Prevent returns and keep customers happy, this is what smart retailers do.
Retailers are investing aggressively in new advanced analytics capabilities so they can leverage everything from POS data to social media comments to panels to beacons to gain new insights into consumer behavior.
One of the top priorities for the use of this data is to prevent returns and preserve the customer experience. But there is a gaping hole in the picture, and that’s in understanding what data to collect and how to interpret it.
What if you had these sorts of insights into what products were coming back, and why?
What if you knew the reason so many blue shirts are being returned is because they were placed in a warehouse slot where the green shirts were supposed to go?
What if the batteries are bad in all those pedometers you’ve been shipping?
What if your size 8 shirts are mis-marked as size 6?
Retailers don’t often know about these issues with their products because they don’t collect good data. This oversight is costing them in customer satisfaction and repeat business.
Retailers need to use data to prevent returns.
Collect better data on returns forms. Write reason codes that really fit the merchandise. Include a comment box so customers can volunteer detail. Collect social media comments that mention returns.
Scrutinize returns. Build a process for receivers to inspect returned product and note not just reason codes, but also vendors, product categories, etcetera. Encourage free-form notes on product condition. Consider taking images of returned goods.
Quickly spot patterns in returns though analytics. Analyzing this data can help e-tailers to identify and correct problems quickly and gain incredible insights into real customer experience with their products – and future products they may sell.
Prevent returns, preserve the customer experience, and increase the customer lifetime value. These should be top priorities for all ecommerce companies.