Where your products appear.
Margot is a personal stylist app. She reads someone's real wardrobe, dresses them from it, and points to a product only when something is genuinely missing. This page shows exactly where that product shows up.
What Margot is
Margot is an iOS and Android app, live on the App Store and Google Play, published by Yavren (Paris). Users photograph the clothes they already own. Margot categorises each piece, builds outfits from them every morning, and learns their taste from what they wear and save.
The audience is over 90% French-speaking: France first, then Belgium, Switzerland and Morocco. Margot carries no display advertising. Product recommendations are editorial, personalised, and disclosed as affiliate links.
How a recommendation happens
- 01The wardrobe is read
Each item is categorised by type, colour, material, formality and season. Nothing is recommended before Margot knows what someone already owns.
- 02A gap is identified
A deterministic styling engine of 49 rules compares the wardrobe against the outfits the user actually needs. It surfaces real gaps: no mid-season jacket, no shoe that works with the two dresses she wears most.
- 03A product fills that gap
The gap becomes a precise product brief: category, colour range, formality, price band, size. Margot matches it against the merchant catalogue and picks what fits both the gap and the user's taste profile.
- 04The user sees a product card
Brand, photo, price and a link to your site. The card says which gap the piece fills. Nothing is bundled, nothing is auto-added, nothing is incentivised.
Two other surfaces work the same way: the stylist chat, where a user asks for a specific piece and Margot answers with three to five real products, and Check Before You Buy, where the user pastes a product URL and Margot gives a verdict against the wardrobe they already own.
The product card
This is the placement, rendered exactly as it appears in the app.
Works with 7 pieces you already own · matches your neutral palette
Affiliate link. Margot may earn a commission. It changes nothing for you and nothing in the recommendation.
Why this traffic is worth having
The gap is identified first, from a real wardrobe. The user is not browsing, she is filling a hole she has just had explained to her.
Colour palette, price band and brand affinity come from her own profile. She is not shown a €400 coat if she has never bought above €120.
The piece is checked against what she already owns before she ever sees it. She knows what she will wear it with.
That is the honest trade. Margot's job is to make an existing wardrobe work harder, so she recommends rarely. When she does, it has been considered.
How we work with advertisers
- We ingest your product feed daily: deep link, licensed images, price, stock, EAN. Links and prices shown in the app come from your feed, never from a scrape.
- Traffic is in-app and editorial. One user, one wardrobe, one recommendation at a time.
- Affiliate relationships are disclosed on every product card.
- No PPC on your brand terms.
- No toolbar, no browser extension, no cashback, no incentivised clicks.
- No coupon or voucher-code site behaviour.
- No scraping of your site, ever. Feeds only.
Working with us
We are live on Awin as publisher Yavren, ID 3048471, primary region France. We are opening Kwanko, Effinity and Tradedoubler alongside it. If you run a fashion, footwear or accessories programme in France and want to see the app before approving, write to us and we will send a build and a walkthrough.
Status, kept honest: Margot already recommends real products to users today. The affiliate catalogue is being connected now, advertiser by advertiser, which is why you are reading this page.