Research Brief: How Returns Analytics Can Drive Good Customer Experiences
Note to reader: all charts represent segments of response data, the rest of which can be found in the final report once published.
Retailers are collecting large amounts of data from consumer returns, but how are they leveraging it to improve their business? As they continue to grapple with omnichannel purchases, retailers are applying analytics and identifying trends to learn how their product sales are performing across channels. Now they're looking to improve returns data and use it to drive better customer experiences.
Nearly half of retailers (48%) claim capitalizing on good customer experiences to drive loyalty and retention is one of their greatest pain points in terms of omnichannel purchases--the most widely acknowledged pain point among seven options (four not shown in chart).
Retailers know they need to adapt to market changes to provide these experiences; to do so, they need the right data. But data alone isn't enough to support decisions that bring about these changes. Retailers must analyze data contextually, even as they look to identify a set structure for doing so.
81% of retailers collect data on purchasing and return patterns, and 75% of retailers claim they regularly collect and act upon consumer data as part of a formal strategy. According to one supply chain vice president:
"We use data lakes [or] pools of information. Our analysts create models, [then] we overlay these models with customer feedback and data [to] create the customer experience."
Meanwhile, only 37% of retailers are collecting behavioral metrics besides purchasing and returns data for this purpose. This raises questions about the degree to which analysts can convert data into insights that drive their progress with customers.
Retailers must understand the entire customer lifecycle, analyzing each step from the time the customer experience begins then overlaying that data with retailers' operations. Retailers can use the data to create models that improves the customer experience while reducing claims and returns. "You have to leverage that data and continue to task and reform that data," says the supply chain VP.
When asked how leveraging data helps them improve business as a whole, 63% of retailers claim anticipating consumer behavior is among their top benefits--the most popular choice among six options (three not shown in chart).
For retailers, plans to improve customer experiences may take time as they learn to sufficiently identify and predict trends. This can become more difficult as retailers adopt complex systems. But by appreciating and analyzing data like demand frequencies, they will be able to create enhanced shopping and returns experiences for customers. On a granular level, they can better understand the relationships between customer responses to promotions, reasons for returns, what drives customers with high return rates, and how to win back estranged customers.
In our upcoming white paper, Leveraging Returns Data to Improve the Customer Experience, we'll explore how retailers can apply cognitive and predictive capabilities to returns, anticipate consumer behavior, and improve customer retention and loyalty. As retailers continue to grapple with omnichannel purchases, we'll share our analysis of how they are applying analytics and identifying trends, then identifying the elements that drive customer satisfaction and business success.
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