Is converting its users into buyers effectively? is one of the top e-commerce site in France (ranked 537 in France). 0.9 million users visit this site every month. But, only 1.2% of these users buy products. We rate its effectiveness 1.2 out of 10. [1]

0.9 million



- 93%

- 95%

- 98.8%

Conversion Stats

  • Traffic: 0.9 million visitors every month through SEO/Ads/Retargeting.
  • Signups: 93% of visitors stay anonymous. Only 7% of them sign up.
  • Engagement: 95% of registered users don't engage. Only 5% of them add products to cart.
  • Conversion: Of the 5% users who add to cart, only 1.2% of them buy.

Comparing with its peers

We have classified as a challenger in its marketing effectiveness, when compared to its peers in France. It has relatively better engagement when compared sign ups.


It has 2 main bottlenecks in its marketing effectiveness:

1. Signups: 93% vistors don't signup

A huge number of the users who visit do not sign up. This is especially prominent in mobile website, where 96.1% of users don't signup. Without user's identity, the products are not personalized for individual users and there is no further chance of engaging the user through email. This causes the largest conversion drop off at

2. Engagement: 95% visitors don't engage

95% of the visitors who visit don't add products to the cart. An average user visits the site atleast 3 times before making the buying the decision. Currently, sends few emails (like cart recovery email) to re-enagage users. This inability to bring back registered users through personalized recommendations causes the second biggest drop off in conversion.

These 2 bottlenecks cause significant drop in conversion. We recommend channel specific solution to solve these 3 conversion bottlenecks. We recommend that you solve the anonymous users problem on mobile and registered but unengaged users on email.

Learn more about the sign up bottleneck in

Can't find the company you are looking for?

Disclaimer: This report is created by Guesswork Research Team based on the publicly available traffic data. We use this data to predict the internal metrics of e-commerce companies using our machine learning algorithm. These are indicative numbers. If you have any questions or feedback on this report, please write to us at