Is fnac.es converting its users into buyers effectively?

Fnac.es mid-size e-commerce site, ranked 4227 among the top websites in Mexico. 4 million users visit this site every month. But, only 0.7% of these users buy products. We rate its effectiveness 1 out of 10. [1]

Visitors 4 million			Registered 4%		Enagaged 3%			Buyers 0.7%
		Anonymous - 96%		Unengaged - 97%		Abandoned - 99.3%

How does fnac.es compare to its peers:

We have classified fnac.es as a challenger in its marketing effectiveness, when compared to its peers in Mexico. It has relatively better activation when compared to engagement. It has 3 main bottlenecks in its marketing effectiveness:

1. Activation: 96% vistors don't signup

A huge number of the users who visit fnac.es do not sign up. This is especially prominent in mobile website, where 97.8% 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 fnac.es.

2. Engagement: 97% visitors don't engage

97% of the visitors who visit fnac.es don't add products to the cart. An average user visits the site atleast 3 times before making the buying the decision. Currently, fnac.es 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.

3. Mobile: Fastest growing channel with lowest conversion

Users are increasingly using mobile website to browse fnac.es. It is the fastest growing channel with 63% of traffic already. Unfortunately, it has the lowest conversion when compared to other channels. In fact, its conversion is 1/3 when compared to its desktop counterpart.

These 3 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.

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 research@guesswork.co

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 research@guesswork.co