Footfall Counting

Accubits collaborated with a prominent supermarket chain in Australia to develop an innovative retail heatmap analytics solution powered by computer vision. By harnessing the capabilities of CCTV cameras placed throughout the store, this solution efficiently collects valuable data on customer traffic.


Our customer, a leading supermarket chain in Australia, which has 20+ supermarkets located in different cities across the country. Supermarkets and Grocery Stores is one of the most competitive industries in Australia. Our client wanted to leverage cutting-edge technology to enhance their digital capabilities to differentiate their brand from the competitors. 


In-store product placement is a critical factor that determines how well a retail store can perform. A highly strategized product placement can be the difference between selling a few units and selling thousands of units of product. Our client followed conventional in-store product placement strategies available from decade-old research findings. They realized that these strategies are not sufficient to drive more sales. Today, data-driven decisions are helping businesses to perform several times better as compared to the results from their conventional modus operandi.

Our client wanted to leverage in-store customer traffic analytics to drive more sales. For example, if they know which section of the store has the highest traffic, they can reposition the product to a different shelf so that people would notice other products on their way or see more product offers that can help to increase more sales. The business challenge was to track the in-store customer traffic in real-time so as to strategize product placements based on the insights generated.


Our client put forward a set of business requirements for us. The major requirements are as follows;

  • Track the in-store customer traffic.
  • Generate a real-time instore heatmap.
  • Pluggable to the existing CCTV infrastructure.
  • Count the number of people enting the store.
  • Count people visiting the defined sections.
  • Track the customer journey within the store
  • Deduct the average customer journey
  • The dashboard in the web as well as mobile interfaces


We built a computer vision-based in-store heatmap analytics solution for our client. The solution collects in-store customers’ traffic data from CCTV cameras installed in the store and analyzes it to create a visualization of the “hot” and “cold” areas of the store. The hot zones represent the areas that are more visited by customers and cold zones represent less-visited or ignored areas.

The solution is capable to count the number of customers entering the store, track the split-up of incoming customers between different sections, track the split-up of customers between different zones, etc. The solution displays the heatmap data, traffic flow data, customer traffic funnels neatly in an intuitive and interactive dashboard that can be accessed by the store admins and managers.


The solution enabled our customers to access insights generated from in-store data analytics and make informed decisions on their product placement strategies. The solution is deployed as a pilot run in 2 supermarkets as an AB testing and evaluated the results.

  • Insights on customer traffic flow
  • Enhanced queue management
  • Efficient facilities management
  • Dynamic staffing based on customer traffic flow
  • Insights on customer traffic funnels, traffic segmentation


The solution was deployed on top of the existing CCTV infrastructure of the store. For one store we used the store’s own server and for the second store, we used a dedicated server for AB testing to compare the result/expense metic. The customer analyzed the performance of both stores for  3 months and saw substantial improvements in sales. The results are as follows;


  • Based on the data generated from the solution, multiple AB testing is done on the product placements, and noticed an increase in overall sales by 18% in 3 months.
  • Noticed an increase in average commodity per customer value from 24 to 31.
  • Reduced peak time queue waits time from 4 minutes to 40 seconds.
  • The efficient use of facilities resulted in a 10% reduction in facilities procurement expenses.

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Frequently Asked Questions

What are the benefits of using a retail heatmap analytics solution?
  1. Enhanced Customer Experience: Businesses can gain deep insights into customer behavior within their physical stores by leveraging a retail heatmap analytics solution. This information allows retailers to optimize store layouts, product placements, and aisle designs to create an intuitive, engaging environment tailored to customers' needs. As a result, customers have a more pleasant and seamless shopping experience.
  2. Data-Driven Decision Making: Heatmap analytics provides retailers objective and data-driven insights into customer interactions, movements, and preferences. This data helps businesses make informed decisions regarding store design, product assortment, marketing strategies, and operational improvements. Instead of relying on assumptions or guesswork, retailers can use concrete data to guide their decision-making processes.
  3. Optimized Store Layout: Retail heatmap analytics enables businesses to identify high-traffic areas, popular zones, and customer engagement hotspots within their stores. With this knowledge, retailers can strategically position high-demand products, promotional displays, or featured items in these areas to maximize their visibility and sales potential. By optimizing the store layout based on customer behavior, retailers can increase the likelihood of conversions and drive revenue growth.
  4. Improved Conversion Rates: Understanding the correlation between customer behavior and purchasing patterns is crucial for increasing conversion rates. A retail heatmap analytics solution enables businesses to identify areas where customers spend the most time and compare it with actual sales data. This analysis helps retailers pinpoint areas needing attention, such as optimizing product displays, improving signage, or streamlining checkout processes. Retailers can optimize conversion rates and boost overall sales performance by addressing these issues.
  5. Efficient Staff Allocation: Heatmap analytics provides valuable insights into customer flow and peak traffic times, enabling retailers to optimize staff allocation accordingly. By accurately predicting and aligning staffing levels with customer demand, businesses can ensure that they have sufficient staff available to provide assistance, answer queries, and deliver exceptional customer service during busy periods. This optimization enhances operational efficiency, reduces customer wait times, and improves customer satisfaction.
  6. Effective Marketing Campaigns: Retail heatmap analytics can provide valuable insights for marketing and advertising strategy. By analyzing customer engagement with promotional displays, signage, or digital screens, retailers can measure the effectiveness of their marketing efforts. This data helps businesses understand which marketing messages, visuals, or locations most attract customers. With this knowledge, retailers can refine their marketing campaigns, optimize their messaging, and drive better results.
  7. Real-time Monitoring and Adaptation: A retail heatmap analytics solution often provides real-time monitoring capabilities, allowing retailers to track customer behavior and store performance. This real-time data empowers businesses to identify emerging trends, respond to customer needs promptly, and make immediate adjustments to optimize the shopping experience.
  8. Competitive Advantage and Differentiation: Implementing a retail heatmap analytics solution can give retailers a competitive advantage by enabling them to understand their customers than their competitors better. Businesses can create unique and personalized experiences tailored to their target audience's preferences by leveraging data-driven insights. This differentiation can increase customer loyalty, positive word-of-mouth, and a stronger market position.

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In-store Heatmap analytics

Customer traffic funnel segmentation

Customer counting

Customer flow analytics

Customer re-identification

Technologies Used