Amazon Quest
Transforming passive customers into active buyers.
Product Designer — Sebastien Chery
Overview
After my internship at Amazon, I was invited to join a Kindle team at Amazon Japan as a product designer.
My role in this project was to own the UX strategy from end-to-end. I led stakeholder alignment across global and local teams, conducted cultural research, and produced wireframes with engineer-ready specs.
The Problem
How might we increase digital content purchases among passive Japanese Kindle users?
Research showed our target customers had purchased only once in the last three months, and 1.5M other customers had not purchased at all after activating their accounts.
Standard re-engagement tactics were ineffective due to Japanese user preferences.
The Challenge
How might we then motivate low-intent Japanese customers in a way that felt native to Japanese re-engagement tactics?
Team
Cross-functional collaboration with engineering, global teams, and product managers.
Deliverable — Complete end-to-end widget for A/B testing.
KPIs — Activation rate, completion rate, and drop-off analysis.
Design Process
Discovery — I researched mechanics and loyalty programs to identify progress and reward systems aligned with Japanese preferences. The research showed that Japanese loyalty preferences favor incremental progress and “almost there” momentum drives completion more than reward size.
I then facilitated an early stakeholder session to align on business goals, technical constraints, requirements, and chosen mechanics.
The discovery and alignment session produced two insights that guided the design:
• Segment cohorts based on purchase frequency data.
• Drive purchases through progressive engagement steps
• Drive purchases through progressive engagement steps
Ideation — I facilitated a stakeholder session to allow engineering and PM stakeholders to react early to two design concepts:
•Stacking — A collection mechanic where diagonal book cards accumulate, encouraging strategic behavior.
•Tracking — A linear progress bar with sequential task cards.
•Stacking — A collection mechanic where diagonal book cards accumulate, encouraging strategic behavior.
•Tracking — A linear progress bar with sequential task cards.
The alignment session concluded with tracking as the chosen concept. The rationale was that linear progress is more technically feasible, and provides incremental feedback.
Development — I facilitated a stakeholder session to secure placement on Amazon’s global 'Thank You Page.' Placement on Amazon's global 'Thank You Page' required approval from global stakeholders who had concerns about targeting accuracy and performance impact of the tracking mechanic.
I created a user flow mapping the technical and business requirements of the TYP, showing how the quest widget would appear only for eligible cohorts.
I invited engineers from my team to explain how the tracking mechanic integrated with Amazon's campaign engine, and what the performance would look like with it on the TYP.
Wireframe — The wireframe mapped cohort eligibility logic, progress states, and reward completion for a relevant cohort. It facilitated technical and scope questions early from both the global and manga team stakeholders to reduce any rework.
Engineering Handoff — I structured all components in Figma Dev Mode using Amazon's AUI component library alongside custom elements. The handoff included edge cases and annotations for both the global team and the manga team.
Results
The campaign launched in late March 2024 and ran for two weeks.
Engaged Users Performance — Among engaged users who completed the quest, purchase behavior increased during the campaign period with a +2279% increase for Cohort 1 and a +662% for Cohort 2.
User Journey Funnel — Strong initial engagement with 91% of visitors enrolling, but only 16% completed the quest.
What Worked
The cohort segmentation strategy proved effective. By using purchase frequency data, meaningful lift was driven in both groups.
Structuring stakeholder alignment around a user flow secured global placement.
Having multiple alignment sessions that answered engineering and product questions early reduced rework.
What I'd Do Differently
I would add user research as part of the backing data for cohort segmentation.
User interviews at the cohort segmentation stage could have addressed the mid-journey retention that drove the 16% completion rate.