Company Context

Affirm is a leading buy now, pay later platform embedded across merchant checkout flows and its consumer app. The Product Growth team is evaluating improvements to the Affirm checkout experience, where conversion, trust, and repeat usage directly affect GMV and revenue.

Problem

Affirm recently launched changes to the prequalification and checkout flow on a subset of merchant partners. Quantitative data shows a positive impact: checkout completion increased from 42% to 45% and repeat usage among approved users rose by 3 percentage points over four weeks. However, qualitative feedback from user interviews, support tickets, and app store reviews is negative. Users say the flow feels "less transparent," "more stressful," and "harder to understand," especially around APR, payment schedule, and why they were or were not approved.

The Growth lead asks you to determine how to respond. The core challenge is not just to explain the mismatch, but to decide whether Affirm should scale, modify, or roll back the experience.

Deliverables

1. Explain how you would diagnose the contradiction between product data and user feedback.
2. Identify which user segments and jobs-to-be-done you would prioritize in your analysis.
3. Recommend a product decision for the Affirm checkout flow: scale, iterate, segment, or roll back.
4. Define the success criteria and guardrails you would use before making a broader launch decision.
5. Describe the key trade-offs you would make between short-term conversion gains and long-term user trust.

Constraints

• You have 6 weeks to make a launch recommendation.
• Engineering capacity is limited to one checkout engineer, one analyst, and shared design support.
• You cannot materially increase checkout latency or add a lengthy new disclosure flow.
• Any solution must remain compliant with lending disclosure requirements and preserve merchant conversion performance.