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CASE STUDY: Smarter Solutions for Retail – Analyzing Customer Product Interaction

How a leading retail chain transformed their business by analyzing customer-product interactions and improved customer experience through product-specific in-store advertisements.

Introduction

With the advent of IoT and advanced analytics, retail businesses can benefit from latest technologies to gain valuable insights into customer behavior; how they navigate the store, what they buy, when they buy it, and which marketing “levers” are responsible for sales.

The solution, integrated with Bluetooth Low Energy (BLE) sensors, helps to identify patterns in customer-product interactions at retail stores and provides analytical insights, besides displaying product-specific advertisements in real time.

Additionally, analytics software helps retailers conduct dwell analyses—how shoppers browse products and what aisles they visit frequently. This enables retailers to improve store layouts and assortments to optimize sales.

Information which was once thought to be out of reach for retail stores can now help marketing and management teams measure and respond to consumer demand.

Client Profile

The client is a leading retail chain with more than 300 stores across the United States of America. 

Business Requirement

There was a growing need to analyze customer-product interactions to gain better insights into product-specific conversions.

  • Track consumer interactions for displayed items in the store, whether sold or unsold
  • Optimize planogram and product assortments throughout the store
  • Identify missed sales opportunities
  • Display product-specific advertisements in real time

Business Transformation

A seamless combination of BLE technology, a customer-facing iPad application, and server-side analytics form the core of the solution. The motion of BLE sensors attached to products is tracked continuously. When the motion signal received for a product is above the cutoff value, the movement is registered. The count and duration of such product interactions are reported to the server.

The solution enables the store to track product-specific conversions of individual products across the shop floor. Unlike traditional metrics which only analyze sales reports, the store can measure consumer interactions with individual units prior to the point of sale, revealing key data on items both sold and unsold. This sensors and analytical backbone of the application creates relevance around each interaction based on quantifiable data.

Point of Interest Advertising

The platform enables retailers to assign specific in-store advertisements for individual products using an iPad application. Once a customer picks up a product, the iPad application displays the assigned advertisement on a screen nearby. By displaying product-specific advertisements in real time, in-store promotions can now be customized for each product at the point of interest.

Key Features

  • Product movement detection algorithm coupled with BLE sensors
  • View count and duration of product-specific interactions
  • Hourly, daily, and monthly analytical reports on customer-product interactions
  • Spot advertisements triggered by customer-product interaction

Business Benefits

  • Provides valuable insights into product-specific conversions
  • Enables planogram revamp to optimize product placement and prepare for seasonal sales
  • Helps to create offers based on shoppers’ purchasing patterns
  • Obviates consumer involvement and reliance on personal information to generate in-store analytics reports
  • Maximize customer engagement through spot advertisements 

Technologies

Bluetooth Low Energy(BLE), Ruby on Rails, and iOS SDK

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Picture of Vishnu Shankar

Vishnu Shankar

Associate Analyst, Digital Marketing, QBurst is a global product development and consulting company with a strong focus on new-generation technology platforms. We provide a broad range of services around Mobile and Web Development, Big Data Analytics, Cloud, User Experience Design, DevOps, and Testing.

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