an intelligent video analytics solution.

1. Graduate from descriptive analytics to predictive analytics

Analyzing historical retail performance and operations data from data sources such as inventory management systems, Point of Sale (POS) systems, people counting devices are the foundation of what Gartner calls “descriptive analytics”.

Descriptive analytics is all about understanding what happened in the past. However, relying only on descriptive analytics may not be enough especially in a world where brand loyalty is fast eroding and customers have very little tolerance for:

Out-of-stocks, pricing inconsistencies, and “store friction”
Inability to offer the convenience of Buy Online, Pick-Up in Store (BOPIS)
Inaccurate fulfillment and gaps in customer service

With video analytics, retail chains can graduate to predictive analytics to get answers for questions such as:

What should be the ideal staff size for a store on a Saturday evening between 5 pm to 8 pm?
Which display unit generates more sales for a product at a location and how does it vary across locations?
What product should a store stock more than usual on a sunny day at a specific location?

2. Go beyond loss prevention to gain a competitive advantage

Retail chains are now forced to invest a lot of money in new and untested technologies to keep pace with the rapid changes in consumer preferences.

Investments in new fulfillment centers, customer delivery and returns management solutions, to name a few, are eroding margins and forcing retail chains to justify the investments or keep a close tab on ROI.

The first wave of video analytics solutions focused on delivering smart or intelligent video data interpretation solutions for a proactive approach to loss prevention and security such as:

Locating suspects in a crowd of shoppers
Tracking the movement of specific items or high-value inventory
Validating employees via facial recognition to allow access to secure areas

Retail video analytics have now moved beyond just video surveillance and security to provide data insights relevant for almost all retail departments. Retail chains can now justify the cost of implementing a sophisticated video analytics solution as the benefits from the data insights can boost store performance across the board. That’s not all. Video analytics applications are available as bolt-on solutions that leverage existing security camera infrastructure that most retail chains already have in place thereby simplifying implementation to a large extent.

How does retail video analytics work?

A combination of video data and visual maps can then be merged into another set of variables such as product SKUs, sales, store geo-location, date and time of the day, in-store marketing campaigns or promotions, lighting, signage, temperature, access to product, product placement and display types, store layout changes or design updates to yield insights on customer behavior inside the store and how store design and other variables play a role in driving sales or any desired customer behavior.

Here is an overview of the top 6 applications of retail video analytics that will allow retail chains to tackle some of the biggest operational challenges facing them.

1. Use customer behavior visualization to optimize store design

Retail chains with a successful e-commerce presence use a variety of software applications to visualize online site traffic to track average time spent on a page, bounce rates, exit rates, shopping cart abandonment, and conversions. Visualizing online site visitor heatmaps, A/B testing of page content, call to action, and other digital marketing techniques are widely used by most e-commerce sites.

Retail video analytics brings the same set of techniques that e-commerce sites use to the physical store.

A store equipped with a 360° ceiling-mounted camera, with a clear line of sight to every corner of the store, can generate valuable data to answer questions such as:

How far do customers go into the store?
How many customers directly go to the register or the service kiosk?
How many customers go to a specific product section or aisle where there are products related to a marketing campaign?
What are the dwell times at various spots within the store?
Which are the location and product display hotspots that draw customer attention?
What are the “dark” areas of the store that customers choose to ignore?
How many people stood in front of a particular product?

An overhead camera with visibility into the entire store shows how far people go into the store to identify high-traffic areas and parts of the store that get little or no store traffic. This insight can be a valuable input for improving store design or A/B testing new design elements in the store.

Video analytics can be used by retail store designers to:

Test and create new floor plans that improve customer experience and maximize sales
Utilize key spaces with the store and minimize dead spaces
Understand how design changes can impact sales and dwell time in adjacent spaces
Decide on product placement by category that helps the customer find what they want quickly
Diagnose issues in lighting, temperature, and signage that might result in poor conversion

In summary, retail chains can use video analytics to make critical updates to store designs that directly influence customer behavior and run fine-tuned experiments in a small set of stores before rolling the changes across the board.

2. Speed of customer service

Delivering fast customer service and efficient queue management at checkout is a major challenge for retail chains. Firstly, the high volume of customers during peak hours or seasons can lead to long queues and delays. Secondly, limited checkout counters can exacerbate the problem. Opening additional counters is not always feasible due to space constraints or budget limitations.

Other challenges include staffing issues, where insufficient or untrained staff can hinder customer service. Complex product or service inquiries can also slow down the process if staff members lack the necessary knowledge or experience. Additionally, an inefficient store layout can contribute to longer waiting times and confusion among customers. Technological issues, such as outdated systems or glitches, further impede service speed.

With video analytics, retail operations teams can monitor queues at the checkout counters to gain real-time insights into queue length, waiting times, and service efficiency. This information helps retailers optimize staffing levels, open additional checkout counters when needed, promote self-service or app-based payment, optimize product mix at the store, and train employees to serve customers faster.

Video analytics can offer insights into some of the critical questions that determine the speed of customer service:

How long do customers typically wait in queues before being served?
What are the peak hours or periods when queues are longest?
Are there specific areas or checkout counters where queues tend to form more frequently?
How many staff members are needed during different times of the day to ensure efficient service?
Are there any bottlenecks or areas in the store layout that slow down the customer service process?
What is the average time it takes for a customer to complete a transaction at a specific checkout counter?
Are there any patterns or trends in wait times based on factors such as day of the week or product category?
How do different staff members or shifts compare in terms of speed and efficiency?
Are there any particular service areas where customers experience longer wait times or delays?
Are there any instances of abandoned queues or customers leaving due to excessive wait times?

Using video analytics retail chains can deep dive into customer service points of friction at every store by time of day, day of the week, and season. Issues with technology (POS screen loading times), training deficiencies, and poor design at checkout can easily surface via drill-down reports.

Retail chains can improve the speed of service at the checkout and in the curbside area using video analytics. Some of the benefits include:

Redesign checkout experience to address points of friction
Align your merchandising and promotional strategy to eliminate purchase complexity
Deliver employee/cashier training to address minimize billing errors and improve customer communication
Optimize shift management to align closely with variations in customer footfalls

In summary, the ability to serve customers faster improves by gaining insights from video analytics can help retail chains improve customer experience and maximize sales.

3. Improve in-store merchandising to drive sales

Maximizing shelf space usage, ensuring every store stocks just the right quantity of products, and choosing the right product mix across product categories to maximize sales are among the most valuable goals for retail merchandising teams. While planograms, merchandising software, and visual audits can get the job done, the speed with which display units can be tested or standardized marketing campaigns can be rolled out at scale continues to be hampered by the lack of real-time data and the inability to take instant corrective actions.

A planogram provides a detailed visual view of the store and is used by the merchandising departments to implement the best possible placement of products on the shelves to maximize sales. Credits: Ejemplo Planograma Textil CC BY-SA 4.0

With retail video analytics, merchandising teams can conclusively evaluate the effectiveness of merchandising strategies and rapidly change tactical implementation at the store-level. Video analytics can shed light on a wide range of valuable insights such as:

How are seasonal sets or floor plan changes impacting customer experience and sales/shopper?
What can be learned about the floor planning process that can be leveraged in future seasons?
How are consumers interacting with the product at an end cap or shelf?
What’s a product display performance in terms of its ability to draw people, sell products, and maximize space usage?
How effective is the new window signage or window display design?
What is the extent of planogram compliance across all the stores?
How are consumers engaging with ads or in-store displays within the store

Retailers can rapidly test the effectiveness of merchandising decisions at a small scale, roll it out across stores, and visually validate compliance.

Retail chains can rapidly zero in on instances of store associates not following merchandising or even re-stocking protocols. For example, video analytics can validate the impact of how restocking/unboxing during store hours can affect customer behavior, product engagement and sales.

Retail chains can boost the productivity of merchandising teams using video analytics. Some of the benefits include:

Align your merchandising strategy closely with customer preferences through video-verified data insights
A/B test every fixture and display type to determine the best option
Get instant alerts when shelves are out of stock with visual validation
Change display tactics in real-time based on date, time, season, or any other event
Do away with manual verification of display guidelines
Get space vs sales data for every display type within the store or across locations

In summary, the ability to keep a tab on how your products are displayed, stocked, and sold using video analytics can help retail chains keep costs under control and maximize sales.

4. Measure online & in-store marketing campaign performance

Rapidly changing consumer behavior and preferences are leading retail chains to overhaul their online marketing campaigns and In-store marketing tactics.

As footfalls nose-dived during the COVID-19 pandemic and retailers retooled to pivot to keep pace with the emergence of e-commerce or BOPIS models, marketing teams in retail chains have discovered that well-established planning practices that are based on historical consumer preferences and sales data have lost their value.

According to Gartner, nearly 30% of marketing leaders believe lack of agility and flexibility negatively impacted marketing execution during the COVID-19 pandemic. The Gartner survey also concluded that marketers are under immense pressure to deliver insights faster than ever before.

Retail video analytics not only gives an accurate, real-time view of how consumer preferences are changing but also offers marketing teams the capability to execute marketing programs with a high degree of confidence even when the world around is changing rapidly.

Specifically, marketing teams can leverage video analytics to answer critical questions such as:

How many people are walking by and not entering the store?
Did the online marketing campaign drive incremental traffic and how did the store perform?
How can new traffic patterns be used as an effective marketing tool?
As traffic flows are there unanticipated changes in adjacent zones?
What stores in certain geographies are outperforming stores in other regions?
Why did the upsell or cross-sell campaign fail?
Did all the stores comply with the display guidelines specified by the brand?
Did the in-store event or sample distribution succeed in generating interest and how much of the sales can be attributed to the in-store event?

With retail video analytics, marketing teams can:

Gather data about the performance of in-store displays for planning and post-rollout analysis
Analyze customer dwell times and hotspots on specific shelves/display units connected to the marketing campaign
A/B test displays, audio announcements, lighting, and ‘experiential’ kiosks and roll out changes rapidly
Visualize sales funnels for every marketing campaign at the store-level and map the data to online promotions
Monitor implementation of agile in-store campaigns based on real-time trends such as local events or weather

One of the ways retail video analytics can give marketers the agility they need to separate insights from noise is by generating a real-time sales funnel report that compares conversion data from online to in-store walk-ins, dwell-time on the relevant product aisle to the sale.

Video analytics allows retailers to zoom in on the performance of in-store displays that may be a part of marketing campaigns. In this image,you can see product activity hotspots corresponding to products on a table-top display unit. Data associated with the product activity hotspots can be used to determine the popularity of products and also correlated with sales data.

The sales funnel data at a regional level can be mapped to unique events such as easing of lockdown restrictions in a state that drove up sales thereby giving a realistic insight to help marketing teams make better decisions.

In summary, video analytics can be used by retail marketing teams to confidently make decisions and measure the impact of marketing campaigns with a high degree of accuracy.

5. Energize retail operations

E-commerce and analytics teams are obsessed with improving the efficiency of their operations and rely on data to guide them in their battle to cut costs and get customers to buy more.Online platforms, like Amazon, have the benefit of a technology-first approach to run their operations and they may have completely bypassed the challenges faced by traditional retail chains that may be relying on legacy software, network, and hardware infrastructure.

In addition to data collection challenges from legacy applications, ensuring customer data privacy, health and safety of customers as well as employees are high priority challenges for brick and mortar retail chains.

Retail video analytics can help level the playing field for retail chains looking to streamline operations and offer a better in-store customer experience. With video analytics, retail operations teams can get insights on key questions such as:

What is the optimal staffing level by employee type by department and by day of the week or hour of the day?
What trends can be seen in dwell times at the checkout counter and how does this align with staffing levels?
Are the store displays and shelves stocked as per the merchandising guidelines?
Are the store personnel complying with the safety and hygiene guidelines?
Which products are out of stock and how quickly are they being refilled?
What’s the average time taken by a store to locate and fix a potentially hazardous spill or debris on the aisle?

Retail video analytics can provide reliable data on footfalls for the entire store or for a specific department by date and time. In this screen, real-time footfall count (highlighted in blue) is compared with expected traffic (highlighted in grey).

Sophisticated video analytics platforms can not only count people inside the store, but also detect if people are wearing a face mask, predict where customers may need help or when inventory is likely to run low, and create alerts when additional manpower may be needed at the checkout counters. All these capabilities can be “turned on” using the IT infrastructure that may already be available at the store.

Here are some of the ways retail operations can get a boost with video analytics:

Eliminate or minimize the need for on-site store audits for merchandising or operations compliance using automated inspection and alerts for all points of interest within the store.
Empower store teams to take localized decisions on merchandising improvements, product promotions or inventory management to align with customer demand or preferences.
Trigger automated audio announcements when customers or employees are not wearing face masks or not observing social distancing inside the store.
Finetune staffing schedules or change shift hours to completely align with predicted customer footfalls to optimize costs and improve customer experience.
Automatically detect misplaced items on shelves and shelves that may be running out of products and alert store associates.

In summary, video analytics provides real-time operational awareness to store employees and gives traditional retail chains the ability to integrate data sources to gain actionable insights.

6. Streamline loss prevention and security

The concept of using video surveillance became popular among retail chains way back in the 1970s and ever since video cameras have been playing a key role in securing inventory, customers, and employees.

With the advent of “intelligent” digital cameras with edge processing capabilities and network video recording, video surveillance has become more autonomous and dependence on human monitoring has come down to assessing exceptions as opposed to continuous monitoring.

However, better cameras alone don’t guarantee a reduction in fraud or shrink. According to the 2020 National Retail Security Survey, retail loss prevention leaders felt in-store fraud has seen the most increase.

Retail video analytics can help loss prevention teams get more out of their limited manpower and budget by focusing on anomalies that indicate deviations from established protocols, internal shrink, shoplifting or fraudulent activities. With video analytics, loss prevention teams can gain a better understanding of these critical questions:

Are store associates following store opening and closing protocols?
Are employees handling cash movement following cash custody protocols?
Are perishable items stored and handled as per the standards?
Is a customer concealing an item in the backpack or hiding it under clothing?
Are the refunds, coupons, and voided transactions legitimate?
Is there a way to be alerted when banned individuals and customers with a history of shoplifting enter the store?

While video analytics can deliver insights in real time that’s usually not available with legacy data sources, the fusion of video data with POS systems, intrusion alarm systems, and access control systems can give loss prevention teams multidimensional information on specific events of interest. For example, a voided transaction recorded by a POS system can be mapped to a time-stamped video snippet to capture the event for validation.

Some of the video analytics software applications come with an integrated video management capability that allows loss prevention teams to quickly locate the video recording and securely share it via password-protected links with team members and law enforcement greatly reducing the time taken to investigate and gather evidence.

Here are some of the ways loss prevention teams can use video analytics to ramp up productivity and get more out of the camera network:

Monitor customer activity and movement of high-value products by designating areas of interests or virtual tripwires
Easily search and locate tagged video recordings by product category, transaction, employee, store location, date or time
Automatically track the movement of employees in high-security areas of the store with the ability to validate access via the access control system
Configure alerts for loitering, suspicious activity, shelf sweep attempts
Detect sweethearting at the checkout counter by avoiding scanning the item, covering the barcode deliberately or by stacking one time on top of the other
Detect instances of price-lookup abuse and directly bagging the item without using the bag weight scale at the self-checkout counters
Cut down incidents of false alarms and avoid false alarm penalties by combining video data with alarm events

In summary, loss prevention teams can leverage retail video analytics to get more done even when operating with sub-optimal staffing levels with increased scrutiny on budgetary allocations. With security cameras playing a central role in uncovering operational insights for all departments, loss prevention teams can maximize ROI for the business.

Share this article

Turn security cameras into a powerful business tool

Talk to Interface to find out how your retail chain can drive sales using video analytics

Learn More

About the author

Steve Womer

SVP, Engineering

Explore more blog articles

Business Security Remote Video Monitoring Video Analytics

Video Monitoring Use Cases

Find out how video monitoring can address a wide range of use cases that go beyond just securing retail and restaurant locations.

Read Blog Post

View All Blog Articles

Connect with Our Experts

Interface solution experts are ready to help you solve challenges. Set up a no-obligation, exploratory call now.

Get a Free Consultation

Video Analytics Archives - Interface Systems

Video Monitoring Use Cases

8 Video Monitoring Use Cases for Retail and Restaurant Chains

1. Stop Shoplifting

2. Deter Smash and Grab

3. Prevent Vandalism and Loitering

4. Enhance Post-Incident Response

5. Boost Employee Retention

6. Monitor Overnight Construction or Renovation

7. Manage Unattended Direct Store Deliveries

8. Audit Business Operations

Make Your Security Cameras Work for You

About the author

Matt Smitheman

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

Introduction

What’s Propelling Restaurant Drive-Thru Innovations?

Speed of Service

Employee Interaction

Order Accuracy

1. Expanded Drive-Thru Lanes

2. Intelligent Outdoor Digital Menu Boards (ODMBs)

3. Gamification for Drive-Thru Employees

4. Computer Vision and Video Analytics at the Drive-Thru

5. AI-Based Voice Assistance

6. Automated Drive-Thru For App Orders

7. Restaurant Robotics & Future Contactless Drive-Thru

Groundwork Needed for Drive-Thru Innovation

1. Network Capacity

2. Network Security

3. Accidents and Claims

4. Backend Bottlenecks

5. Operational Complexity

Innovate Fearlessly and Change Gears with Confidence

About the author

Steve Womer

Explore more blog articles

Business Video Surveillance Insights for Loss Prevention Teams

7 Groundbreaking Drive-Thru Concepts and Trends for QSRs in 2024

Retail Network Transformational Insights

Connect with Our Experts

6 Game-Changing Retail Technology Trends in 2024

6 Game-Changing Retail Technology Trends in 2024

Digital Transformation in the Retail Industry

1. Contactless Stores

What are contactless stores

What are the key drivers for contactless stores?

Technology implications of implementing contactless stores for retailers

2. Artificial Intelligence (AI) Enabled Security Cameras

What Are AI-Enabled Cameras?

What Are the Key Drivers for AI-Enabled Cameras?

Technology Implications of Implementing AI-Enabled Cameras for Retailers

3. Retail Video Analytics

What Is Retail Video Analytics?

What Are the Key Drivers for Retail Video Analytics?

Technology Implications of Implementing Video Analytics for Retailers

4. Metaverse

What Is Metaverse?

What Are the Key Drivers for Metaverse Adoption?

Technology Implications of Implementing Metaverse Presence for Retailers

5. Retail Demand Planning

What Is Retail Demand Planning?

What Are the Key Drivers for Retail Demand Planning?

Technology Implications of Implementing Retail Demand Planning

6. Generative AI

What Is Generative AI?

What Are the Key Drivers for Generative AI

Technology Implications of Implementing Generative AI Applications for Retailers

Transform retail operations with Interface

About the author

Bud Homeyer

Explore more blog articles

5 Essential Steps to Create a Lone Worker Safety Policy

Making IT Happen – The Interface Blog for Distributed Enterprises

5 Technology Solutions For Essential Business Services

Connect with Our Experts

Retail Store Layout Optimization with Video Analytics

Retail Store Layout Optimization with Video Analytics

What is Retail Store Layout?