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

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Complete the look

[ 02 ] · Use case

One product page becomes four. 

One product page becomes four. 

One product page becomes four. 

A dress sells a dress. Nobody on your site sells the blazer that goes with it.

No credit card · Live in under an hour

Elara building a complete outfit around the dress a shopper is viewing on a product pageSilk slip dress · three pieces added

[ 01 ]

the situation

What does this look like today?

Your average order is one item, and “you might also like” shows four more dresses. The shopper who was about to buy one thing leaves with one thing — or with nothing, because the decision got harder, not easier. Around 70% of carts are abandoned; most of them held a single item that never became an outfit.

[ 02 ]

the shopper’s side

What does the shopper experience?

01

The piece

She is on the silk slip dress, 40 seconds, size chart twice.

02

The offer

“Still deciding? I can build a full outfit around this piece.”

03

The look

Camel coat, slingbacks, top-handle bag, in her size, £1,000 total.

04

The bag

The set added in one tap; swap any slot without starting over.

[ 04 ]

the number

What does it do to the numbers?

+0%
Average order value
0.0×
Items per session
Industry standards for AI-assisted shopping sessions. Your holdout report shows your own.

Baymard Institute puts the share of abandoned online carts at around 70%. Many of those carts hold a single item that never found its context — the dress without the layer, the shoes without the bag. Building the outfit around the piece already in view gives the shopper a reason to finish, and gives the order a second, third and fourth line.

[ 05 ]

what it replaces

What are brands doing instead?

Elara“You might also like”Manual bundles
Pairs across categories
Built from live stock in her size
Anchored on the piece in view
Shopper can swap slots
Measured against a holdout

[ 06 ]

who it is for

Which brands get the most from it?

Any brand whose items-per-order is stuck near one; strongest for separates, tailoring, footwear and accessories that need a context to sell.

SEPARATES · TAILORING · ACCESSORIES

ITEMS / ORDER < 1.5

PDP DWELL > 30S

[ 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: items per session and AOV.

[ ? ]

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. Bundles are fixed; a look is built live around the piece in view, in the shopper’s size, and every slot can be swapped.

Merchandising rules in the dashboard pin, boost or exclude products per slot.

It works on product, collection and cart pages; on a collection page it starts from the first piece the shopper engages with.

Never. The lift comes from items, not margin.

Seconds; the pieces are already related in the Style Graph before the shopper arrives.

Yes, in the merchant dashboard’s insights.

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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