Mobile Conversion Architecture
Small UX decisions can create outsized business impact on mobile. This case study shows how research-informed design, competitive benchmarking, and intentional deviation from default frameworks were used to optimize a revenue-critical mobile journey. The result is a conversion-focused experience built for trust, accessibility, and measurable performance.
Explore Key UX & Conversion Drivers
What improved
Digital quote journey on mobile, treated like a product.
The personal auto insurance direct Quote Form is a high-intent moment. A customer is not browsing. They are deciding. This work focused on reducing friction while reinforcing clarity, trust, and support at every step.
What I did
Key UX & Conversion Drivers
Collaborate
This Case Study Highlights the work, not the company or client
In regulated environments, care was taken to focus on decisions, patterns, and outcomes. Full, unredacted flows and real product samples are available to walk through live.
Features at a Glance
Auto-save
Resume later without re-entry. Great for interruptions and flaky connectivity.
SMS nudges
Gentle re-engagement for abandoned quotes. High intent, low pressure.
Voice input
Accessibility plus multitasking support. Improves ease on mobile.
Auto-save
Resume later without re-entry. Great for interruptions and flaky connectivity.
Drop-off visibility
See exactly where users exit the form. Enables targeted UX fixes.
Device-level insight
Separates mobile and desktop behavior so optimization reflects real patterns.
Trust-first CTAs
CTA color and language tuned for confidence in high-intent moments.
UX–revenue alignment
Connects form completion to downstream conversions grounded in revenue outcomes.
Where revenue is won or lost
Designing the Space Between
Demand and Conversion
Sales creates demand. Engineering delivers capability. UX determines whether people can confidently act on intent.
Let's Talk- Increased mobile form completion by reducing mid-flow abandonment.
- Increased mobile form completion by reducing mid-flow abandonment.
- Reduced silent revenue loss caused by default framework behaviors.
- Strengthened trust signals at high-intent moments.
- Lowered error rates through clearer decision states.
- Improved downstream agent conversion.
- Expanded accessibility.
- Enabled precise drop-off visibility.
