Sprint 4: Conducting interviews

A step forward to unearth users’ needs.

Sprint 4, Week 1 | Interview — Round 1

During sprint 3, we recruited 6 participants using a detailed screening questionnaire deployed through Qualtrics. Each participant identified having previous experience purchasing an insurance policy, and for additional diversity, participants were chosen across different levels of tech literacy. We planned to conduct hour-long interviews with every participant.

Interview schedule

Interview Structure

The team began conducting interviews with participants using the following interview techniques to better explore the user experience: semi-structured, directed storytelling, and think aloud. These interview methods were woven throughout the interview guide that the interviewers used during each session.


Over the course of the first six interviews, the team started to identify inconsistencies between screener answers and interviewee answers during each session. With further investigation, the team found suspicious submissions that used false identities/impersonations (e.g. using fake names, refusing to show their faces, etc) to pass the screener and receive the compensation from interviews. These interviews made contradictory statements during the interviews leading to some interviews being cut short.


Our team decided to reinforce our screening. We made 3 changes to our recruiting process:

  1. Redeployed the screener. The old screener link had pipeline of suspicious interviewee submissions and we had to cut the flow.
  2. Removed the mention of compensation. The $30 Amazon gift card that previously incentivized candidates who weren’t eligible is no longer mentioned.
  3. Reaffirmed candidates’ answers before the interviews. To avoid participants with inconsistent backgrounds and history, we re-presented questions from the screener to the interviewee to check if their current answers matched their previously given answers.

Sprint 4, Week 2 | Interview — Round 2

As a result of the new recruitment process, we were able to recruit 10 authentic interviewees. From 10, 60 minute intensive interviews, we discovered that people have different perceptions and definitions on insurance and this is reflected in how they research and purchase insurance policies.

Think Aloud session with an interviewee

Synthesizing through modeling

To expedite the generation of research insights, we began synthesizing the findings concurrently with interviews. After each interview, the 2 interviewers completed a wrap-up meeting to share their learnings, high-level takeaways and noteworthy findings. From the discussions, the team began creating new models to communicate these findings in more digestible manners.

Modeling users: Personas

The team reframed each interviewee into a persona. The persona framework captures the interviewees’ demographics, highlighted quotes, empathy map, and user journey. By synthesizing this information for each participant, we were able to grasp what each individual values the most, how they prefer to purchase and maintain insurance and how they compare insurance policies.


Modeling the service: Service blueprints

To understand how the user experience engages with the service design, we created a service blueprint of the current insurance flow. The blueprint covers the user journey from discovering the need for insurance to purchasing and owning the insurance. For each stage of the journey, we identified the touch points that users interact with, both the front and backstage staff that operate the service, and additional support staff and processes. Since the blueprint was built on the data collected from user/stakeholder interviews, it helped us to understand the current model of service components from the users’ perspective.

Service blueprint

What’s next?

For our next sprint, we plan to create an ideal future state model of acquiring insurance. This will not only help us to set the direction of our experience, but also spur us to come up with interesting ideas to reach the goal. Also, we will test our hypothesis with prototypes. Lots of things have been done, but we have a lot more to do.



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