How to Use Returns Data to Improve Customer Relationships and Prevent Returns

Customer Service Representative

When a product of yours does not live up to a customer’s expectations, the initial excitement over the purchase will turn into frustration and disappointment, and the possibility of that customer buying from you again will fly out the window.

This is why creating a plan for promoting customer loyalty and repeat business is massively vital to any retailer. Obviously, the most ideal plan is to make sure that your products satisfy or exceed customer expectations so that customers won’t return them.

To help you execute this plan, consider looking into your returns data.

The Importance of Returns Data

Returns data is a priceless source of customer insights that you can use to implement better and manage your returns process. The earlier you pinpoint and resolve an issue with your product, the higher your chances of fostering stronger customer relationships.

The problem is that for most retailers, using returns data for preventing issues is uncharted territory, but one that can help with providing a better shopping experience for customers. Applying data analytics with help from your RMA software or app to product returns could uncover all kinds of insights that you might not have gotten otherwise, for instance:

  • Learning that a button is missing from a full shipment of your best-selling button-down shirts.
  • Finding out that the material utilized in your newest t-shirt release is scratchy, hard, and easily irritates the skin.
  • Pinpointing an increase of returned black socks since they were stored in the spot where gray socks were supposed to be stored.
  • Seeing a significant error in the measurements listed in the description of a product you sell in your online site.

Leveraging Returns Data

packaging boxes

You will only need to conduct some additional steps to obtain insights like those listed above. These include:

  • Inspecting the returned products. You should take note of the reason codes, product categories, associated relevant vendors, etc. and the checker’s observations of the returned products. It’s also a good idea to take photos of the products and then tag them with the reason codes.
  • Ensure your returns data is accurate. Unfortunately, the reason codes aren’t always accurate. To remedy this, check and tweak your reason codes accordingly to better fit your products, and put a comment box on all returns forms to make it easier on customers to supply relevant information. Make sure to regularly check the web, your website, and social media accounts for reviews or mentions of your products and shopping experience.
  • Identify patterns faster, using analytics. Integrate returns analytics to your returns management strategy to garner insights that were previously unattainable from real experiences of customers. You should then utilize this knowledge for ensuring improved orders and customer experiences. Quick identification of the common reasons for returns and implementing strategic tweaks to help prevent them from happening in the future will improve customer relations and save you money in the long run.

An effective and data-driven returns management process is tactical ammunition that any retailer should have to fight decreasing profit margins and product returns. Otherwise, you may find yourself left in the dust by your competitors.

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