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Understanding the Full User Journey with T-Mobile

T-Mobile's Andrea Lindeman walks us through her team's approach to longitudinal qual on agile timelines. 


At a company like T-Mobile, mobile research is a necessity, and longitudinal, contextual research is often needed. And executing mobile, longitudinal, in-context research can be a resource drain. From Andrea Lindeman, Principal User Experience Researcher:

“Since we've discovered dscout, we’ve been able to reach a larger number of participants and get more in-context mobile data—and we still get that data super quick. We can also reach out to the same participants over time and follow up post-study as needed. That’s been really valuable for us; ‘how much data can we get before a design comes out’ is a measure of success.”

Case 1: Out of the app and in context

When the team launched T-Mobile Tuesdays (their rewards program) they had a lot of behavioral analytics data within the associated app. But once people save offers and go to redeem them—they’re out of the application. The researchers lose track of what they're doing, what happens to them, and what their experience is.

“dscout allowed us to really effectively track where our users go and helped us to better understand their experience outside the app. They're able to record their screen and upload what they do—versus being constrained to a specific prototype or application—which was so powerful for us. We could also capture users when redeeming offers in a physical retail store to understand the in-store experience as well.


It was the first full picture that we had of customers redeeming various offers. And naturally, we found the experience wasn’t always delightful. So we were able to then go back to our partners and make some changes on our end as well.”

Case 2: More effective beta bug zapping

While the T-Mobile app was in its beta period—before a major redesign— the team did a dscout study to test it. Participants signed up to interact in the beta over the course of four weeks. They asked them to do some specific tasks, but also asked them to, whenever they went into the app, record their natural usage.

“If they were going in to check their data allowance, or pay their bill or what not, we asked them to upload those moments. In this way, we could capture key interactions with the app in users’ own contexts and timing, resulting in much richer and true-to-life insights than we get in the lab.


Anytime a user submitted a video with a serious issue, our product team could watch the videos back and replicate how the user encountered the problem. We resolved countless issues that way, in real time, before the new app was launched.”

The Impact

Before dscout

  • Stakeholders are too busy to engage with lab sessions (and are skeptical of small-sample results)
  • Difficult to test in-app and multi-channel experiences in context
  • Unable to follow up or engage with participants after a study is complete

After dscout

  • Stakeholders can watch short videos with visceral feedback and begin to implement findings immediately
  • More easily test across channels to more fully understand the whole customer journey (e.g., website or app to store)
  • Can source hyper-specific recruits within days and follow up with participants as needed

See how dscout scales insights in tech. Stream a demo on-demand.

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