Customizing the insurance quoting experience based on personality and context.
Challenge
Our insurance company stakeholders wanted to optimize shopping for car insurance online by providing unique experiences for different user archetypes.
We set out to define meaningful archetypes, and to design an ideal experience for each archetype. Business stakeholders requested that we have something ready for development within a few months.
Team & My Role
I led this UX initiative, collaborating with business stakeholders and technical implementation teams. I managed the project and an interdisciplinary team of designers, content writers, and data scientists. I was also the sole researcher on this project and planned, conducted, and synthesized all research activities.
Process
Because of the quick turnaround time for this project, we combined discovery and design feedback into one moderated study with 13 participants.
Recruitment & Quant
We recruited participants through a descriptive dscout survey; almost 200 respondents provided short video selfies and answered questions aimed at identifying their affinity towards several hypothesized prescriptive variables (such as price consciousness and passive/active loyalty). I did a quick analysis of their responses, levering the screener as a small quant survey, and started noticing a correlation with prescriptive variables and contexts of use.
In-depth Interviews & Concept Testing
The first half of each moderated session was an in-depth interview where we dove deep into the story of their recent online quoting experiences, to understand how they approached insurance quoting, and their needs, expectations, motivations, and use-case scenarios.
The second half of each session involved walking through three prototypes with a task-based scenario. This was a between-subjects Rapid Iterative Testing study, and provided us with insight into which elements of which prototypes participants preferred.
Synthesis
Through the research I identified a number of prescriptive variables across participants, encompassing different mental models, behaviors, personalities, needs, motivations, and contexts. I mapped participants on these spectras looking for patterns and themes, and compared them with differences in prototyped concept feedback. Through this process archetypes and concept feedback emerged.
Outcomes
We identified 3 meaningful archetypes through this research; the Newbie, the Quick Shopper, and the Tinkerer. Some aspects of the concept feedback was unique for each archetype, allowing us to personalize the experience for each archetype. For example, the Newbies were overwhelmed when provided with too much information at once, conversely, the Tinker and Quick Shopper wanted to have fewer comprehensive steps.
There were many more similarities in concept feedback than differences between archetypes, and from our initial quant we hypothesize that a majority of respondents fall into the Quick Shopper archetype. We decided to proceed with one design optimized for Quick Shoppers, and including features that were important to Tinkers and Newbies. In the future we're considering exploring using customer data to provide a customized experience for Newbies.
This research provided several insights into the needs and motivations of all archetypes, including price consciousness, a need to build trust, and a desire to learn without being overwhelmed or confused. We also discovered and implemented some usability feedback. The findings from this study are being implemented in higher fidelity designs for usability testing ahead of development.