Quick Overview
NielsenIQ integrated AI with data from point-of-sale systems, loyalty programs, and in-store sensors to provide real-time insights into shopper behavior. Collaborating with a multinational supermarket chain, AI identified underperforming product categories and optimized store layouts and promotions. This resulted in increased category sales, improved customer satisfaction, and more effective retail operations.
NielsenIQ
Company Size
Large multinational retail analytics firm
Revenue Range
Not publicly disclosed
Primary Challenge
Providing actionable, real-time retail insights to optimize product placement and promotions
Key Metrics
\- Real-time shopper insights\- Sales uplift in targeted categories\- Optimized store layout and promotional strategies\- Enhanced customer satisfaction
The Problem
Retailers lacked timely, actionable insights to respond to shopper behavior and optimize store performance
The Solution
AI-driven analytics platform combining POS, loyalty, and sensor data to detect patterns and recommend operational improvements
Results
\- Increased sales and category performance\- Improved customer shopping experience\- Faster, data-driven decision-making\- Enhanced promotional effectiveness
“Real-time AI analytics allowed the retailer to act swiftly and strategically, resulting in measurable performance improvements.”
NielsenIQ Client
Details
Industry
Retail & E-commerce
Departments
Data & Analytics
Use Cases
Market Research
Tags
GenAI
NLP
Scalability
AI Tools Used
No items found.
Sources
https://researchworld.com/articles/successful-ai-implementations-in-market-researchhttps://www.nielseniq.com/global/en/solutions/retail-measurement/
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