Fitnote product preview / Turn return feedback into a starting point for improvement Explore the demo
KOEN
Interactive demo

APPAREL INTELLIGENCE Fitnote for apparel brands

Turn returns
into product improvements.

Find insights in recurring size and fit feedback
to improve your next product page.

We are building a tool that groups return reasons by product, compares them with measurements and fit details, and drafts product-page improvements for merchants to review.

Early-stage prototype · Explore synthetic data without signing up

ffitnote / workspaceSAMPLE DATA
PRODUCT OVERVIEW

Return feedback insights

Sample period · 7 days
Feedback notes24notesSynthetic data
Products reviewed3productsSize · fit related
Priority reviewShirtCheck product info

Recurring feedback Illustrative grouping

Feels narrow
12
Too long
8
Sleeves long
4
Counts are illustrative synthetic notes.
Illustration of a sample cotton shirt
Cotton everyday shirtSKU · CT-001
Review product info
Review the “relaxed fit” description.

Feedback about body width appears repeatedly. Check the garment measurements and actual fit before updating product information.

Check the evidence. The merchant decides.View review note →
✓
From feedback to a reviewable changeProduct by product, with evidence.
Three perspectives for
better product information
01 Recurring customer feedback
02 Product facts
03 Merchant judgment

LISTEN. UNDERSTAND. IMPROVE.

Look beyond return counts
to understand why.

Customer feedback comes in many forms, but improvement opportunities can be connected.
Explore the workflow we are building.

“It feels tight across the chest”“The body is narrower than expected”
01 / FEEDBACK GROUPING

See recurring themes at a glance.

Group return reasons by product and variant to spot recurring themes.

Product informationStatus
Chest width by variantCheck needed
Model size wornListed
Fit and ease descriptionReview needed
02 / PRODUCT CONTEXT

Find information gaps.

Compare feedback with measurements, fit descriptions, and model details to identify what to check first.

PRODUCT COPY / DRAFT

Add measurement details,
and review whether the fit description matches how it wears.

Source notes 3Merchant review
03 / REVIEWABLE SUGGESTIONS

Turn insights into product-page edits.

Draft suggestions based on product facts. Merchants review and decide what to publish.

BEFORE / SAMPLE COPY

A relaxed fit that feels great on everyone.

A model size alone may not help shoppers judge how relaxed the fit will feel.

“I expected it to feel as roomy as it looks.”Synthetic return note
AFTER / REVIEW DIRECTION

Give shoppers details that set clearer expectations.

  • Add measurements by variant and explain how they are taken
  • List the model’s measurements and size worn
  • Describe the fit based on a verified try-on
✓ Apply only after verifying product facts

MAKE THE NEXT PAGE BETTER

Replace assumptions with
the information shoppers need.

“It runs small” does not automatically mean the product is defective. Fitnote is designed to organize feedback into hypotheses to review and show what product information to verify.

Explore a review note ↗

A CLEAR WORKFLOW

Start with a clear
first review.

The first version will start with return notes and product information.
CSV upload and live analysis are planned, not available yet.

01

Prepare return notes

Organize product, variant, and return reason. Leave out customer names, contact details, and addresses.

Product / variant / return reason
02

Compare product information

Review measurements and fit descriptions to understand feedback in context.

Measurements / try-on details / fit description
03

Review suggestions

Merchants review source feedback and product facts, then decide what to change.

Evidence / checks / suggested edits

EXPLORE THE PRODUCT

For your product,
what would you check first?

Switch products to explore how sample return notes connect to review suggestions.

Fitnote / Product feedback reviewSynthetic-data demo

PRODUCT REVIEW NOTE

What to check first

Product-page review direction

Merchant review before publishing

This demo shows prewritten examples. Live AI analysis, file uploads, and store integrations are not available yet.

GOOD QUESTIONS

Before you
get started.

What is available now
and what is still planned.

Can I analyze real return data now?

This site currently offers a product overview and synthetic-data demo. CSV uploads and AI analysis are planned; this page does not collect customer data.

Who is Fitnote for?

Fitnote is being built for independent online apparel retailers who want to use size- and fit-related return feedback to improve product pages.

Do I need a store integration or app?

The demo runs in your browser without signup or installation. The first live-analysis version is planned around CSV and product information; store integrations are not available yet.

Does Fitnote guarantee fewer returns?

No. Suggestions are hypotheses and review directions for product information. Any impact must be validated with real sales and return data and merchant feedback.

What are the pricing and launch timeline?

The demo is free to explore. Pricing and launch timing for the full product are not set; we will share them after building live analysis and validating with merchants.

THE NEXT IMPROVEMENT IS IN YOUR FEEDBACK

Start by rethinking how you
read return feedback.

Explore how Fitnote could help improve your next product page.

Explore the product demo ↗

ABOUT FITNOTE

Product information
that learns from returns.

Fitnote is an early-stage product project building a tool to help independent online apparel retailers understand size- and fit-related return feedback and improve product pages.

We currently have a product overview and synthetic-data demo. Live CSV analysis and merchant validation are planned next.

DEMO DATA

About the demo data.

Products, return notes, counts, and analysis shown here are synthetic examples to explain the product flow. They are not real customer data.

Product selection and note downloads run in the browser. This demo does not send user input to a server and includes no analytics or tracking scripts. Web fonts are requested from Google Fonts. Hosting access-log practices depend on the hosting provider.

Data processing, retention, and deletion policies will be prepared before live analysis launches.