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Life Insurance Price Widget
Driving acquisition funnel growth with targeted behavioral insights
Proactively spotting growth opportunities
First, some context: Policygenius is a NYC-based insurance marketplace with a mission to help people get the financial protection they need and have them feel good about it.
Most of my work as Lead Product Designer on the Life Insurance Growth team focused on boosting conversion through the product funnel — a series of health and lifestyle questions that determined what products customers were eligible for, and their premiums.
But this case study unfolded differently. A colleague on the Partnerships team mentioned that one of our acquisition partners was seeing low engagement with a third-party widget embedded in their content. The widget was intended to get customers comfortable with life insurance pricing, in order to drive them to a third-party marketplace to compare and buy. But customers weren't clicking through.
We thought if we went to our partner with a more compelling design, we could convince them to replace their current widget with ours — a win-win for them and for us. Internally, we got leadership’s blessing to pitch our idea.
The full business context of this case study is confidential. Please get in touch to discuss further!
Existing third-party widget
…with poor click-through rate, hosted on a partner site.
A versatile widget for any brand, on any screen
With the goals of:
Easily plugging into a wide range of partnership placements and brandings, and
Increasing engagement and click-through conversion to our funnel
…I started wireframing approaches, exploring problems like:
Question framing
Question sequence and grouping
Size and layout (in various contexts)
Framing of the price estimate
And later, form design and branding
Initial wireframe explorations (layout & content)
I landed on two layouts: a horizontally-oriented version for more spacious placements on large screens, and a vertically-oriented version for mobile, tablet, or the right-rail of a larger page.
I explored the collection of additional data points — like coverage amount, and a customer's best-guess of their own health class — in order to provide a more precise life insurance quote. With design team feedback, I iterated on aspects of the design:
Turbocharging conversion via customer insights
I knew from previous research that customers want to make sure life insurance fits their budget before committing to the full quoting and application process.
Further, they typically have no idea what determines their life insurance pricing (answer: a carrier's risk assessment of their health profile). That uncertainty often discouraged them from starting the process.
I had a lightbulb moment:
Research-backed hypothesis 💡
If we show a range of prices framed in terms of health class, we can educate customers about how life insurance pricing works — building trust in Policygenius, and motivating them to continue to a full quote.
Research insight-driven design iteration
Vertical orientation for mobile, tablet, or in a right-rail on larger screens.
The outcome? Major traffic & revenue growth, and an expanded roster of partners
We pitched the concept to our partner, and they loved it. With their blessing, we started building the widget in our code base to be hosted on partner content.
Because we designed and built the widget to be so flexible, it was easy to plug-and-play in various contexts and therefore easy to pitch to additional partners. Our partnership roster expanded rapidly — driving traffic growth to our funnel and resulting in major revenue growth.
31%
Increase in click-through conversion compared to previous widget
20%
Policygenius life insurance applications that start with the widget today (net new traffic)
9%
Increase in total company revenue attributable to widget
Because we designed and built the price widget to be so flexible, it was easy to plug-and-play in various contexts and therefore easy to pitch to additional partners. In addition to placements in Policygenius content, our partnership roster expanded rapidly.
Price estimates update in real-time based on customer inputs.