Understanding
product users

When I joined the analytics product team at Acoustic,
the designers and content writers had many questions about
who they were designing and writing for...

The Research Need + The Challenge

Needed to understand: Who was using our product, what goals they were trying to accomplish, how they were using our product, and challenges they faced.

Coming into a team that had lots of research demands and work in-flight, I needed to adapt my approach to efficiently deliver on these questions for a product & engineering team that was already in the build phase.

The Approach

Mixed-methods: Interviews, survey & usability testing add-ons, web analytics & data science collaboration.

By gathering most of the data as part of my onboarding and other research projects, I was able to deliver value sooner while also delivering on my other projects:

 

Research Outcomes

Delivered data-driven user profiles & use cases that helped the team understand our users at a basic level.

This research uncovered that we had more Marketing users than the team had previously assumed, which contributed to conversations for integrating with other products in our platform.

Some of the other impacts stemming from this were:

  • Content writers were able to add user-based use cases, framings, & examples into help articles,  grounding the content in user-centered information.
  • More product focus was directed towards the non-technical users we had, who were struggling.
  • Designers & UX Researchers were able to include more targeted and representative participants for future UX Research, ensuring we were understanding the correct users' needs and if they were able to easily use future features & designs.

In the end, the team was thrilled with my work, and one product manager even said I helped him get over his "persona baggage" from a previous company.

More details

Key insights from this research

We learned...

  • Our product was used by a broad range of users! Based on this research, we formed or updated 3 primary and 7 secondary personas.

    • We confirmed the types of users our internal experts talked about, and also expanded on the list. Our experts said we didn't have Marketing users, but usage data showed that we did. This influenced a later decision to cross-sell / integrate our analytics customers & marketing-tool customers!

  • Some roles/functions overlapped when a team was smaller.

  • Some team compositions were correlated with a company succeeding with our tool versus struggling with it. This influenced a later research project & redesign of the setup process for the product!

  • Which roles tended to use which parts of our products, and what their goals & struggles were

 

Excerpts of analysis and reporting documents from this project.

Research lessons learned

  • The value of mixed methods research: Combining rich, human details from interviews & observations with bigger data from usage analytics. This gave us data to answer questions about user behaviors, goals, and struggles, and allowed us to connect the dots between these different data types.
  • Helped me find creative, adaptable approaches to delivering value efficiently to my team.

If I were to do this again, I would also learn data scraping (or partner with a team member who could do that). This could make future, similar projects more efficient and less manual.