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Unveiling the Power of External Data: Revolutionizing Customer Behavior Analysis in Retail

Have you ever gone into a retail store, bought something, and then been prompted at checkout or via email afterwards to fill out a survey about your shopping experience and methodology? In the retail sector, understanding customer behavior has long been a key point of focus for many companies. From grocery stores to clothing shops to hardware stores, understanding purchase intention and customer behavior is an essential business function and, done right, can be a powerful differentiating factor.

Currently, many retail stores use only internal data collected from previous search history to inform decisions, resulting in a lesser picture of each consumer, their behavior, and how to adapt to those buyer personas.

Through external data, retail businesses can get a much better understanding of consumer behavior, allowing them to make more informed decisions about stocking stores, promotional campaigns, pricing/sales, and more. Following the path of a consumer’s entire life, not just their in-store or online purchasing patterns, can be a vital differentiating and competitive factor that can draw customers in droves to stores that deeply understand their needs, wants, and tendencies. Understanding buyers is the key to successful marketing campaigns, sales tactics, and forward-facing business practices.

Some retail stores are making strides to dive deep into customer behavior research and analytics. Amazon is a prime example of an online and in person retail business that is maximizing external and internal data collection to provide the best experience for their customers, including predicting future purchases and reminders to repurchase past products that might be running low.

Through the use of external, quality, and well-priced data, retail businesses can improve the experience they offer customers, increasing buyer retention, loyalty, and the accuracy of demand-driven predictions/decisions.

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