Many companies struggle to accurately identify who buys their products and which potential customers exist in the market. Often, businesses rely on broad survey data that fails to provide precise audience segmentation. This leads to inefficient marketing strategies, missed opportunities, and unnecessary wastage. Without detailed knowledge of buyer profiles, executing targeted and cost-effective campaigns becomes challenging.
Why we’re better
shopeyeQ Audience Observation & Experimentation leverages Nielsen IQ (NIQ) panel data and combines it with thousands of shopper profiles created on platforms such as Meta, Google, and Amazon. This approach allows us to determine which specific customer segments (e.g., "Bargain Hunters", "Premium Shoppers") are purchasing a product. Through this observation, we can better gauge the size of the reachable audience and target them more precisely. Additionally, experimentation using the RFM model (Recency, Frequency, Monetary Value) and A/B testing helps identify and focus on the most valuable customer segments, optimizing marketing spend and increasing ROI.
Empower Your Retail Success
Discover how our platform's advanced features—like dynamic clustering algorithms, real-time insights, and predictive analytics—empower you to drive smarter growth.
Maximize Promotional Impact
By combining observation with experimentation, shopeyeQ provides a comprehensive marketing solution that enables more effective and targeted campaigns, delivering the best possible results.
1- Data Acquisition:
- Import NIQ panel data and online platform data.
- Define relevant shopper profiles based on segments such as „Convenience Shoppers“, „Organic Buyers“, etc.
2- Data Analysis (Observation):
- Analyse who has purchased your product and identify potential market segments.
- Assess the reach and size of your target audience.
3- Experimentation:
- Select hundreds of profiles for further investigation and segmentation using the RFM model.
- Conduct A/B tests to filter out the most valuable profiles.
4- Campaign Optimisation:
- Continuously review and adjust target audiences and campaigns based on results and real-time data.
Optimizing Retail Insights
This section presents a series of case studies that demonstrate the transformative impact of POS clustering on retail operations.
Explore Similar Use Cases
Turn Insights into Impact with shopeyeQ
