Fairgen
Revolutionize research with AI-driven synthetic sampling and data integrity tools.. [Contact for Pricing]
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What is Fairgen?
Fairgen is an AI-powered synthetic data research suite designed for market research professionals, insights teams, and research agencies. It combines generative AI with proven market research methods to deliver faster, deeper, and more trusted insights. The platform offers two main capabilities: Fairgen Twins (digital twins/simulated audiences) and Fairgen Boost (AI-augmented synthetic respondents for survey data).
Fairgen Twins creates simulated versions of real survey respondents built from premium panel data or your own research. Users can pick an audience, run end-to-end studies (concept testing, messaging/ad testing, customer discovery, pricing & packaging, brand perception), and receive a full consultancy-grade insights deck in about 20 minutes. Alternatively, users can chat directly with individual digital twins for depth-interview-style conversations. Teams can also build private audiences by uploading their own quant and qual research data.
Fairgen Boost enhances existing survey results by generating predictive synthetic respondents that match underrepresented niche segments. This allows researchers to unlock granular insights into hard-to-reach audiences (like Gen Z, early adopters, niche voters) without additional fieldwork. The platform preserves survey integrity by understanding skip logic, piping, and multi-selects, and achieves error margins comparable to tripling real sample sizes.
Key features include: fraud detection (Check), sample expansion (Boost), imputation for filling gaps in existing studies, digital twins marketplace with 100k+ twins across 40+ industries, XML survey structure uploads, white-labeling for agencies, and a 14-day free trial. The tool is designed for product managers, marketers, insights teams at brands, research firms, panel providers, and CMI teams who need customer input on decisions that can't justify expensive traditional studies.
Fairgen pricing
Pricing model: Freemium
14 days free trial with no credit card required. Pricing details are not publicly disclosed on the website - users must schedule an introductory call/demo with the Fairgen team. The website mentions traditional research costs $5K to $200K and Fairgen sits in the gap for decisions that can't justify a $10K study. Marketplace audiences are ready immediately upon signup. Private audiences require uploading your own quantitative dataset. Enterprise-grade deployment with governance and security is available through professional services.
Fairgen pros
- 14-day free trial with no credit card required
- Generates full insights deck in under 20 minutes
- 100k+ digital twins available across consumer and B2B categories
- Covers 40+ industries represented in the twin catalog
- Trains only on your real survey data - no external sources or LLMs
- Preserves survey structure including skip logic and piping
- Achieves error margins comparable to tripling real sample sizes
- Detects and removes fraudulent or unwanted survey responses
- White-labeling built in for agencies (your logo, brand colors, deck)
- Works for concept testing, ad testing, pricing, customer discovery, brand perception
- Build private audiences from your own research data
- Marketplace audiences ready immediately without upload or setup
- Chat with individual twins for depth-interview-style conversations
- Validated across 10,000+ concurrent boosts
- No minimum sample size required to create private audiences
- Upload XML survey structure for automatic interpretation
- Extends revenue for research providers by publishing twin panels
- Reduces need for costly oversampling in trackers
- Supports quantitative fields including NPS, rankings, ratings
- Results ready in just 15 minutes for boosted samples
Fairgen cons
- Directional research only - not a replacement for definitive field studies
- Not suitable for brand tracking, segmentation, or conjoint analysis
- Cannot simulate audiences with no existing data in catalog or primary data
- Qualitative questions cannot be augmented (quantitative fields only)
- Requires base large enough to ensure statistical confidence for boosting
- Focus-group format with multiple twins in live conversation not yet available
- Enterprise deployment requires professional services support
- Pricing details not publicly disclosed - requires scheduling demo
- Built from real respondents only - cannot create twins from scratch
- Generic AI making educated guesses warning applies to out-of-data questions
Frequently asked questions about Fairgen
What is Fairgen Twins?
Fairgen Twins is a marketplace of digital twins: simulated versions of real, named respondents built from premium panel data. You pick an audience, run a study, and get a full research deck in 20 minutes with quantitative results, qualitative themes, direct quotes from individual twins, and a recommendation summary. Teams with their own research data can also build private audiences by uploading quant and qual research. This is directional research for decisions before the big study and for smaller decisions that won't get one.
What is a digital twin in market research?
A digital twin is a simulated version of a real survey respondent. Individual-level data from a quantitative study is used to build a detailed profile for each one: what they buy, what they believe, how they respond in their category, how they write and reason. Each twin gets an assigned name and photo. The panel behaves like the audience it was built from, not like a generic population.
How are digital twins different from ChatGPT for audience research?
ChatGPT is trained on the whole internet and gives confident, smooth, unverifiable answers optimized for plausibility rather than truth. Fairgen twins are built from real individual-level data specific to that person, that category, that geography. They disagree with each other, have different views, and answer the way the underlying research data says they should. There are no invented profiles - nothing exists until real panel data is used to build it.
How accurate are digital twins compared to real market research?
Directional, not definitive. Every twin is built from real panel data from trusted sources researchers already rely on. The twins reflect how a real, known audience actually thinks and behaves. Category-specific twins built from deep research give stronger results than generic profile studies. Use Twins to pressure-test before going to field - filter concepts, find which message lands, validate pricing hypothesis - then spend real budget on what you know will work. Not right for brand tracking, segmentation, complex statistical modeling, or conjoint analysis.
Who are Fairgen Twins built for?
Product managers, marketers, and insights teams who need customer input on decisions that can't justify a $10K study. Also research agencies looking to extend the life of work they've already delivered. Not the right tool for decisions that need statistical confidence - those go to field.
What can digital twins be used for in market research?
Five categories: concept testing (rank ideas, identify winner and why), messaging & ad testing (test copy, creative, CTAs before media budget), customer discovery (understand pain points and jobs-to-be-done without focus group), pricing & packaging (find out how target segment thinks about price), and brand perception (see how brand sits in category). Run end-to-end studies producing executive insights decks in about 20 minutes, or have one-on-one conversations with individual twins like depth interviews without scheduling.
Do I need to upload my own data to use Fairgen Twins?
No. You can start with the marketplace immediately. Marketplace hosts premium audiences built using premium data, ready to use the moment you sign up with no upload or setup. If you want to build a private audience from your own data, that requires uploading your quantitative dataset through the audience creation wizard. The two options are independent - you can use marketplace audiences today and build private audiences later.
What is the difference between marketplace audiences and private audiences?
Marketplace audiences are built with data providers using custom and syndicated data. They are available immediately with no upload required. Private audiences are built from your own data - upload a dataset, optionally add transcripts and reports, and get a simulated audience visible only to your account. Build once, test endlessly.
How long does it take to run a study with Fairgen Twins?
End-to-end research takes minutes. From picking your audience to running a study to receiving a full executive deck with quant results, qualitative themes, direct quotes, and recommendation summary, the whole thing is done in under 20 minutes. From there you can go straight into chat with any individual twin to dig deeper on anything the study surfaced.
How is Fairgen Boost different than reweighting?
Fairgen will reduce your niche segment's margin of error while classic reweighting techniques will not. When applying different weights for specific segments in quantitative surveys, there is no impact on confidence intervals for that group. Fairgen generates predictive synthetic respondents that statistically match properties of additional real ones, achieving error margins comparable to tripling real sample sizes.