UX Personas: Digital Car Insurance 👋

Research Persona for digital insurance

How might we… Establish foundational understanding of our customers to better serve their specific needs, goals, and motivations through our digital product experiences.

Generating UX Personas for Digital Car Insurance

Emphasizing: Generative research planning, data science, user & SME interviews, and standout deliverables.

Having a clear idea of our customers is vital to the business and design decisions. It delineates what we should do for each customer segment, as much as what we should NOT do for each segment. Creating great user experiences becomes easier when there is common understanding of customer needs, behaviors, and expectations.

In 2019, our UX Research team partnered with cross-functional teams, such as Data Analytics, Marketing, Design, Product, and Operations to generate our Esurance UX Personas. The goal was to define major needs, pain points, and opportunities across the purchasing, managing, and claims experience for our major customer segments.



  • Developed proprietary data analytics model
  • Informed new product feature development for acquisition
  • Built comprehensive log of UX needs across touch points and personas
  • Increased empathy and statistical understanding of major user groups
  • Improved relationships between Product, Research, Design, and Operations



First, we partnered with the data science team to understand the book of business on macro scale. We stratified our customers along a variety of data axes (plural of axis) to pull apart our customers in different ways. This helped us examine our population from multiple angles to get a sense for what stood out. It also provided the UX design and research team with invaluable understanding of our customers, so that we could wrap our minds around the broader population.

Second, we conducted SME interviews to understand what we already knew about our different customer types. Qualitative digging with thought-leader teams who are versed in the detailed aspects of our different customers helped round out our 30,000 foot view. Virtual Assistant (VA) chat data, website behaviors, NPS data, and marketing segmentation data were other examples of rich inputs to our process. Often, connecting internal data and teams is as important as much as generating additional outside user-data.

Third, we conducted in-depth qualitative interviews with our digital chat agents, phone agents, and customers. The operations experts have first-hand knowledge of the questions, needs, and issues that our different customers express on a daily basis. They’re able to summarize and create early themes of our customer types. Anecdotes, quotes, and example dialogs provided more details and color to the early groupings. After conducting 30+ qualitative interviews 💭 with actual customers as well as claims, sales, and service agents, we had robust data set with which to work.

Lastly, we synthesized our insights into version 1.0 of UX Personas through working sessions, affinity mapping, and validation with prior teams. We have quickly established a foundational understanding of 3 actionable customers groups. Complete with individual journeys, spectrums of characteristics, statistical data, detailed need statements, and opportunity areas. Through further communication at various levels in the organization, we’re strengthening the empathy and knowledge of our customers with those who create/deliver services to them.

Next steps include additional field research with targeted customers from each segment to dive deeper into visceral stand-alone deliverables:

  • Short videos characterizing segments clearly
  • Feedback on early-stage prototypes
  • Generation of long-term ideas
  • High-fidelity 2.0 UX Personas
  • Design sprints focused on high priority areas
  • Evolution of our backlog of UX user needs


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