People Counting System – The Complete Guide for Enterprises

Will Kelso
SVP, Managed Networking & Business Intelligence

Managed network services provider

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  • What is a People Counting System?
  • Use Cases for People Counting Systems
  • How to Implement a People Counting System
  • 1. Select the Right Type of People Counting Sensor
  • 2. Identify Sensor Installation Parameters
  • 3. Plan for Bandwidth and Power Requirements
  • 4. Evaluate Data Sharing and Integration Capabilities
  • 5. Map Sensor Data with KPIs
  • 6. Build a Data Governance Strategy
  • Start Your People Counting Project Here

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.

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.

  1. 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.
  2. 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.
  3. 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.
  4. 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

Go beyond people counting

Find out what’s possible with Interface

Schedule a free consultation

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