Your retail data is worth millions. Start monetizing it.
Promotions, sales, shopper behavior, assortment performance, and shelf execution: CPG brands will pay for all of it. CINDE turns your platform data into a recurring revenue stream.



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CPG brands spend billions on trade promotions with almost no visibility into what happens at the shelf.
CPG brands spend billions on trade promotions with almost no visibility into what happens at the shelf. Retailers sit on the intelligence they need: sales, promotions, shopper behavior, shelf execution. Packaging and selling that data is a new revenue line with no new products or stores.
CINDE generates analytics across sales, promotions, assortment, shopper insights, and shelf execution. CPG brands subscribe for access.
Syndicated data is periodic and market-level. Your platform data is real-time, retailer-specific, and tied to actual execution.
Both sides work from the same platform and methodology. Category reviews, promotion analysis, and basket insights happen in one place.
Real outcomes, proven in production
Frequently asked questions about retail data monetization
Retailers package platform analytics (sales, promotions, assortment, shopper behavior, shelf execution) into a subscription where CPG brands pay for access. The retailer generates recurring revenue; the CPG brand gets intelligence unavailable from syndicated providers.
Retail media is advertising: sponsored search, display ads, offsite media. Retail data monetization is intelligence: selling shelf-level execution data and joint business planning tools to CPG partners. Both generate CPG-funded revenue, but they serve different buyer needs and different budget lines.
Typical data includes sales and volume analytics, promotion effectiveness, assortment performance, on-shelf availability, planogram compliance, share of shelf, and shopper and household insights. The top five data types by CPG demand: customer and promotion insights (25%), assortment analytics (18%), store intelligence (18%), supply chain data (14%), and customer segmentation (12%).

