Avvo Q&A

Project date: 2017
My Role: UX Designer
Other team members: Product Manager, UX Researcher, UX Designer, Full Stack Engineers
Project description: Avvo’s Q&A product allows anyone to post a legal question, and get immediate responses from local lawyers. Q&A accounted for Avvo’s highest traffic pages, and often served as the first touch point for a new user. My team’s focus was to improve engagement, and convert new users.

Responsibilities:
Research & testing
Wireframing
Prototyping
Visual design
Front-end
Data analysis
QandA-on-screen.png

The Challenge

Avvo’s Q&A product was already a great tool for people at the beginning of their legal Journey (and throughout it to a lesser extent). It helped people answer questions like: “Do I even need a lawyer for this?”, “Should I take action?”, “Am I understanding this correctly?”. The other great part about the product was that it provided a huge amount of user-generated content that was valuable for other people in the same situation. This meant that Q&A pages ranked very highly in Google searches, and for a company that makes money on ads that meant they were very valuable. The problem was that these pages had a very high bounce rate, and low engagement from users coming in from google. We hypothesized that this was either because A. They immediately got the answer they came for, and thus saw no reason to stick around, or B. The question they landed on was too specific and wasn’t really what they were looking for.

Our team’s goal was to increase the number of pages per visit by helping users get to an answer and give them a next step.

My process

Working on this product gave me the opportunity to use data in ways that I never had before. Avvo’s Q&A pages ranked very highly in Google, which meant that they were extremely high traffic. This gave us the ability to test and learn at a very high pace. Since we knew our goal was to increase the number of pages per visit, we started by looking at the quantitative data for clues: “Where are people bouncing most?”, “Are there certain pages that have really good engagement?”, “Of the people who do stick around, where are they going next?”. Once we had the answers to those questions, the next step was to find out “Why?”, to find out why we used a combination of qualitative methods (User interviews, surveys, and usability testing). In cases where there was an obvious hypothesis, we often designed A/B tests in order to prove or disprove the theory. If the test was a success, the new design would be rolled out permanently, and if it was a failure we’d go back to the drawing board.

Results

  • Drastically increased pages per visit and reduced the bounce rate of Q&A pages

  • Improved engagement on Q&A pages lead to a huge increase in ad revenue

  • Integrated a machine learning based system to recommend more relevant content in smarter ways

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