Intelligent retail in-store traffic analytics that helps increase revenue per m2

Industry: Retail
Location: Denmark

Project

The client is an international company that develops and manufactures advanced energy-efficient LED lighting solutions. They approached Euristiq to build a retail IoT system for in-store foot traffic analytics. The system should collect data and form heat maps to help determine the most popular zones in stores. As an additional requirement, the solution should help control energy consumption with individual light dimming settings via an iPad or iPhone.

Key features
we delivered

  • Cost-efficient in-store foot traffic analytics

  • Data collection and heat maps

  • Smart control of energy consumption

Tools and technologies

ASP.NET MVC
Azure
Azure SQL
MongoDB
Entity Framework Code First
Redis
AngularJS
StructureMap
AutoMapper
HTML/CSS
JavaScript
jQuery/Bootstrap

PROBLEM

No actionable insights about the customer journey in the retail store

Our client, an international company that develops and manufactures advanced energy-efficient LED lighting solutions, needed Euristiq to empower their software development expertise with a cross-functional performance team. The project’s goals were to develop an IoT solution to help client’s customers to increase revenue per m2. improve in-store customer engagement, and collect data to make effective marketing decisions.

SOLUTION

Real-time foot traffic analytics as an IoT solution for smart retail

In-store traffic counting, data collection, and analytics

We developed a system that uses triangulation to determine the most popular zones in the store. The solution uses intelligent LED track lighting with the True ColorTM system that has a high CRI (Color Rendering Index) of 93. It aggregates data in the form of heat maps which give useful insights for store owners. Heat maps are taken every 5-10 min and can illustrate the customers’ journey. 

The system also allows controlling light energy consumption and offers individual dimming control via an iPad or iPhone. In addition, various groups and light scenes can be timed to activate at different intervals of the day. Thus one can achieve more attractive retail spaces.

RESULTS

In-store consumer behavior analytics to help make effective marketing decisions

An intelligent foot traffic analytics system tracks customers around the shop and builds heat maps with the most popular zones. The data can be analyzed to make strategic marketing decisions in placing products and advertisements to increase revenue. The lighting in the store can also be optimized thanks to the solution – it can be programmed to dim or brighten in certain hours of the day.

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