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Trust signal check
Amazon UX case study
Amazon Transparency
Amazon Transparency helps brands reduce counterfeit risk, build customer trust, and create a more verifiable product experience across the purchase and post-purchase journey.
Featured case study
Product authenticity signals across shopping and post-purchase
flows.
6%
Decrease in customer returns for enrolled products.
2%
Increase in purchase rates through stronger trust signals.
2x
Expected growth in Transparency code scans.
350+
UserTesting sessions across the US, UK, and Germany.
Role + ownership
Sole UX designer across a complex authentication ecosystem.
Transparency portal
Designed the web experience brands used to onboard products,
order and print Transparency codes, access dashboards, and
manage operations.
Seller Central
Extended seller workflows with Transparency authentication
features that fit into existing Amazon selling patterns.
Fulfillment Centers
Designed authentication tools embedded in internal warehouse
systems where speed, clarity, and accuracy were essential.
Amazon.com + Amazon Lens
Integrated Transparency into customer touchpoints including
detail pages, trust messaging, and scan-based verification.
Problem
Low awareness and weak trust signals.
Transparency had a strong anti-counterfeiting promise, but that value was not obvious enough in the customer experience.
The challenge was to bring meaningful trust signals into high-visibility moments without adding friction or confusion. I helped define the language, flows, and visual treatments needed to make the program understandable, credible, and worth engaging with.
Research + discovery
From landscape analysis to customer validation.
Research clarified how trust should be introduced, explained, and reinforced over time.
Competitive analysis
Reviewed anti-counterfeiting and verification patterns to
understand trust-building language, iconography, and
call-to-action design.
Lean Canvas framing
Structured assumptions with Product to turn a broad
anti-counterfeiting initiative into testable design
decisions.
UserTesting validation
Ran 350+ unmoderated and 6 moderated sessions across the US,
UK, and DE to test comprehension, clarity, and the value of
Amazon Lens.
Artifact
Landscape + themes
A common pattern across the analysis was the use of familiar iconography and similar color palettes to build trust with users.
Artifact
Lean Canvas
Lean Canvas helped the team align around assumptions, opportunity framing, and testable design decisions.
Design process
Prototypes turned strategy into something teams could evaluate.
Customer flows
Created flows that introduced product authentication without
interrupting the shopping journey.
Content strategy
Refined language after learning that “Verify with
Transparency” was too vague without progressive explanation.
Amazon Lens
Explored scan-based verification experiences that helped
customers confirm authenticity when proof mattered most.
Prototype
Flow diagram
Mapping the flow helped clarify how customers moved from product discovery to verification.
Final screens
Customer-facing touchpoints
Final designs emphasized clearer explanations, accessibility, iconography, and alignment with Amazon design system branding.
Media + references
Research prototypes and artifacts
Validation + insights
The language had to earn trust before the feature could.
The strongest finding was that the initial message, “Verify with Transparency,” was too vague on its own.
Once participants saw progressive explanation and understood how the program could help them verify a product, sentiment improved significantly. That insight shaped the final content strategy and how the experience introduced value over time.
“The scanner is excellent for verification purposes and offers additional opportunities for future enhancements.”
“It’s compelling when there’s a problem, and I need proof to decide if I need to escalate the issue.”
Research tools
Research methods matched the question.
UserTesting.com
Moderated interviews, unmoderated surveys, prototype walkthroughs.
Moderated interviews, unmoderated surveys, prototype walkthroughs.
Qualtrics
Complex branching surveys and studies requiring statistical significance.
Complex branching surveys and studies requiring statistical significance.
Eye tracking
Used to compare stated preferences with actual behavior.
Used to compare stated preferences with actual behavior.
In-person sessions
One-on-one interviews and roundtable discussions.
One-on-one interviews and roundtable discussions.
Impact
Improved trust signals in moments that mattered.
Search, Detail, Progress Tracker, Amazon Lens, and content design improvements contributed to measurable gains for products enrolled in the Transparency program.
By making the program easier to understand and more credible in context, the experience helped strengthen trust signals and improve customer behavior in key moments of the journey.
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