Bring the signals together.
Start with exported feedback, organized around the products and variants your customers actually bought.
CUSTOMER FEEDBACK → BETTER PRODUCT DECISIONS
Every return
is a clue.
Your customers are telling you what to fix.
Find a clearer way to listen.
AI-assisted insights from returns, support conversations, and reviews—connected to the evidence behind your next product decision.
A product by Lindenwake
FROM CUSTOMER SIGNALS
TO SOMETHING YOU CAN ACT ON
TO SOMETHING YOU CAN ACT ON
Return note“Smaller than expected.”
Product review“Love it. Size up, though.”
PRODUCT BRIEF / 01Sample data
THE EVERYDAY TEE
A fit expectation gap.
A recurring theme across three feedback sources
A CHANGE TO TEST
Show garment measurements
next to the size selector.
Evidence → hypothesis → test
Illustrative example · sample data
Built around your products. Grounded in customer evidence.Designed for decisions.
THE MISSING CONNECTIONThe feedback is everywhere.
The feedback is everywhere.
The answer isn’t.
“Not as expected” closes a return ticket. It doesn’t tell your team whether to change the size guide, reshoot a photo, or rethink the product.
The useful details are scattered across return notes, support conversations, and reviews. SKUClue brings a simple idea to that complexity: connect the clues, product by product, so a repeated frustration can become a specific decision.
↩ Return reasons≋ Support conversations✦ Product reviews
One product briefWhat happened. What to try. What to measure.
FROM FEEDBACK TO ACTIONFrom “why?”
From “why?”
to “what next?”
A practical loop for small ecommerce teams.
AI helps connect the dots. Your team makes the call.
Find a pattern. Check its roots.
Review recurring themes alongside their source excerpts. Keep what customers said separate from what we infer.
Choose a change worth testing.
Prioritize a concrete action, assign an owner, and define a measure before deciding whether it worked.
A LOOK AT THE THINKINGSee the clue.
See the clue.
Follow the evidence.
Explore three possible product briefs.
Choose a product to see the story change.
FIT & SIZING
The fit isn’t matching expectations.
Customers describe a closer fit than the product page led them to expect.
OBSERVED IN FEEDBACKSource excerpts
Return noteR-014“I ordered my usual medium, but it’s tight across the shoulders.”
Support conversationS-008“Could you share the actual chest measurement for a size large?”
Product reviewV-021“The fabric is lovely. I wish the page had said it was a slim fit.”
SUGGESTED ACTION
Make the fit clearer before checkout.
Add garment measurements beside the size selector and state “slim fit” in the product description.
Owner: merchandising TEST & MEASURE
Test the page before changing the product.
Compare fit-related returns per delivered order after a complete return window. Track conversion and exchanges, too.
These excerpts suggest an expectation gap; they do not establish a sizing defect or prove a change will reduce returns.
Synthetic products and feedback. Explore the concept—no store connection required.
A BETTER KIND OF PRODUCT INTELLIGENCEMore than a theme.
More than a theme.
A reason to act.
A useful insight should survive a simple question:
“What makes us think that?”
Evidence you can inspect
Source excerpts belong beside the finding, so your team can judge the context.
Suggestions you can challenge
A customer’s words, an AI interpretation, and a proposed action are different things. We keep them distinct.
Progress you can measure
A change is a hypothesis. Define what success looks like, then watch for the outcome.
INVITING DESIGN PARTNERSLet’s turn your
Let’s turn your
“why” into a next step.
Run an independent ecommerce brand? Help shape a product around the questions your team needs answered.
Start a conversationWHAT WE’D EXPLORE TOGETHER
- Where feedback gets lost today
- Which product decisions feel uncertain
- What would make an insight actionable
SHAPED WITH YOU
[email protected] Your hardest product questions.
A thoughtful workflow, designed together.
A FEW PRACTICAL DETAILS
Good questions.
Can I connect my store today?
Not yet. SKUClue is in development. The example above demonstrates the approach we’re exploring; it does not connect to a store or process your data. Contact us to discuss the first workflow and what your team needs.
Who is SKUClue for?
Independent ecommerce brands whose merchandising, operations, or customer experience teams want to understand recurring product issues. We’re particularly interested in teams that already review customer feedback but struggle to turn it into clear product decisions.
Will it tell us which changes reduce returns?
The goal is to identify evidence-backed changes worth testing. Feedback alone cannot prove causation. Your team would still need to test a change and measure its effect over an appropriate return window, accounting for product mix, seasonality, and other changes.
How do we get started?
Email [email protected] with a little about your brand and the decisions you’re trying to make. Start with a description of the problem; please don’t email customer personal information or raw customer records.