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Store heatmap
The electronics retailer, wanted to improve their sales and customer service by analyzing the flow of people into their stores. We created a system using Machine Learning, image detection, and face recognition. The system tracks visitors' movements and the most viewed shelves and products. This information helps the store to focus on selling popular products and to avoid unpopular ones, ultimately improving the sales process.
9%
increase in sales
100%
dead zones removed
About the client
One of the largest electronic retailers in Eastern Europe.
Tech stack
Python
Flask
reCAPTCHA
PostgreSQL
MySQL
AWS
Challenges & solutions
Challenge
Measure the impact of promotional displays.
Improve customer service in busy areas.
Remove dead zones.
Effectively place products.
Solution
Built a system based on Machine Learning, image detection and face recognition.
All cameras work in a centralized form and pass data to a single server that processes the information received.
Solution analyzes the movement of visitors around the store, keeps track of shelves that are viewed most often and products which clients skip.
Solution optimizes the process of selling goods, since the information received makes it possible to concentrate on selling goods in which the visitor is most interested, and to identify not popular ones.
DATAFOREST provides meaningful shopper-behavior Insights. They are very responsive and effective, trying to engineer and offer the best fit solution.
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