New research guide: The Confidence Economy, how AI is changing fashion commerce.

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Reduce returns

[ 05 ] · Use case

Try it on before it ships. 

Try it on before it ships. 

Try it on before it ships. 

Most returns are not a logistics problem. They are a decision that was made without enough information.

No credit card · Live in under an hour

A shopper seeing a complete outfit rendered on her own photo in Elara before checkoutSeen on her · before checkout

[ 01 ]

the situation

What does this look like today?

Online apparel returns run at 20–30% against single digits in store, and every one costs you twice — the shipping and the margin on the piece that comes back worn once. The shopper did not change her mind; she never saw the outfit on herself, in her size, with the shoes, until it arrived.

[ 02 ]

the shopper’s side

What does the shopper experience?

01

The doubt

“Does this work on me?” — size chart open, cursor at the tab bar.

02

The photo

One photo, in the widget, deleted after the session.

03

The look on her

The whole outfit head to heels, in her size and colour.

04

The bag

Bought with the surprise already had.

[ 04 ]

the number

What does it do to the numbers?

0×
Conversion, assisted sessions
+0%
Average order value
Industry standards for AI-assisted shopping sessions. Your holdout report shows your own.

Industry benchmarks commonly put online apparel return rates at 20–30%, far above the single digits typical in store. The gap is mostly information: in a fitting room the shopper sees the outfit on herself before paying. Showing the whole look on her own photo, in her size, before checkout moves that moment back to where it costs nothing to change her mind.

[ 05 ]

what it replaces

What are brands doing instead?

ElaraSize-guide widgetsFree-returns policies
Shows the outfit on the shopper
Whole look, not one item
Captures size once
Costs nothing per return avoided
Measured against a holdout

[ 06 ]

who it is for

Which brands get the most from it?

Dresses, tailoring, occasionwear, denim — any category where return rates are above 25% and “didn’t suit me” beats “didn’t fit”.

RETURNS > 25%

“DIDN’T SUIT ME” > “DIDN’T FIT”

DRESSES · TAILORING · DENIM

[ 07 ]

proof in 30 days

How would I test it?

01

Day 1 — install, sync, write the opener.

Four lines or the Shopify app. The catalog syncs within the hour; the opener is set in Widget Studio.

02

Days 2–30 — run it against a holdout.

10–20% of sessions never see Elara. Nothing else on the store changes.

03

Day 30 — read the report.

The number to watch: return rate on orders from assisted sessions.

[ ? ]

questions

Questions a Head of Ecommerce asks first. 

Questions a Head of Ecommerce asks first. 

Questions a Head of Ecommerce asks first. 

Anything else, book twenty minutes and ask the founder directly.

No. It answers “does this work on me”; your size guide answers “which size”. Elara shows both.

Only if the shopper saves the look; otherwise deleted after the session and never used for training.

“Didn’t suit me”, “not as expected”, “wrong colour” and “ordered several to choose” — the ones that come from deciding without seeing.

Indirectly: size is captured in the brief and remembered, so repeat orders are placed in the right size.

Return rate for assisted sessions against the holdout, in the report, once your returns window has closed.

No; rendering happens off-page and only on request.

Give your store a stylist that actually sells. 

Give your store a stylist that actually sells. 

Give your store a stylist that actually sells. 

Thirty days free. Live in under an hour. Measured against a holdout from day one.

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