'Freemium plans bring in more product usage and feed your growth loops so you can invest more in your product and less in marketing…' Amplitude blog
Hyperskill is a platform for learning STEM and programming languages. The web version of the platform has an audience of about 900k registered users.
Product: web application
Target audience: all users of the web application
Role: middle product designer
Team: product manager, UX researcher, lead designer, project manager, frontend & backend developers
Objective: increase the daily paying audience without losing revenue.
Timeline: August 2023 — November 2023
Results: MRR grows by 28%, conversion to subscription grows by 36%
The platform has long used a trial + subscription model for monetization. This model did not allow for effective growth of the project's audience. Based on competitive analysis results, the project team decided to switch to a freemium monetization model.
The transition to the freemium plan affected almost all parts of the platform interface. It was necessary to inform current users about the plan changes and new users about how they would learn. This required significant efforts from the entire team.
I designed the interface with freemium plan limits: the limits dashboard, cards on the pricing page, triggers and entry points for premium plan payment scenarios. Together with the team, I prepared a prototype for testing and made design adjustments based on UX test results.
For comparative analysis, we examined both programming education platforms like Codecademy, Mimo, and DataCamp, as well as big tech projects such as Duolingo. During the research, we discovered that on free plans, platforms impose limits on the number of tasks that can be solved per day and restrict access to key features. At the same time, the platforms inform users about the advantages of their paid plans. Based on this information, we decided to test the journey from user registration on the platform to the point where they exhaust their daily limits.
As the main limitation for users with the free plan, we chose the number of tasks a user can solve per day. Additionally, we restricted access to certain platform features: projects, hints, solutions of other users, and feedback.
However, freemium users can solve the daily task, review previously covered material, and read theory. This way, users can try out the platform's main features. When users encounter limitations, the platform suggests purchasing the Premium plan.
Before launching the first iteration, the team conducted a series of UX tests. During these tests, we checked whether users could see the limitations and understand how they work. For example, the limits panel required some improvements because users didn't understand when the limits would refresh.
To encourage users to purchase the Premium plan, it was necessary to tell them about its advantages. For this purpose, we included triggers leading to the purchase of the premium plan in various places.
After registering on the platform, the user's free plan becomes active automatically. Therefore, the user sees triggers to purchase the premium plan at various stages of learning: when choosing a track, on the subscription page, in the pricing section, and while solving tasks.
On the limits dashboard, the user can see information about how many tasks they can solve and how much time is left until the limits are refreshed.
From this dashboard, the user can also proceed to purchase the Premium plan. The main advantages of the Premium plan are shown in a separate modal window, as well as on the pricing page.
While solving a task, the user may encounter difficulties and refer to the hints provided by the platform. We decided to limit the number of hints on the Freemium plan to encourage users to purchase: 1 hint per solution, 1 solution in the task forum.
When the user reaches the daily limit, the message leading to the purchase of the Premium plan appears. However, the user can also proceed to other available activities.
After testing, we launched the first iteration, in which we implemented the limits and conducted user migration. During subsequent iterations, we gradually introduced trigger points leading to the purchase of the premium plan, updated plan names and conditions.
The following iterations aimed to explain the benefits of the premium plan to users and stimulate purchases.
The transition of the product to the new monetization model took about six months. The implementation of the freemium model increased MRR by 28% and conversion to subscription rate by 36%.
Refinements to the purchase scenarios continued throughout the experiment. In particular, a reverse trial was added, which should increase the number of paying users.
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© 2024 Viktor Seleikov