Liz Slavin

I turn messy questions into decisions.

I do the research behind product, pricing, and market decisions: what people value, what they will pay, where the opportunity is, and how sure we can be.

Product insights lead · MBA candidate at UC Davis · United States

Portrait of Liz Slavin

About me

I am a Product Insights Lead at VRChat. I usually get pulled in when the question is important, the data is incomplete, and the team still has to make a call. My job is to work out what we can learn, find a practical way to learn it, and make the result useful.

Quick facts

Current role
Product Insights Lead at VRChat
Focus
Market research, consumer insights, product strategy, pricing, and market intelligence
Education
MBA candidate at UC Davis; B.A. in Economics from CSUN
Languages
Russian (native)Ukrainian (intermediate)French (beginner)
Interests
ChessComic booksCookingLifelong learning

What I actually do

I start by figuring out what the team is really trying to decide. Sometimes the answer is a survey. Sometimes it is market research, a model built from imperfect data, or a closer look at what users are already doing. The method should fit the problem.

Market and consumer research

When the usual market reports are not enough, I piece together secondary research, search behavior, audience overlap, current-user data, surveys, and interviews to get to a useful answer.

Pricing and monetization

I use conjoint, including Hierarchical Bayes estimation, and willingness-to-pay research to understand which features matter, what people will pay for them, how products should be packaged, and where cannibalization may show up.

Product and user insights

I study how different groups of users experience a product, where their needs diverge, and what changes are most likely to improve the experience. I build Amplitude dashboards when teams need a recurring view of the findings.

Quantitative analysis

I use regression, factor and cluster analysis, significance testing, weighting, and financial models when they help answer the question. I also spend a lot of time checking whether the data can support the claim.

Explaining what the analysis means

Technical work can become useless very quickly if no one understands it. I write short memos, build research readouts, and explain the assumptions and tradeoffs in plain language.

Working across the company

My projects usually involve Product, Design, Data, Engineering, Finance, Business Development, Trust and Safety, IT, and leadership. Their questions make the research better and more useful.

Experience

I have worked in consumer technology, consulting, investing, gaming, and applied economics. The thread through all of it is pretty simple: start with a messy question and work out what the evidence can honestly tell us.

View resume

April 2025 - Present

Product Insights Lead

VRChat Inc.

Consumer technology · United States

A social platform centered on shared virtual experiences and user-created content.

  • Lead projects that help teams price new products, understand user sentiment, evaluate markets, and make product decisions.
  • Built pricing studies using choice-based conjoint and Hierarchical Bayes, then moved the work into packaging, market simulation, cannibalization, and revenue scenarios.
  • Run a recurring experience-quality study and built the analysis and reporting system behind it, including dashboards in Amplitude and Streamlit.
  • Explain the technical findings and make clear recommendations to product teams, executives, and the board.

September 2025 - Present

Graduate Teaching Assistant, Applied Statistics

University of California, Davis

Teaching and analytics · California

  • Hold weekly meetings with students and help them work through regression, advanced statistical methods, and the logic behind their analysis.
  • Created original video guides so students could revisit the hard parts on their own time.

June 2024 - August 2024

Market Research Consultant

Mobalytics

Gaming market research · Remote

  • Researched gaming audiences, demographics, motivations, platforms, spending, and genre trends for a gaming analytics platform.
  • Recommended an expansion into open-world role-playing games and translated the research into concrete audience and product considerations.

June 2023 - June 2024

Consultant

StoneTurn

Advisory · Los Angeles, California

  • Used operational, pricing, and competitive analysis to find potential cost savings for healthcare and pharmaceutical clients.
  • Analyzed more than 10,000 unstructured data points for a platform with more than 2 million users.
  • Explained the findings and recommendations to senior and C-suite audiences.

June 2022 - August 2022

Investment Research Analyst Intern

Anthos Capital

Investment research · Santa Monica, California

  • Studied engagement and monetization across the top 100 mobile games.
  • Built due-diligence presentations from company financials, market research, and secondary sources.

June 2020 - June 2022

Market Research Analyst / Economics Researcher

California State University, Northridge

Applied economics research · Northridge, California

  • Built 6 predictive models in Python to study consumer trends.
  • Worked with 19 organizations and brought more than 50 public-sector datasets together into 2 research plans.

Selected case studies

A few projects where the answer was not obvious at the start.

Pricing something that had never existed before

Read the case study

The product was new. There was no sales history and no obvious benchmark, but the team still needed to choose the features, packaging, and price.

Method: Choice-based conjoint, Hierarchical Bayes, logit modeling, willingness to pay, interaction effects, market simulation, bundle analysis, and price optimization.

Making a recurring survey actually useful

Read the case study

The survey was meant to track product experience over time, but the first wave missed too many new users and a monthly memo could only answer so much.

Method: Survey design, oversampling, stratified weighting, significance testing, factor analysis, Python, Amplitude, Streamlit, and executive writing.

Finding an answer when the market data barely existed

Read the case study

The team needed to compare expansion and partnership opportunities, but the markets were small enough that the usual reports did not have much to say.

Method: Google Trends, audience overlap, community analysis, market sizing, secondary research, web-scraped metadata, and language-model-assisted coding.

Looking for the next audience in gaming

Read the case study

Mobalytics wanted to understand where it could grow beyond its current game mix. The useful evidence was scattered across audience, genre, platform, and competitor sources.

Method: Audience research, secondary research, demographic and motivation analysis, platform and spending trends, and competitive review.

Interactive demos

Three small tools built with synthetic data. They show how I structure pricing, product-experience, and market-opportunity questions without exposing employer work.

Choice Model Lab showing scenario controls and simulated preference results

Choice Model Lab

Change price and features, then see how preference, adoption, and revenue move across simulated customer segments.

Open the simulator
Pulseboard showing study filters, summary measures, and a trend chart

Pulseboard

Filter a synthetic product-experience study by platform, tenure, and metric, with confidence and cohort context built in.

Open the dashboard
Market Signal Mixer showing evidence weights and an opportunity ranking

Market Signal Mixer

Change how much demand, overlap, product fit, and whitespace matter, then watch the opportunity ranking move.

Open the explorer

Methods and tools

These are the methods and tools I reach for most often. I use them to answer the research question, check my assumptions, and share the result in a way other people can work with.

Research methods

  • Survey design
  • Conjoint
  • Hierarchical Bayes
  • Segmentation
  • Market sizing
  • Competitive intelligence

Analysis

  • Excel
  • Python
  • SQL
  • SPSS
  • Regression

Reporting

  • Tableau
  • Amplitude
  • Streamlit
  • PowerPoint
  • Research memos
  • Executive readouts

Research operations

  • SurveyMonkey
  • GitHub
  • Railway
  • Jira
  • Confluence

Interested in working together?

I am especially interested in market research, consumer insights, product insights, pricing, and market-intelligence roles. If that sounds like the kind of work you need help with, I would be glad to hear from you. Email or LinkedIn is easiest.

lizzieslavin@gmail.com · github.com/LizSlavin · United States