Mentspot is a platform that connects people who need advice with those willing to give it. It's an innovative way to get help and learn from others without ever leaving the comfort of your couch.
Mentspot's Product Manager wants to provide users with a platform that is both engaging and intuitive. They hope to keep people coming back for more and using the platform on daily basis.
The idea is to optimize the listing of mentors and get users to view more mentor profiles so that they are more relevant to the user currently visiting the website.
We do this by implementing a recommender model that will recommend the most relevant mentor profiles for conversion based on time of day, week, device, location, and other factors.
We want to test if the recommender model is really improving retention, or if it's hurting it by accident. This we do by using the A/B testing template and choosing the retention experimentation goal.
The results show the impact of using a recommender model to find mentors. When 50% of customers saw results recommended by the personalized model, their conversion rate was 18% better than when they were shown randomly selected mentors! 🎉
Have you ever wished for a better way to retain your customers and increase user engagement? Well, with this powerful model, you'll be able to do just that! With a few clicks of the mouse, you can apply this new idea and watch it work its magic.
In no time at all, you'll see an improvement in retention rate and user engagement too! Simply connect your data and get blown away by the results! 🤯