Checkout Flow Optimization

Context & Problem

Users were abandoning checkout at a 67% rate—more than twice the industry average. The payment flow had accumulated 8 steps over 5 years as different teams added features without considering the overall experience. Mobile users faced an entirely broken flow with form validation errors that prevented completion.

The business impact was significant: we were losing an estimated $2.3M in annual revenue. Customer support was overwhelmed with payment-related tickets. The engineering team was hesitant to touch the code due to its complexity and lack of test coverage.

My Role & Approach

I owned the end-to-end checkout experience, reporting directly to the VP of Product. My first priority was understanding the full scope of the problem before proposing solutions.

Discovery process:

• Ran 20 user interviews (mix of successful completers and abandoners)
• Analyzed 50K session recordings in FullStory
• Deep-dived into Amplitude data to map the exact drop-off points
• Shadowed customer support for a week to understand pain points
• Mapped every API call and dependency in the current flow

Key findings:

• 40% of users abandoned due to unexpected shipping costs appearing late
• 25% hit validation errors that weren’t clearly explained
• Mobile keyboard covered critical form fields
• Guest checkout was buried; users thought they had to create accounts
• Payment processor integration had a 3-second lag that felt broken

Process & Decisions

I evaluated three approaches:

1. Complete rebuild (3 months dev time)

   • Pros: Clean slate, best UX, easier to maintain
   • Cons: High risk, blocks other features, big bang launch

2. Incremental refactor (6 months, ongoing)

   • Pros: Lower risk, continuous improvement
   • Cons: Slow ROI, compounding technical debt

3. Parallel new flow with gradual rollout (1 month + testing)

   • Pros: Fast time to value, can A/B test, easy rollback
   • Cons: Temporarily maintaining two codepaths

I chose option 3 because we needed quick wins and couldn’t freeze feature development for months. The engineering team was skeptical of the added complexity, so I committed to owning the rollout plan and monitoring closely.

Technical approach

Worked with the lead engineer to design the architecture:

• Built new checkout as a separate React component tree
• Shared validation logic but isolated rendering
• Feature-flagged rollout (5% → 25% → 50% → 100% over 2 weeks)
• Extensive logging to catch edge cases early

UX decisions

Simplified to 3 steps:

1. Contact info (with prominent guest checkout)
2. Shipping (with live rate calculation upfront)
3. Payment (with clear error messaging and retry logic)

Key improvements:

• Guest checkout as default (account creation post-purchase)
• All costs visible from step 1
• Mobile-optimized keyboard handling
• Inline validation with helpful error messages
• Loading states for all async operations
• One-click Apple Pay and Google Pay integration

Trade-offs:

• Removed “save for later” feature (only 2% usage, high complexity)
• Postponed international address validation (would add 2 weeks)
• Kept existing payment gateway despite exploring Stripe (migration risk too high)

Outcome & Impact

Business metrics:

• Checkout completion increased from 33% to 58% (+25 percentage points)
• Added $2.3M in recovered ARR
• Mobile conversion caught up to desktop (previously 15pp behind)
• Average time-to-purchase decreased from 4.2min to 2.1min

User feedback:

• NPS for checkout experience increased from 12 to 67
• Support tickets for payment issues dropped 40%
• Multiple users specifically mentioned the “finally works on mobile” in feedback

Technical outcomes:

• Test coverage increased from 0% to 85%
• Payment provider integration now takes 2 days vs 2 weeks
• P95 checkout latency improved from 8.2s to 1.4s

Lessons Learned

What worked:

• Parallel implementation de-risked the project significantly
• Heavy instrumentation caught 3 critical bugs before they affected many users
• Guest checkout default was controversial internally but absolutely the right call

What I’d do differently:

• Should have negotiated for a dedicated QA engineer—caught several mobile bugs in production
• International address validation turned out to be needed sooner than expected
• Feature flag cleanup took longer than planned; should have set sunset dates upfront

Broader takeaways:

• Sometimes the “right” technical approach (complete rebuild) isn’t the right business approach
• Friction in checkout compounds exponentially; small improvements stack
• Mobile-first isn’t just a buzzword—50% of our traffic came from mobile but previous PM never tested on device