​Rate Your Lyft
How can we re-invent the experience of the traditional 5-star rating systems?

challenge. 
Our challenge is to create an alternative rating system that will better fit the needs of the drivers and shift the mental model of the users so that the system is able to accurately reflect experiences through the ratings.

my role.
user research - usability testing - paper prototyping - storyboarding

outcome.
We created a concept video for the alternative rating system we designed.

reflection. 
The biggest lesson I learned through this project is the benefit of realignment. We came in with many assumptions about how the problem should be approached and who the solve the problem for. However, as we gained insights from the users realized our approach was flawed and we needed to take a step back to consider the problem from a different perspective. My team and I learned the importance of not getting attached to ideas to allow for re-adjustment to create more successful outcomes. 

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how did we get there?

We listened to the users through researching on online sources & conducting interviews with both the drivers and users to validate our assumptions and findings. 

Finding #1
100% of drivers interviewed agree that one extreme rating have too large of an impact on overall ratings. ​

Finding #2
The system does not differentiate between if the low ratings is because of the driver's fault or external factors. ​

Finding #3
100% of customers did not realize that 4 stars is considered bad in Lyft's standards. ​

We reflected on the findings from competitive analysis and user research to create many, many sketches for different approaches we can take.  We realized there is a gap between what the users think they are communicating about their experience versus how it is interpreted so we focused our ideation on how we can close this gap and allow users to accurately communicate their experiences. 

We evaluated our sketches based on our goal of allowing the rating system to accurately reflect the user's experience and narrowed down on an initial solution to move forward with. This initial idea was focused on the back-end aspect of the application where the ratings will be interpreted through patterns of ratings rather than averaging them. 

We got feedback through interviews with our users (drivers and customers). The feedback was good. 

We realized that we were focusing solely on the one of the user group's experience, the driver's experience, and not enough about the customer's. This is why we came back and reframed our solution, we looked at how to improve the customer's experience while also creating positive impacts on the driver's experience as well.

We re-evaluated our results from the initial user research with affinity diagraming with our new mindset to consider the needs of both user groups. The result was we became more aware of the needs and motivation of the customers while giving ratings. 

With these new insights, we also wanted  to break out of the box about how rating systems are traditionally thought of. We reflected back to why the rating system even existed. As a result, we concluded that the rating system is just a way for companies to know whether the drivers are good enough.

“Would you ride with [driver] again?

We adapted the idea of using “re-watchabilty” as a criteria for judging the quality of a film for our context. We reflected on what it means for the customers to have a good experience, which was where the question “Would you ride with [driver] again?” originated from. We felt that regardless of what happens in the trip, if the customers are okay with having the driver again in the future, that could suggest that the driver should still be qualified as a driver.

We tested our idea to explore the experience users had with it. Through role-playing, usability testing and interviews we were able to gain insights to further refine our idea. 

"'would you recommend [driver] to a friend?' is more formal, friendly, and fair than asking 'would you ride with [driver] again?]'

We listened and refined our idea based on the feedback from our users.