What is Rewards App?
Rewards app is an app dedicated to gig workers who work with ride-hailing apps like Uber and Lyft and food delivery apps like Uber eats, Doordash, Grubhub, etc. The app shows insights about gig earnings and work data.
Creating monetisation model and improving engagement
When I joined the team, the app was a light MVP with just a basic dashboard which was showing a summary of the user’s earnings from gig apps. The app wasn’t generating any revenue and users weren’t engaged with the product as much as we wanted. So our goal was to create a monetization model and improve engagement.
First of all, I wanted to understand our potential users better and that’s why I was actively participating in user interviews, analyzing data from them, and creating personas. This was a good foundation for a team brainstorming session to gather ideas for solutions that could solve the key pain points of our personas and help with ideation for the monetization model. Having the outcome of the mentioned activities, I started working on features. For this project, I selected a few case studies: creating an incentive model to monetize our free user base and creating functionality that would suggest workers which app they could make the most money with to improve engagement.
Implementing the incentive model was a complex project with many design and usability testing iterations. The result of it was the introduction of the new incentive section of the app which became the most popular among users and also allowed customization which brings many potential monetization mechanisms.
Another feature I worked on was suggesting gig workers which apps would bring the most income based on the app usage data from other users. The result of this was increasing overall engagement.
If you read this and are still interested in knowing more, let’s go through it in more detail and start with understanding users.
I was working closely with the user researcher, participating in user interviews, processing data, and creating personas. As the result, we came up with 5 personas and focused on persona Alex when it comes to building solutions.
Having personas allowed us as a team to run a solutions ideation session. When the ideas gathered were translated to tickets and prioritized, I moved to the next stage of my process and started working on implementing ideas.
Creating incentive model
One of the biggest challenges of this project was the proposed logic for the incentives suggested by the business stakeholders. The main idea of it was to create logic that would allow users to get points from the gigs they do and exchange them for the internal currency (gig coins). Then using gig coins, users could purchase gift cards. On top of that, we would need to add a limitation on the amount of points exchanged per month and introduce an expiry date for points. All of that was supposed to help control the cost and increase engagement.
The idea of exchanging points for coins seemed overwhelming from a user experience point of view, so we decided to test it first.
I started working by creating a user flow that presents the logic of the proposed idea.
Based on the agreed flow I started to work on wireframes and iterated until I reach a state of wireframes that I could use for usability testing. The next step was validating the idea by running usability testing.
I started with writing down all the assumptions and based on them I created a script for testing. I prepared two scripts since I wanted to test the path for a new user and the path for a user who is already familiar with our app. Based on the prepared scripts, I created two prototypes. Considering distance and time zone limitations, I decided to run unmoderated usability testing.
I also allowed users to give open ended feedback about the new flow we proposed.
Results and feedback
Though many participants understood what should be done in order to get a gift card, the results weren’t satisfying, and the most important was the negative feedback we received about the new logic itself.
Now that I had feedback from users, it was easier to challenge the logic and push for a different concept. After giving it a second thought, having a long discussion about the logic, and running a brainstorming session with the UX team, the idea of a new concept was born.
We would introduce challenges with a limited number of spots which would limit the gifts budget. Users would be able to choose the goal of the challenge from the proposed ones. Each goal had a number of earnings the user would aim for in a month and if they would reach that goal, they would get coins which can then be spent on gift cards.
The idea was translated into mockups and I prepared one more round of usability testing for it which had way better feedback from users and seemed less confusing for them.
Later we ran a few more usability testing studies to validate the changes we applied after each iteration.
Most of the users joined challenges which boosted engagement and made it the most popular section in the app. Challenges are customizable, which gives the business the possibility to partner with different gig companies that would like to pay to promote their own challenges.
Best gig apps to work with
One of the outcomes of our user research and personas creation exercise mentioned earlier was the following hypothesis: Showing estimated earnings for each app in the user’s area, would increase retention and engagement.
Based on the data we had, there was a possibility to predict earnings if the user would work with various apps in their area based on the earning patterns of all the other users nearby. My main task was to create a solution, test it, and iterate on it based on the outcome of testing.
When the problem and idea for the solution were clear, I started working on designs. My goal was to create a section in the app where users could see which apps would bring the most income. One challenge I faced was the fact that the data was time sensitive, so it had to be presented to the user for the current time block, not for the entire day. This required clear communication to the user.
After a few iterations, I landed on the final version and prepared for usability testing for it. Due to lack of time, timezone differences, and distance limitations, I decided to run unmoderated usability testing with our users. I wrote down all the assumptions I had and created a script based on it. Based on the script I prepared the usability test.
Results of usability testing
Among other minor issues usability testing helped to uncover that:
- users thought that we were showing them which apps they completed the most gigs with instead of estimated earnings if they were to work with those apps
- users thought that data is shown for a week instead of few minutes/ an hour
Based on the feedback, I decided to change the header and to make the time period more prominent in order to address the main issues.
The “Best apps now” section became one of the most popular sections in the app and improved user’s daily engagement.