Cabela's Uses Analytics to Predict Shopping Behavior
Outdoors superstore Cabela's uses real-time analytics from Retail Equation to predict and optimize in-store shopper behavior. Using advanced analytics, the retailer plans to generate incremental net-sales revenue for its 29 destination retail stores.
Cabela's also will use return optimization to address previously overlooked customer interactions - such as returns or exchanges - and improve the value of its return process; typically increasing store comps by as much as 2 percent. This revenue impact is accomplished by validating the integrity of each return.
"The financial impact of The Retail Equation's solutions had an immediate, positive effect and greatly exceeded our expectations," said Michael Copeland, vice president of retail operations, Cabela's. "Not only does it create an improved overall customer experience, but we have seen a significant net-sales increase."
Cabela's also will use return optimization to address previously overlooked customer interactions - such as returns or exchanges - and improve the value of its return process; typically increasing store comps by as much as 2 percent. This revenue impact is accomplished by validating the integrity of each return.
"The financial impact of The Retail Equation's solutions had an immediate, positive effect and greatly exceeded our expectations," said Michael Copeland, vice president of retail operations, Cabela's. "Not only does it create an improved overall customer experience, but we have seen a significant net-sales increase."