5 min
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
- 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
- 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
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