Simulate Market Adoption
Before You Build
Market Physics Engine simulates how real stakeholders react to a new product — then tells you exactly what is blocking adoption and what to change. Behavioral economics, synthetic market modeling, strategic recommendations.
Most validation methods miss the real failure mode
Product ideas fail not because the technology is weak, but because markets resist adoption. The behavioral friction — perceived risk, cognitive cost, regulatory resistance — is invisible to standard validation approaches.
Successful products must overcome real stakeholder psychology before they can grow. Understanding these forces early prevents costly mistakes.
- Cognitive friction and switching cost
- Perceived financial and regulatory risk
- Ecosystem readiness and timing
- Stakeholder resistance across the value chain
- Trust and social signaling dynamics
Typical validation methods
- Intuition and founder conviction
- Small user surveys
- Market size estimates
- Limited focus groups
- Landing page A/B tests
- Advisor opinions
None of these methods simulate behavioral adoption dynamics across a real stakeholder ecosystem.
From product idea to adoption probability in minutes
Enter the concept
Describe a product or startup idea in plain language. No templates, no forms — the system reads context directly.
Persona generation
A language model generates 12 industry-specific stakeholder archetypes with calibrated behavioral vectors across 8 decision dimensions.
Agent expansion
Each persona seeds a population of synthetic agents. Gaussian variation creates 10,000 heterogeneous decision-makers approximating real market diversity.
Behavioral scoring
Each agent computes a utility score: value drivers (utility, emotion, social, timing, market readiness) minus friction drivers (cognitive cost, risk, regulatory).
Diffusion simulation
12 sequential market periods model adoption spread through a Watts-Strogatz network. Social proof builds, risk perception decays, adoption accelerates.
Fitness analysis
The Idea Fitness Index combines normalized utility, market readiness, adoption probability, and a friction penalty. Output benchmarks against Airbnb, Uber, Stripe, and Slack.
Strategic Action Layer
Friction variables ranked by dominance. Scenario deltas show exactly what happens if R, C, or G drops 20%. Specific recommendations tied directly to model output — not generic advice.
Scenario Comparison
Run the same pitch under different market conditions and see side-by-side deltas on IFI, adoption, and tipping point period — with a causal explanation of what drove the change.
Adoption Leverage Points
Identifies the highest-impact changes to increase adoption. Quantifies how sensitive IFI is to each friction variable and highlights which reductions produce meaningful gains versus negligible effects.
Simulation outputs
Most validation tools ask what people think. This simulates what they do.
The engine treats stakeholder decisions as a behavioral physics problem — where perceived value competes against structural friction across a population of heterogeneous decision-makers.
Each model was chosen for a specific reason. Not because it is well-known, but because it explains a specific failure mode that standard validation misses.
Prospect Theory
Kahneman & Tversky showed that losses loom larger than equivalent gains. Friction variables are weighted asymmetrically — a regulator's resistance costs more adoption than equal consumer enthusiasm generates.
Bass Diffusion Model
Separates innovator adoption (intrinsic utility) from imitator adoption (social proof). Produces the S-curve observed in every major platform market — slow start, acceleration, saturation.
Watts-Strogatz Network
Agents respond to their immediate network, not a global signal. Local adoption cascades through clusters before reaching the broader population — which is why real markets have tipping points.
Monte-Carlo Simulation
No single persona represents a market. Gaussian variation across 10,000 agents captures the decision heterogeneity that single-point estimates miss — including the resistant tail that often determines whether a product scales.
Airbnb — tested at concept stage
A marketplace allowing travelers to book rooms with local hosts instead of hotels.
12-period adoption curve
Stakeholder sentiment sample
Built for decisions made before the product exists
Startup Founders
Validate ideas before committing engineering resources. Identify friction early enough to address it in the design.
Venture Investors
Assess behavioral adoption risk in early-stage startups. Compare IFI scores against historical benchmarks.
Innovation Teams
Evaluate product concepts before launching internal development projects or committing budget.
Accelerators
Screen startup applicants using standardized behavioral simulation. Run hundreds of pitches through the same model.
Start free. Scale when it matters.
- 3 simulations per month
- 12-period diffusion curve
- Stakeholder sentiment
- Benchmark comparison
- 50 simulations per month
- Strategic Action Layer
- Scenario comparison view
- Full PDF reports
- Run history dashboard
- Scenario engine access
- All benchmark anchors
- Unlimited simulations
- Strategic Action Layer
- Scenario comparison view
- Unlimited PDF reports
- Full run history
- Priority support
- API access soon
Before investing capital or engineering resources, simulate how the market reacts.
10,000 agents. Behavioral economics. Diffusion simulation. Results in minutes.
Run Market Simulation →