How increased the free-to-paid ratio by 73%  is an online booking software to organise your business. Specifically tailored toward practitioners and specialists, EasyPractice has helped over 20,000 customers simplify their day-to-day operations.

The client contacted me with the request to analyse the website traffic and figure out how they can improve the sign-up and trial-to-paid ratio. 

As with almost every client, the process started with the Analytics Health-Check. Since it’s a SaaS client, we decided that it could be much more beneficial for them to use two analytics products: Universal Analytics (Google Analytics) and Mixpanel. 

Mixpanel is an excellent tool for product analytics, and if you are a SaaS company, there are not many alternatives. You can easily track the sign-up ratio, trial-to-paid ratio, retention rate, LTV, acquisition costs of specific paid channels, and behaviour data of your users. 

The main reason why I didn’t recommend them to use only Mixpanel is that there is no better tool to work with organic data than Google Analytics. Google Analytics helps you to track Google Search organic traffic properly. Google Analytics has native integration with Google Search Console. The primary analytics tools for SEO marketers.

After my review of existing analytics, we understood that there are missed actions that we want to measure. Therefore I prepared the implementation plan with the information for the developers and brief implementation specifications for us to have a summary of every event we want to measure on the website and, more specifically, why we want to measure it.

You can see the example of the Mixpanel implementation specification below, and you can open it on the full screen here.

Mixpanel Implementation Spec Example

When we understood that we had all the necessary events in Google Analytics and Mixpanel to proceed with further analyses, we decided to wait a few months to collect the data for reliable insights.

I always recommend to clients not to rush analysing the data and letting tools collect fresh and new data after Analytics Health-Check. You can explore the data, but the insights you will receive won’t be accurate or will be biased because you won’t have enough data for statistical inferences.  

If you received ideas from analysing data, but statistics can’t prove them, these are just assumptions, nothing else. 

In the meantime, when Mixpanel was collecting the data, I prepared the Mixpanel dashboard for to track weekly business performance. It included the following key metrics:

  1. New sign-ups
  2. Funnel (new users to paid users)
  3. Number of bookings created
  4. Weekly Active Users or WAU
  5. Week 1 or W1 Retention 
Mixpanel Dashboard Created for EasyPractice. It was blurred due to NDA.

After the data gathering process finished, I delved deeper into analysing what was happening on the website and why new users left the platform. The following tools were used:

  • Mixpanel and Google Analytics Reports
  • Mixpanel JQL
  • Mixpanel API
  • Python. Such libraries as Pandas, Numpy, Matplotlib, Plotly, SciPy, 

The critical insights were:

  • The main reason new free users didn’t convert to paid clients was that they didn’t engage with the product very much. 47% of new users made just one session, which usually finished without understanding how EasyPractice works. 90% of the first sessions lasted no more than 5 minutes.
  • A significant percentage of clients leave EasyPractice right after the onboarding flow. From the observation, it can mean that they misread “free access” information on the page and didn’t think they needed to pay for the program.
  • A group of new users used search to find if the platform had some specific app and couldn’t find it. Therefore it was essential to collect all search keywords the users used. It could help a client to build a new feature that clients require. 

  • 75% of all new users spent no more than 2 days, 8 hours, 14 minutes and 20 seconds making 5 sessions. If the client wants to convert users, he has only a few days. If they leave, most likely, they won’t return. Moreover, this also makes us think that an email campaign isn’t the best way to engage the users but push notifications and in-app messages. It would be best if you worked with them when they were on the website.

The client spent a few next months creating a new onboarding flow to improve the engagement rate for new users. You can try it yourself at 

According to the client, the new onboarding flow helped to improve the trial-to-paid ratio by 73%. 

Here is the client’s testimonial.

“I had the pleasure of working with Ihar twice now and both times was great experiences. He is communicative and proactive! I did not experience anything else than a great cooperation between us! Thanks, Ihar!” – Oliver Lindebod,⭐️⭐️⭐️⭐️⭐️

If you are interested in analysing your product users, please contact me