Webshops & e-commerce · Data, reporting & decision-making
Return reasons and reviews turned into product fixes
Free-text return reasons, review comments and support chats are clustered per product each week: sizes running small, missing parts, misleading photos, so buying and content teams see what to change first.
- Avg. time saved
- 2–4 h/week· ≈ 13 h/month
- Rollout
- CoreDays 15–35
- Who it is for
- Online retail and marketplaces
In short
Return reasons and reviews turned into product fixes: Free-text return reasons, review comments and support chats are clustered per product each week: sizes running small, missing parts, misleading photos, so buying and content teams see what to change first. It typically gives back 2–4 hours a week to whoever does this by hand today. Built for: Online retail and marketplaces.
Typical hours saved per week for the people doing this by hand today, from the 2026 report's ranges. The AI writes what that time makes possible.
Example
Comes in
Last week: 214 returns with a reason text, 96 new reviews
The AI
- Clusters reasons per SKU and separates product issues from delivery issues
Comes back
“Women's jacket 2231: 41% returned as ‘too small’. Add ‘runs small, size up’ to the page. Estimated 60 fewer returns a month.”
Similar solutions
- Webshop anomaly detection (payments & coupons)Alerts instantly if card payment breaks or a mistyped coupon code causes loss-making purchases.1–3 h/week
- True margin per product after returns, shipping and adsMarketplace commissions, payment fees, shipping, returns and attributed ad spend are pulled into one margin figure per SKU and channel, so the weekly report shows which bestsellers actually lose money.3–6 h/week
- Competitor price watch with margin-safe repricing suggestionsPrices of your key products are checked daily on competitor shops and price-comparison sites; where you are undercut or leaving money on the table, the AI suggests a new price above your margin floor for one-click approval.2–5 h/week
- Morning trading brief in plain languageYesterday's orders, conversion, average basket, ad spend, stock-outs and refund rate are explained in a few sentences on chat every morning, with the one thing that changed and why.2–4 h/week
Related terms
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