Pleazup is a free social network to share gift ideas tactfully with your family.

The value proposition is to share a list of gifts that we would like to receive, while preserving as much as possible the joy of surprises through anonymous interactions. You can make a suggestion or book a gift idea without the recipient knowing your identity.

It's a  twitter-like social network : everybody could follow anybody without accepting request. But you're always notified when followed, and you can block anyone if needed.

I cofounded the company with Diane Frachon ( The project started in La cantine then Numa  (, back then a free coworking in Paris. We lately moved to Réunion Island and were incubated by the regional startup program.


Pleazup revenue model is based on affiliation. If a gift idea is a merchant product, for instance a book or consumer appliance, we try to find merchant websites that sell it, and we provide a link to purchase it. If the merchant also offer an affiliate program, we earn a commission after each sale if the user previously click on our link during the last month.


We have 2 strategies to reduce the chicken and egg problem that every social networks face: our service is only truly useful when a whole family use it, but users only want to use it when it's already useful.

Firstly, we try to reduce onboarding friction of building the network. We ask new users to share their email or phone contact and automatically match existing users. We also notify them whenever one of their contact signup.

Secondly, we optionally provide a public url of your gift idea list, shareable to anyone without authentication.


Social networks share certain technical generalities. For instance, they need complexes database queries to answer complexes social questions (ideas liked by friends of friends, etc).

They also need an  algorithm to sort their content. Notifications could be displayed chronologically, but suggested content from our "Inspirations" feature require a recommendation engine, like Facebook EdgeRank ( We implemented a similar algorithm, weighting freshness, popularity, and monetization. Essentially, a recommendation engine is a search engine without textual queries: what should you see if you don't know what you want?

Our affiliation business model also require to match gift ideas with product pages from affiliate merchant websites. Since textual information from gift ideas is rarely specific enough, we developed an image search engine restricted to merchants websites.

- Native iOS (Swift) & Android (Java) mobile apps
- React web app
- Material design system
- Node backend using Parse Plateform (
- Heroku hosting
- Search with Algolia
- Recommender engine using Google Vision API