The commercial case
Sizing, returns and imagery are usually owned by three different people in a fashion business. They are the same problem measured at three points.
Where the margin goes
- #1
- Fit is the most common reason for fashion returns
- 2×
- A return costs the outbound shipment again, plus handling
- 3
- Touches per return: inbound, inspection, restock
- 0
- Revenue from a return that ends as a refund
The exact numbers differ by category and market. The shape does not: an avoided return is worth more than a recovered one, and a return you understand is worth more than a return you merely processed.
Pick the one that matches your bottleneck
If returns are size-driven, start with YourSizer
Fewer wrong sizes leave the warehouse, and shoppers who were hesitating between two sizes buy one instead of two — or instead of none. Measure: product-page conversion on widget-engaged sessions, size return rate per SKU, share of orders with a recommendation.
If returns eat your support inbox, start with ResReturn
Self-service takes the “how do I return this” ticket out of the queue entirely, and store credit and exchange keep revenue a refund would lose. Measure: return tickets per 100 orders, time to resolution, share retained as exchange or credit, restock latency.
If shooting is the bottleneck, start with NoShot
Products go live without waiting for studio time, and a category page looks coherent because the model and light are constant across it. Measure: days from receiving stock to live product page, cost per product image, returns tagged “not as pictured”.
Numbers we will not fake for you
Every attribution number in our dashboards records the signal that proved it, and orders are deduplicated across signals. If a figure cannot be proven, it is reported separately rather than folded into the headline.
What we report
- Assisted orders, with the proving signal named
- Recommendation distribution per SKU and per size
- Return rate and return reasons, per product and per reason
- Portal completion rate and outcome mix
What we tell you to check yourself
- Run an A/B split on your own store rather than trusting a benchmark
- Compare return rate on widget-engaged versus non-engaged orders
- Watch the size distribution before a production run, not after
What a rollout looks like
Connect the store. App install or credentials. Catalogue and orders sync; nothing is written back yet.
Load your charts. Size charts imported or ingested from images, then reviewed. This is the step that decides accuracy.
Pilot on a category. One category, one placement. Verify the recommendation against products you know well.
Turn on measurement. Attribution and analytics before scaling, so the rollout can be judged on your data rather than ours.
Scale, then add the second product. Most brands add returns after sizing, or sizing after returns, within a quarter.