Michelle Boisson

Role
Product definition, information architecture, user research and synthesis in collaboration with a UX researcher, collaborating with a data scientist to produce data-driven prototypes, workshop facilitation with stakeholders, requirements documentation and prototyping.

Observations
Through interviews and surveys, we also learned that used car shoppers are not interested in learning how a car performed when when it was new, which is what CR’s main reporting is about. They were much more interested in learning how other owners felt about the car. The closer they could get to speaking to the previous owner of a car, the better. In speaking with our car testing experts, we learned that, while we don’t test the same model every year, we do test them when their are major changes or redesign to the model.

Issues
The experience on Consumer Reports used cars information was pretty dire considering the rich information they’ve been collecting over the last 15 years. A used car model page was in fact a general description of the model and it’s performance over the last 10 years. This is not in line with how used car researchers look for information.

Solutions
I came up with an information architecture that would support our user’s research behavior in providing details about individual model years and leaning on smart use of user-generated reporting via our surveys.

While CR does not test used cars–they only test new cars, their annual survey of about 1 million vehicles tells the story of how used cars are performing today. This data was traditionally used to exact a reliability score for every model year. I proposed new ways of using that data so that we could report on used cars. It was a major shift in design, product, and analytics

Results

• Consumers are able to read and compare 10 years of CR data on car models, year by year
• Tighter integration of user-generated reporting and CR’s test data
• Alignment of consumer’s research behavior with the architecture of the interface and data that they find more appealing
• This architecture stemmed from my work with the mobile apps team, but is now being adopted by the website team

Prototypes

Initial Prototype http://4lwazs.axshare.com/view.html

Car Ownership App Interaction Exploration (concept: scroll through past and potential future issues)
http://michelleboisson.github.io/cr-mobile-mycarfuture/

Car Ownership Click Through (concept: predict my car’s future)
https://invis.io/DU9B24R6W#/56347919_Homepage_Android

My Role:
Product definition, information architecture, user research and synthesis in collaboration with a UX researcher, workshop facilitation with stakeholders, requirements documentation and prototyping.

Observations:
Most people looking into purchasing a new car tend to focus on which model is right for them, narrowing their choices to a few models, ignoring trim in the beginning. Once they’ve settled on a model, their focus will shift to selecting trims and options. Another observation revealed that car researchers are in a mode of constant compare, hoping to validate that the choice they’ve made is the right one.

Issues:
Consumer Reports car testing and reporting is second to none and a major driver for new signups. Despite it being one of the biggest franchise areas for the non-profit, there were many holes in the user experience that didn’t match how the target audience does car research. We were forcing them to decide on a trim or to draw their own conclusions when comparing models by jumping between tested trim pages in the interface.

Solutions:
In comparing the user’s research journey with the strengths in CR’s car testing , we came up with this statement: “We test cars to report on models.” This means, we can’t test every trim in a model, but we can use the data we have in the trims we do test to inform our reporting on a model. In aligning our focus with the major pain point of comparing and deciding on a model, we can be a better serve our members during the car research process.

To support the mental mode of constant compare, we represented every model with 3 data points: overall score, MPG and price, making it easier to compare models at every step of the journey. These were the three most important factors in beginning to compare models.

Results:

• streamlined user experience that aligns with how members do research
• turned a hole in the experience (the fact that we can’t test every trim) into an opportunity
• removed a lot of redundancies
• this architecture stemmed from my work with the mobile apps team, but soon after was adopted by the website team