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Retrnly analyzes return reasons, reviews, support tickets, and product data to show which products and issues drive avoidable ecommerce returns. It groups feedback by product and cause, flags at-risk products, estimates savings, and delivers prioritized fixes: better sizing guidance, clearer descriptions, sharper imagery, and quality fixes. Import via CSV or connect Shopify, track past analyses, and export reports. Built for founders, product, ops, and CX teams cutting return costs.
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!
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About Retrnly on Product Hunt
“Return prevention analytics for Ecommerce brands”
Retrnly was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #159 on the daily leaderboard. Retrnly analyzes return reasons, reviews, support tickets, and product data to show which products and issues drive avoidable ecommerce returns. It groups feedback by product and cause, flags at-risk products, estimates savings, and delivers prioritized fixes: better sizing guidance, clearer descriptions, sharper imagery, and quality fixes. Import via CSV or connect Shopify, track past analyses, and export reports. Built for founders, product, ops, and CX teams cutting return costs.
Retrnly was featured in Analytics (173.6k followers), Artificial Intelligence (478.1k followers) and E-Commerce (41.8k followers) on Product Hunt. Together, these topics include over 155.1k products, making this a competitive space to launch in.
Who hunted Retrnly?
Retrnly was hunted by Katlego sithole. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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