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C-store data used to be limited to weekly delivery (at best) focused in sales and trend, but with little to no detail and even less chance for understanding how consumers shop and the choices they make in-store. Those days are gone. New data acquisition and analysis capabilities for c-stores are helping not only a wider array of c-store operators, but help CPG brands remove a long-lasting blind spot and drive revenue growth through that channel at rates they could only dream of, even in the face of the post-COVID “new normal.” These tools allow CPG brands to monitor and mine performance in c-stores by the hour, down to the SKU, enriched by the powerful ability to understand consumer behavior and geographic differences. This has enormous implications for everything from merchandising and assortment to product development, marketing strategy, and activation. It promises to be a rich vein of information for everyone who mines it. The Angels in The Details These analytics platforms have been specifically developed for the unique circumstances of c-store transactions. Unlike grocery and big-box retailers, c-store visits can be less planned, the basket mix can vary more predictably by time of day, and customers’ trip missions can be quite different from other retail channels. This is amplified by retailers focus on food service solutions, categories uniquely available in c-stores, or the possibility of a purchase following a fuel stop. By connecting c-store ERP systems to POS data, loyalty and other data, retailers and CPG brands can gain a full cycle view of c-store commerce activities and trends, with key line of sight to trip and basket choices. This data is collected in or at near-real time and analyzed as the “heartbeat” of the channel. This is in sharp contrast with legacy reporting systems for c-store sales that only publish their metrics weekly, often with a minimum of 7-day lag. In contrast, access to data and insight in near-real time can help CPGs and retailers make decisions and implement them at the right time, while also allowing for strategy or tactics development that are not as time-sensitive. Moreover, these legacy systems can provide only limited, if at all, basket-level details, loyalty/tender associations, or timestamps for day parts required to get a detailed view of this channel. Older systems only provide information for general business drivers like sales and price, derived from aggregated data. Moreover, the newer solutions provide rich…

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