Optimizing conversion through A/B testing on a B2C insurance media page
Led UX-driven CRO experiments on a paid media landing page, increasing quote conversions by +18%.
Role:
Senior UX Designer
Goal:
Increase quote generation (conversion) from traffic driven by paid ads.
Team:
Image of Jewelers Mutual media page. One of several pages A/B tested to increase conversions. Link to Page
Overview
What I Did
Defined test hypotheses from analytics patterns and interview insights
Created wireframes for variants and mapped page-level content hierarchyMonitored test performance and shared insights with stakeholders.
Partnered with engineering to launch tests in VWO across targeted cohorts
Tools I used
Usertesting.com: Moderated interviews to understand expectations and friction
VWO: A/B testing, heat maps, scroll maps, session recordings
Mixpanel: Behavioral analytics to identify drop-off points and CTA engagement
Figma: Rapid iteration of layouts and copy variants
Challenge
Paid media drove strong ad engagement, but visitors landing on the insurance page didn’t progress to the primary CTA. Analytics (Mixpanel, VWO) showed attention drop-off near the call-to-action and trust signals buried below the fold. The challenge: reduce friction and align content with what visitors valued most at this moment.
Visitors were engaging with the ad but hesitated at the landing page—uncertain about cost, coverage, and effort required. The CTA ‘Get a Quote’ signaled a long, tedious process, increasing abandonment.
Image of the quote and application funnel for the insurance product. These were our milestone goals that we tracked as part of the end to end conversion funnel.
Solution
I led a series of UX-driven A/B tests focused on clarity, trust, and information hierarchy. We iterated CTA copy, elevated trust-building elements, and reorganized content to match visitor priorities at this stage. The winning variant—‘Check Your Rate’—increased quote conversions by +18%, aligning with annual new-business objectives.
My Process
I began with analytics to pinpoint where visitors hesitated, then used moderated interviews to uncover why. Insights shaped hypotheses and variants: clarify effort, surface trust signals earlier, and make cost/coverage obvious above the fold. Each test focused on a single variable to isolate impact, with cohorts matched to paid media segments
Research and Discovery
I conducted ten 30-minute moderated interviews to learn what visitors needed to feel confident requesting a quote. Three insights stood out:
Cost clarity: Visitors wanted a quick way to see estimated pricing
Coverage basics: Clear, simple coverage explanations mattered
Social proof: Reviews and trust badges increased confidence
We also learned ‘Get a Quote’ suggested a long process. In reality, only jewelry type, value, and zip code were needed to get a preliminary rate—creating a mismatch between perception and effort.
Hypothesis and test plan
Based on insights, I defined the core hypothesis:
Hypothesis: Reframing the CTA to emphasize speed and rate transparency (‘Check Your Rate’) will increase engagement and quote completions.
Primary metric: Quote completions
Secondary metrics: CTA clicks, scroll depth, time to first interaction
Variants tested: CTA copy; repositioning trust badges/reviews; simplifying above-the-fold content; reorganized coverage/cost blocks
Results
+18% increase in quote conversions!
The winning CTA variant (‘Check Your Rate’) increased quote conversions by +18%. Engagement improved where pricing transparency and trust signals appeared earlier in the journey. Visitors progressed more confidently once effort felt minimal and value was clear.
Slide from presentation to stakeholders on results of the test.
Lesson’s learned
Match copy to the visitor’s top question at that stage (cost, coverage, trust)
Reduce perceived effort to clarify how quick the first step is—set expectations
Align cross-functionally: Marketing, UX, and Engineering alignment accelerates learning and impact