I am a mixed-method researcher who uses data-driven insights to improve user experiences and help businesses grow.

Places I've worked @ Meta (Reality Lab, Commerce Platform), Glints Vietnam, University of Washington


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Boosting buyer trust with clear pricing

2 minutes to read · 249 words
tl;dr: A series of unmoderated design tests that aimed to drive buyer trust by improving how pricing and promotions are displayed throughout the shopping journey.

Methods: Literature Review, Competitive Analysis, Unmoderated Design Testing

Timeline: January 2023 - April 2023

The What

  • A series of unmoderated design tests to assess new concepts aimed at enhancing the visibility and understanding of pricing.

The Why

  • The team sought to identify which design variations significantly increase the completion rate of user shopping journeys on our platform.

The Who

  • Collaborated with another UX Researcher from a different team.
  • Stakeholders included Product Designers, Product Managers from three different teams to address this issue.

The How

Part one: Background research

  • Established the problem space through literature review and competitive analysis.

Part two: Design testing

  • Worked closely with Product Designers to refine and iterate on new design solutions, actively providing feedback and insights to enhance the final outcomes.
  • Collaborated with a fellow UX Researcher to develop and finalize a research plan, with my specific responsibility being the creation of the survey questionnaire for concept testing.
  • Conducted concept tests using UserZoom, featuring images from current designs and two new proposals. Three tests ran simultaneously with participants randomly assigned to each, allowing us to evaluate the designs effectively.

The Impact

  • Recommended design iterations and which concepts to advance to A/B testing, based on statistical analysis of over 380 responses.
  • Enhanced clarity and user experience, boosting Return-on-Ads-Spending (ROAS)[1] by 0.07% and achieving a 0.35% increase during the holiday season.


Note

[1]: Return-on-Ad-Spending (ROAS) measures the revenue generated for every dollar spent on advertising, indicating the effectiveness of specific marketing campaigns (source).