![]() ![]() For example, if a large portion of your returns are coming from a region with more expensive shipping costs, you can try to reduce those costs by offering customers in that region a discount in exchange for forgoing your standard returns policy. Rewarding behaviors you’re seeking can be very effective in reducing returns volume. ĬRM data can also offer insights into better ways to incentivize certain customer behavior. This can help you better plan for returns volume from various consumer segments and regions.Īccording to a 2020 survey conducted on the state of online returns, more than 60% of consumers surveyed now bracket their purchases, and certain segments (e.g., those under age 30) are even more likely to do so. ![]() For instance, you may want to identify which customers are more likely to return certain products. To better understand customer habits and behaviors (both individually and in broader segments), cross-reference customer relationship management (CRM) data with returns data to explore emergent trends. Accept Skip to content search close menu close For more information on the Postal Service’s cookie policies and how the Postal Service uses cookies to improve your experience on and its affiliated websites, including, please see our Privacy Policy. By clicking Accept, you represent to the Postal Service that you are located outside the European Economic Area and consent to the Postal Service’s use of cookies. To improve your online experience, the Postal Service ™ uses cookies on our website to remember user preferences, tailor banner advertisements to your interests, and ensure a smooth shopping experience.
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