HILTON HEAD, S.C. -- Retailers interested in developing more sophisticated promotions and customer-relevant offers might want to consider improving their ability to collect data coming from their own stores.
Speaking before about 175 people at the Gilbarco 2016 Retail Technology Conference held May 17-19 in Hilton Head, S.C., Haya Ajjan, a researcher and professor of management information systems, Elon University, Elon, N.C., said knowing the customer was the overriding goal of data collection and analytics. Through such efforts, retailers can ultimately reduce costs and improve the effectiveness of marketing, promotional and inventory-management activities.
She identified four data-collection options that, in tandem, can significantly improve a retailer’s ability to understand and predict customers’ needs.
Retailers need to identify individual customers and customer characteristics in order to match them with in-store behavior and purchasing activity. Whether done in-house or through a third party, retailers should consider initiating some form of customer-specific loyalty program.
Whether it’s sensors rigged throughout the store to monitor item movement or a locator function in a customer’s app that’s tracked via cellphone Wi-Fi, retailers need to consider ways to gather information about what’s moving in their stores.
This could be something as simple as a cashier asking a customer if they want to buy gum that’s on special and the cashier hitting a “yes” or “no” key on the register. Other more sophisticated systems can record and track people’s facial responses to questions.
Cameras around the store can track people’s movement, or more sophisticated services can offer retailers “heat maps,” which use video to track and map out customer movement.
Through an electronic, app-based survey conducted during her session, Ajjan asked conference attendees if they used big data to help them make decisions. About half, 53%, said they used a mix between data and the combination of intuition and expertise.
She said retailers must migrate to make more data-driven decisions; however, in her experience, she said many companies struggle over trusting data vs. their own intuition.
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