Mood Tracker - Zenklub
November 2020 to January 2021.
Zenklub is a digital platform that is mostly known for offering online therapy. However, the company also offer others types of products in the App, like a mood tracker and consume of contents.
In addition to offering therapy to users, Zenklub wanted to offer a complete immersion of emotional well-being and therefore made available content such as podcasts, yoga sessions, texts and tests on the App.
The purpose of this research was to understand whether this ancillary product was important to users or not, and how we could improve the functionality.
Insights about contents:
Power User: 5% of users who use any type of content do it more than 3 times a week.
User profile: 60% of users using the functionality are B2C.
Therapy sessions: 21% do not do therapy on the platform.
Insights about mood tracker:
Power User: 32% of users who use any type of content do it more than 3 times a week.
User profile: 73% of users using the functionality are B2C.
Therapy sessions: 34% do not do therapy on the platform.
Interview and Insights
At the discovery phase of my project, I conducted user interviews in order to get a better understanding of the problem. We prefer to follow up with users who use mood tracker as the data suggests it is a more important feature for the user.
The interviews was done in one week.
Why did I use this search method?
After understanding a little better about the profile of users who used the application's mood tracker, I decided to use the interviews to get more depth of these profiles and the greatest pain.
How many users did i interview?
I interviewed 10 people. 5 people considered power users and 5 people who used the tool but no longer use it.
What was I most curious about?
The main objective was to understand how users use the tool, why they used it or stopped using it.
Based on the interviews and quantitative data we set up one persona. We referred to them throughout the entire product development process.
The persona was built at this moment to synthesize the research we've done, in this way the pains and the user profile are always exposed during the design and implementation process.
It was important to show the product and development team who we are making changes to and why.
After the interview, together with Squad's PM, we organized the survey results by value for the user and the size of the effort that each feature would bring to the development team. What we defined as a priority in a first version of the mood tracker were:
Add notes to the records.
Show users' past records.
Show a first version of the analysis on emotions.
Wireframes began to be made and discussed with the technology and product team.
After we came to an agreement on what best represented the surveys, we decided to do usability testing before releasing the functionality.
After launching the product, I did a testing round in order to reveal possible usability problems.
What was I aiming to find out with the user tests? I wanted to make sure that the experience of recording and analyzing emotions was easy for users.
What method did I use for testing? I use de method moderate, because I want to see the difficult and see the face of the users too.
According to users, they missed the moodt racker to add notes. This need is also linked to the personalization and individualization of each record.
Now when the user clicks on a reason for his emotion, he has the option to write you a personalized note to the record.
Show users' past records
Another important point for users is to be able to view their records made in the past days. In the previous version, the user was only able to register but was unable to consult past records.
In this functionality we think we carried out a usability test on a high-fidelity prototype to understand what is the best way to view mood records for users: through a monthly or weekly calendar.
The vast majority of users found it easier to understand the monthly preview version. This version requires fewer clicks, and has proved to be more intuitive as well.
Analysis of emotions
We gave the user an analytical view of their emotions. he can know what affects his mood, for example: family makes me happy, work makes me anxious.
In this way we hope to make the functionality more useful and add more value to the user