Returns are an inherent part of e-commerce businesses, from broken packages to customers having the wrong product expectations. However, the way many companies view these returns is on a case-by-case basis; this loses you the bigger picture and prevents you from connecting the dots of underlying issues that affect vast swathes of your customer base. Imagine you are a DTC apparel company. You want to see what categories of customers return items, ranging from repeat versus new customers or by CLV or marketing cohort. Knowing which customers are returning items will help you uncover customer insights and highlight hidden customer friction points.
Shopify: order_id, product_sku, customer id, customer segment
Returnly: return code, return reason
Zendesk: support text
By breaking down returns by customer segments, you get a better sense of which customers are encountering issues, even when they were expected to be top customers. Let's say the Marketing team thought they found a very lucrative segment. Marketing focuses on KPIs like click-through rates and conversion rates and finds that men aged 18-25 purchase a lot from your company. However, by breaking down returns by Customer Segments, your team discovers that this segment disproportionately returns items compared to order volume. These customers complained that the fit of the clothes felt off. As a result, you notify marketing to adjust their targeting towards other segments that have higher retention and repurchase rates, while also passing along feedback to the Product team about these complaints.
Create an account and instantly connect insights across internal teams. Have custom integrations or use cases you'd like solved?We're here to help.