Hey Product Hunt! 👋 I built Retrnly because I kept seeing the same pattern with ecommerce founders I talked to: returns get treated as a logistics problem (process the refund, restock the item, move on) instead of a data problem. Meanwhile the actual reason a product keeps coming back, whether it's a size chart that runs small, a photo that doesn't match the real color, or a stitching issue nobody's flagged internally, sits buried across a returns portal, a pile of reviews, and a support inbox, and nobody has time to connect the dots between them. The original idea was simple: pull return reasons, reviews, and support tickets into one place and cluster them by product. But early on I realized the "so what" mattered more than the data itself. A list of complaints isn't useful; a prioritized list of fixes is. So the product evolved from "here's your return data, organized" to "here's what to change first, and roughly what it's worth fixing." Right now it works with CSV uploads or a direct Shopify connection, and it's built for small and mid-sized teams who don't have a data analyst on staff to do this manually every month. I'd love feedback, especially from anyone who's tried to tackle returns analytics before. What worked, what didn't, and what you wish existed? Happy to answer anything here today!

Retrnly

Return prevention analytics for Ecommerce brands

Return prevention analytics for Ecommerce brands