shreya jaiswal

Research that lands before the roadmap moves on.

Shreya Jaiswal
Subtly placed copy of the Power Broker

Lead Mixed Methods Researcher

Led research at JPMorgan, Unity, Peloton, and Google through AnswerLab. đź“Ť New York

How I lead research

  • Start from the decision, not the method.
  • Match the method to the uncertainty.
  • Ground actionable insights in behavior.
  • Direction

    Turn vague asks into the right question

  • Influence

    Design studies around a decision

  • Integration

    Combine various sources of truth

  • Capability

    Build new methods, processes and AI workflows so the org learns faster

Rapid research is the future

Research must keep pace with AI that lets teams build in days.

  1. MondayFrame the decision

    Align stakeholders on what’s being decided and what evidence would change it. Pull existing data first, so we only study what we don’t already know.

  2. TuesdayGo to the source

    Sessions with the right users. Product, design and engineering watch live, so insight lands without a handoff.

  3. WednesdayPressure-test early

    Emerging patterns are shared the same day, so stakeholders can challenge them while there’s still time to adjust.

  4. ThursdayTriangulate

    Check what we heard against behavioral and survey data, to separate what’s real from what’s loud.

  5. FridayRecommend

    A streamlined set of findings, a decision, how confident we are in it, and the risks. Not a bloated deck, no filler.

How I combine evidence

Quant tells you how many and how sure. Qual tells you why, and what it feels like. Now that AI makes doing both a matter of days, there's no justification for leaving a blind spot.

  • Quant then Qual

    Explanatory sequential

    Find it, then explain it

    The data shows where something is happening; talking to the people behind the numbers shows why.

    e.g. Funnel and cohort analysis isolate where and for whom a metric breaks; targeted interviews with that exact cohort explain the mechanism.

  • Qual then Quant

    Exploratory sequential

    Discover it, then size it

    Interviews surface what matters; a survey or experiment shows how much it matters, and to whom.

    e.g. Interviews generate hypotheses about churn drivers; a MaxDiff then sizes their relative importance across segments.

  • Quant + Qual, in parallel

    Convergent, or triangulation

    Check one against the other

    Both run in parallel and get compared. Where they disagree is often the most useful finding.

    e.g. A statistically powered survey and contextual interviews run in parallel; the gap between stated and observed behavior becomes the headline.

  • One inside the other

    Embedded

    Measure while you watch

    Numbers and observation are captured in the same session.

    e.g. Benchmarks capture task success, time on task and SUS alongside think-aloud, so every metric arrives with a reason attached.

  • Repeated cycles

    Multiphase, over time

    Track it, then dig in

    A recurring measure shows when something moves; a quick deep dive shows why.

    e.g. A quarterly tracker with significance testing separates real shifts from noise; each real shift triggers a rapid diagnostic study.

  • Selected work

Previews of recent case studies. I take company privacy seriously, so ask me for the full redacted versions.

  • Prioritization

    What to build first Feature prioritization with MaxDiff and conjoint

    Challenge
    With limited engineering bandwidth for the year, the team needed to know 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 test how strongly the features really differed.
    Impact
    A clear, data-driven prioritization model that guided roadmap decisions and aligned stakeholders on where to invest.
  • Benchmarking

    Success without a sales number Impact measurement with usability benchmarking

    Challenge
    Redesigning a complex product without standard success metrics like conversion or revenue, and with limited access to user data.
    Approach
    A mixed methods usability benchmark, combining qualitative insight (friction, mental models) with quantitative metrics (time on task, errors, SUS score).
    Impact
    A clear, measurable framework for product success, and a culture of data-driven decisions on the team.
    • 250users surveyed
    • 5fewer clicks on average
    • 12%increase in satisfaction
  • Segmentation

    Personas you can act on Data-backed personas through user segmentation

    Challenge
    Build personas backed by data, with segments different enough in behavior and needs to point to real product improvements.
    Approach
    A large-scale survey pairing profiling questions with behavioral questions, analyzed to find segments that matter for the product.
    Impact
    Distinct designs for each segment, leading to higher than average increases in satisfaction.
    • 380users surveyed
    • 5user segments
    • 13redundant personas removed

About

In a past life, I studied primates (technically I still do).

I came to UX research from ten behavioral research labs, where I studied how hormones and cooperation shape each other. That's where my rigor comes from: training in experimental design, careful measurement, and a healthy dose of suspicion. My behavioral science background (UC Davis, University of Chicago) still informs how I understand the way people interact with interfaces.

I'm an advocate for UX research that's far more grounded in how people actually behave, and that looks for durable principles the way academic research does.

I trained in rapid research consulting for Google through AnswerLab, then built a program of my own at JPMorgan and piloted an agentic AI workflow connecting research to content design. I'm at my best when the problem is tangled, the timeline is short, and nobody agrees yet on the question. I untangle it and turn it into a clear call a team can act on. The strategy changes every time. The standard of evidence doesn't.

Away from the desk

An eclectic, ever-changing set of interests that keeps my mind sharp and full of wonder.

  • [Photo: a dish or an old cookbook][Describe your food history photo]
    Food

    Food history Tracing the trade routes behind a dish, poring over the ancient texts that recorded it, and then trying it myself

  • [Photo: you at the harp]Shreya playing the harp
    Music

    Pulling strings A magical, forgiving instrument you can learn as an adult without upsetting your neighbors

  • [Photo: a bird you spotted][Name the bird in your photo]
    Birding

    Field notes Birding, growing my life list, and getting vicariously excited about a bird I'd never heard of, just because everyone else is

A reminder to breathe, find a bird, and log it in your PokĂ©dex.

Let's talk

I'm looking for my next research leadership role. Bring me the question you can't answer yet.

LinkedIn Resume (PDF)