Understand demand.
Before you commit.
Test products, pricing and positioning with AI audiences grounded in real social signals. Turn an uncertain decision into a clearer view of what your customers may choose.
The problem
New products need
more than old data.
Historical sales can explain what happened. They offer less guidance for a product, format or price your customers have never seen. Small focus groups and internal judgment leave important questions unanswered.
Social Mirror Audiences builds a research panel from thousands of creator profiles, then calibrates its responses against real-world signals. Your team can compare options before committing to production or a launch.
The research model
A panel grounded
in real signals.
The method
A richer model of
the people you serve.
Creator-to-audience signals
Social creators act as proxies for audience segments. Their content and preferences help inform the consumer profiles in a panel.
Multimodal understanding
The analysis draws on over 100 visual, linguistic, behavioral and audience signals, rather than a few profile fields.
Calibrated predictions
A proprietary validation process tests the panel against real signals before its responses become part of a study.
How it works
From social signals
to a decision.
Research foundations
More than plausible answers.
The approach draws on research into personality prediction from digital content, synthetic survey respondents and the relationship between creator preferences and audience behavior. The source methodology is patent-pending.
Real signals
Panels are anchored to observed content and calibrated reference data.
Category expertise
Research questions reflect the way customers evaluate your category, product and alternatives.
Validation
Predictions are checked against outcomes where sales or other observed evidence is available.
Product decisions
Build the range
people actually want.
Range strategy
Compare variants, tiers and offers. Identify which options deserve space in the range.
New lineups
Put a proposed collection side by side and evaluate it before production.
New formats
Test bundles, extensions and multi-use products as complete propositions.
Inventory planning
Use predicted demand shares to inform how much of each option to order.
Concept forecasts
Assess purchase intent, relevance, uniqueness, credibility and perceived value.
Unmet demand
Explore what customers are asking for that your current range does not provide.
Product research in practice
Explore the original studies.
Marketing decisions
Find the price,
message and audience.
Willingness to pay
Compare price points and identify where purchase intent falls away.
Size and price
Evaluate the pack size and price together, as customers encounter them.
Competitive positioning
Understand where an offer wins and loses against relevant alternatives.
Audience and channel
Find the segments and channels where demand is most concentrated.
Claims and language
Test messages and explore the reasons behind a response.
Demand ranking
Compare predicted product preferences with real sales when results become available.
Marketing research in practice
See the evidence
behind the decision.
A published study
A launch ranking,
called before launch.
A DTC beauty brand used GEN’s Social Mirror Audiences across product, pricing and positioning studies. In a lip-liner study, the panel’s pairwise comparisons predicted the same order later observed in sales.
- 01 Soft Pink
- 02 Cool Nude
- 03 Blush Berry
Soft Pink won its comparison with Cool Nude at 80.3%. Soft Pink beat Blush Berry at 58.2%, and Cool Nude beat Blush Berry at 58.2%.
A published, anonymized case study. Pairwise preference establishes this ranking; individual top-choice shares are a different measure. The result is evidence from this study, not a guarantee for another product.
Estimated business impact
What the decision
can change.
A week-long pilot
A specific question.
A useful answer.
Day 1 — Scope and calibrate
Agree the decision, review reference signals, select the audience and frame the study.
Days 2–4 — Run and analyze
Run the panel, build rankings or scorecards, inspect segment differences and validate the output.
Day 5 — Make the call
Receive a hosted report with the finding, supporting data, sample responses and a practical recommendation.
Let’s build what comes next