Claire Ferrari, PhD
All work

03 · Verizon · 2026

Finding traps in a mobile checkout flow

I tested a reskinned mobile checkout with 27 assistive technology users, traced the barriers they hit to four root causes, and turned them into prioritized fixes for engineering.

Org and Year
Verizon, 2026
Role and Team
Senior IC, UX + Accessibility Research
Methods
Assistive technology usability, n=27
Partners
Wireless plan sales experience team, design leads and engineering
Flow diagram of the Next Gen Digital purchase journey tested in the study: 13 screenshots in three rows joined by arrows. It starts at Account Overview and moves through choosing an Unlimited plan, browsing smartphones, customizing an iPhone 17 Pro, picking an offer, getting a new number or bringing one, device protection, a rewards card prompt, accessories and the cart, ending at a Bill Pay Estimate. The first and last screens are labeled Existing Customer only.
The purchase flow participants worked through, from Account Overview to Bill Pay Estimate. Open the full-size flow

Could people using assistive technology actually buy a phone in the reskinned mobile sales flow?

Context

Verizon's Next Gen Digital mobile sales flow was being reskinned under the new Monarch brand. The study checked whether people using assistive technology could still complete a purchase.

Approach

I designed and ran this study on my own: an unmoderated test with 27 assistive technology users, 10 prospects and 17 existing customers, on desktop and mobile. They included 16 screen reader users, 5 switch and voice control users, and 6 low-vision magnification users, each working through purchase tasks.

Findings

Participants ran into four kinds of barriers:

  • Authentication and session handling
  • Keyboard focus management in dialogs
  • Form controls without accessible labels
  • Visual density beyond what participants could comfortably take in

I turned the findings into prioritized fixes for engineering and design, covering session persistence, focus management, programmatic labels and progressive disclosure for dense content.

What changed

Each fix was logged in Jira and prioritized with the wireless plan sales experience team, design leads and engineering, focused on the checkout steps where high-intent customers were dropping out.

27assistive technology users
3assistive technology groups: screen reader, switch and voice control, magnification
4root causes, each turned into a prioritized fix