Andrea McVittie

Design Challenge

While early versions of the filtering and search experience on Vroom, an e-commerce site for used cars, were heavily patterned after those of competitors, my Search & Discovery team wanted to get to know our customers needs around shopping for a used car in depth, so that we could offer a quicker, more tailored experience.

A formal research group didn't exist at the company yet, and only basic demographic details about our customers were available, so working with my Product Manager, I set out to do quick, high impact research with low requirements from engineering or other teams.

Process, Findings & Insights

• Conducted user research into the impact of the current vehicle information
• Building on findings about the role of photos and vehicle details, conducted broader surveys around these areas
• Crafted a affinity diagram from hundreds of data points, to highlight and communicate areas of opportunity

To begin, I wanted to assess how useful the information we were offering customers on the current product page was to them. I crafted a card sorting exercise where I described the data on the page (ex: "manufacturers exterior color name" or "transmission type" etc.)

With the help of a few teammates we asked 8 people who had recently shopped for a vehicle to sort the cards describing the car data into piles, indicating how important that information was to their decision making while considering their purchase. Piles were labeled from "I must know this to make a purchase decision" down to "I don't care about this" and even "I don't want to know this."

As they sorted the cards into piles, we also conducted informal interviews about their purchase process, making note of points of interest to explore further, the process as a whole, pain points, etc.

A heavy focus by our interview subjects on both car feature details and photographs lead me to design two light-weight, open surveys to learn more about these areas of interest. I ran two onlione surveys on the Vroom website, one on the product detail page specifically asking about the photographs, and one more general survey asking about how we could improve the catalog/search experience. Nearly 400 responses were gathered.

To organize the hundreds of responses gathered across these three studies I constructed an affinity diagram, making it easier to summarize and discuss the main trends that my research surfaced.

Solution & Outcomes

• New filters targeted at the specific features users want to shop by
• Improved photography guidelines around the quality customers expected, and the details they wanted to see
• A better understanding of the entire used car shopping process through the eyes of our customers

The research provided a solid foundation for the entire team to evaluate our existing product information, and search/discovery interface, and begin customizing the experience to better suit our customers needs.

Using the insights about our customers and trends found within the affinity diagram I was able to work with my product manager to identify important filter functions the catalog needed to add to assist our users in getting to the right vehicle quickly. We selected some high priority options and worked together with engineering to build out these filters.

The research also helped us confirm that most of the car information we were providing was critical to our users, but assisted me in begining to rework the information architecture of the page so that the most vital information was presented more prominently.

Using the photography portion of our research, I also collaborated with our photo editor and photography vendors to begin using the user provided insights to improve the quality and helpfulness of the product photos we provided of each vehicle.

Why I Liked This Project

I enjoy mapping out what I think I need to know about my users and then crafting research sessions around getting authentic feedback, insights and observations.

I particularly enjoy conducting low tech, shoe-string-budget research that digs into a users process and looks for pain points and unmet needs where design improvements can significantly impact their experience.