Under the hood

Your store's returns,
fully decoded

Every Monday ReturnIQ pulls data from every corner of your store, finds the patterns costing you the most money, and tells you exactly how to fix them.

01
Connect your store
Link Shopify, Amazon, Gorgias, Zendesk, and your review platform. One-time setup, takes 2 minutes.
02
AI ingests everything
Every return reason, 1–3 star review, support ticket, and survey response from the past 7 days is pulled and read.
03
Root causes identified
Every signal is classified into a root cause. sizing, photo mismatch, defect, shipping damage, or buyer's remorse.
04
Ranked by dollar impact
Not just volume. each cause is ranked by how many real dollars it's costing you in margin and processing fees.
05
Specific fixes generated
For each root cause, ReturnIQ writes the exact fix. new size chart copy, image flags, supplier alerts, packaging notes.
06
Digest in your inbox
Every Monday morning, one plain-English email. No dashboard. No login. Just the answer and what to do next.

We read every signal your customers leave behind

Most stores look at return reasons in Shopify and nothing else. That's maybe 30% of the picture. ReturnIQ pulls from every place customers tell you something is wrong.

When a customer returns something and says "it didn't match the photos". and five other customers left a 2-star review saying the same thing. and three support tickets mention it. that's a pattern. ReturnIQ connects those dots automatically.

  • Shopify & Amazon return reasons and refund data
  • 1, 2 and 3-star product reviews
  • Gorgias and Zendesk support tickets mentioning returns
  • Post-purchase survey responses
  • All pulled automatically every Monday at 6am

Connected sources

Shopify Amazon Gorgias Zendesk Reviews Surveys

This week's signals

60 Shopify returns
45 Amazon returns
30 support tickets
40 low-star reviews
25 survey responses

Every signal gets a root cause. not just a label

Claude reads the full text of every return reason, review, and ticket. Not keyword matching. actual understanding. "The jacket looked navy online but it's clearly black" gets classified as photo mismatch, not just "wrong item."

Six root causes cover 95% of all e-commerce returns. ReturnIQ maps everything to one of them so you can act on patterns, not individual complaints.

  • Sizing confusion. size charts missing or misleading
  • Photo mismatch. product looks different in person
  • Quality defect. item broken, damaged, or poorly made
  • Shipping damage. damaged in transit
  • Buyer's remorse. changed mind
  • Competitor switch. found better elsewhere

Root cause breakdown

Sizing confusion
75%
Photo mismatch
55%
Quality defect
40%
Shipping damage
25%
Buyer's remorse
15%

Ranked by real dollars. not just return volume

A product with 5 returns costing $89 each and a 40% margin loses you more than a product with 20 returns at $20 each. ReturnIQ calculates the true cost of every return driver. margin lost plus the $15 average cost to process each return.

This is the list you actually need to prioritize your week. Fix the top item and you get the biggest financial return for your effort.

  • Margin impact calculated per SKU
  • Processing cost ($15 avg) added to every return
  • Annualized projection so you see the full picture
  • Supplier batch flags when defects come from one batch

Financial impact this week

Root cause Returns Cost
Sizing confusion 38 -$1,847
Photo mismatch 22 -$940
Quality defect 14 -$728
Shipping damage 8 -$312
Buyer's remorse 5 -$195
Total weekly loss -$4,022

Not just what's wrong. exactly how to fix it

ReturnIQ doesn't stop at the diagnosis. For each root cause it generates a specific, actionable fix. And for the top 2 impacted SKUs it rewrites your product description, size chart copy, and listing bullets so you can approve and publish immediately.

  • Sizing issues → new size chart copy with exact measurements
  • Photo mismatch → flags which specific images mislead
  • Defects → supplier batch flagged, QC hold recommended
  • Shipping damage → packaging spec recommendation
  • Updated listing copy ready to copy-paste into Shopify

Generated fixes

01
JACKET-L-GRN sizing. Add chest measurement in cm to listing. Suggest customers size up if between sizes. Current chart missing shoulder width.
02
DRESS-S-RED image 1. Main image shot in bright studio light makes fabric appear lighter. Replace with natural light photo to match real color.
03
Batch #GRN-2024-11. 14 zipper defects traced to Hangzhou Textiles Nov batch. Recommend QC hold on remaining inventory.

One email every Monday. No dashboard needed.

Every Monday morning the full analysis lands in your inbox as a plain-English email. No login. No dashboard to check. No notifications to manage. Just the answer and what to do.

It's written for a founder or ops lead who has 5 minutes and needs to know what to fix this week. Numbers first. Jargon never.

  • Delivered every Monday by 10am your timezone
  • Forwarded to your whole team in one click
  • Archive becomes your return history over time

Ready to stop losing money
to preventable returns?

Connect your store in 2 minutes. Your first digest lands this Monday.

Start 14-day free trial →