Shreya Jaiswal

I'm Shreya — a Lead Mixed Methods UX Researcher.

I’m an experienced mixed methods UX researcher with a Master’s in Behavioral Science. Over the last 6+ years, I’ve honed my skills at J.P. Morgan Chase, Google, Peloton, Unity, and multiple startups.

SJ

Shreya Jaiswal

📍 New York City

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Published: March 14, 2025
⤷ Last updated October 30th, 2025

Feature Prioritization with MaxDiff

Challenge: With limited engineering bandwidth for the year, our team needed to identify which features delivered the most user value.

Approach: I designed a quantitative MaxDiff study to measure feature importance, followed by a conjoint where participants could choose “no preference” to validate differentiation strength.

Impact: The analysis produced a clear, data-driven prioritization model that guided roadmap decisions and aligned stakeholders on where to invest.




Note: I take company privacy seriously, contact me to go over redacted case studies.

Impact Measurement with Usability Benchmarking

Challenge: Redesigning a complex product without standard success metrics like conversion or revenue, with limited user data access.

Approach: Designed a mixed-methods usability benchmark, combining qualitative insights (user friction, mental models) with quantitative metrics (time on task, errors, SUS score).

Impact: Established a clear, measurable framework for product success and embedded a culture of data-driven decision-making.

250
Users Surveyed
5
Fewer Average Clicks
12%
User Satisfaction Increase
Note: I take company privacy seriously, contact me to go over redacted case studies.

Data-Backed Personas with User Segmentation

Challenge: Build personas that are data-backed with segmentation that is also meaningful; the difference in behaviors, actions, and needs should lead to an actionable improvement for our team.

Approach: Conducted a large-scale quantitative survey, with profiling questions and respective behavioral questions to find segments that are meaningful for product improvements.

Impact: The discovered breakdown of segments led to a varying design for each group - resulting in higher than average increases in satisfaction.

380
Users Surveyed
5
User Segments
13
Redundant Personas Removed
Note: I take company privacy seriously, contact me to go over redacted case studies.