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Examining Share of Visits in the Convenience Store Channel: the Functional Versus the Emotional Shop

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This guest blog was authored by Brian Czarny, Chief Marketing Officer of Factual, a leader in location data.

This year, we assisted dunnhumby with their 2019 dunnhumby Retailer Preference Index: Convenience Store Edition by providing high-quality location data to help with market analysis. Capturing real-world visits is one of the most important retail KPIs today, as channel and media fragmentation is elevating competitive pressures and making it increasingly difficult for brick-and-mortar retailers to grow or even maintain visits. By delving into the data we provided, dunnhumby was able to compare Share of Visits between convenience stores that ranked in the top quartiles and those that ranked in the bottom. Ultimately, they were able to determine that Share of Visits does not differ much across the top two and bottom two quartiles of stores. In fact, they were the same at 14.4%. With the initial results in hand, the RPI analysts wondered: Why was there so little difference between the quartiles, given that almost every other performance measure favored the top performers?


Although Share of Visits data doesn't necessarily provide definitive answers on why the quartiles are so similar, the analysts hypothesized that the Convenience channel has a dual nature and preference patterns are split across emotional and functional drivers. While dunnhumby had previously found that in the Grocery channel, what people think and feel aligns nicely with what they do and how they shop, Convenience proved to be different. It is less clear why some Convenience retailers capture visits through a connection with the customer while other retailers mainly attract functional shoppers and quick trips with their numerous locations. In other words, emotion wins the day for some, but true convenience wins for others -- the sheer number of stores can be effective at capturing trips for gas, a cup of coffee, or getting milk for your morning cereal.

After comparing Share of Visits to other attributes, analysts concluded that there was no correlation between Share of Visits and Assortment, Store Experience, Ready-to-Eat, Private Brands, or Price. However, all stages of the Marketing Funnel and conversion rates were significantly correlated with Share of Visits, which further highlights the importance of location data in measuring and forecasting performance.

These location-based findings supports dunnhumby's initial hypothesis that shoppers do not need to love their retailer to pay it a visit. But it does raise a question: if the retailers who have more of an emotional connection with their customers continue to grow their footprint, will there be increasing pressure on the more functional retailers? To find out, he analysts grouped regional Convenience retailers into two buckets -- More Convenient and Less Convenient -- and analyzed whether either group had a higher Share of Visits. It turned out that there was a statistically significant difference. The Convenient group saw a 15.6% mean Share of Visits while the Less Convenient group saw a 12.7% mean. This is simply association and not causation, but it does suggest that as regional retailers expand and increase their geographical footprints, they could put pressure on the larger incumbents.

If simply having convenient locations becomes less of an advantage for larger retailers, then emotional connection will begin to play a larger role in determining customer preference. In fact, dunnhumby is beginning to see this happen as smaller retailers continue to expand, winning both the emotional and financial battle. As the market and consumer preference evolves, retailers big and small will have to stay on top of the game and leverage the highest-quality data and technology to help them better understand, reach, and engage their customers.

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FOR RETAILERS

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FOR BRANDS

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The approach outlined below is not intended to replace these formal tools; rather, these observations are intended as a kind of 'toe in the water' to help retail leaders form early hypotheses and points of views. These are rules of thumb, heuristics culled from global experience. Later, leaders might use these observations to informally check progress from time to time as a way of assessing whether the "program in the stores matches the program in our heads".

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