ShelfMatch has been a game-changer for our retail operations. The platform’s AI-powered shelf analytics and real-time product matching capabilities eliminated the guesswork from our merchandising strategy. We now get instant insights into out-of-stock risks, planogram compliance, and competitor pricing—all in one dashboard. The “Shelf Health Score” feature is genius; it quantifies shelf performance in seconds, helping us prioritize store-level actions.
What truly impressed us was the accuracy of their image recognition technology. Our field teams upload shelf photos via the mobile app, and ShelfMatch detects gaps, misplacements, and even pricing errors with uncanny precision. This has reduced manual audits by 70% and improved our on-shelf availability by 25% in just three months. Review collected by and hosted on G2.com.
While ShelfMatch’s API is refreshingly straightforward to integrate, developers might crave more granular documentation for edge cases—adding code samples for less common endpoints would streamline troubleshooting. The rate limits on the base pricing tier could be restrictive for high-volume users scaling rapidly, though upgrading plans is seamless. Lastly, while the pricing model is transparent, a ‘pay-as-you-go’ option would benefit startups with unpredictable API call patterns. That said, these are minor trade-offs for a service that otherwise delivers reliability and hassle-free scaling Review collected by and hosted on G2.com.
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