Predict how the market reacts to a price change or move
Simulate customer churn, social backlash, and competitor counter-moves before you commit — online, in minutes.
MiroFish predicts market reaction by simulating the actual actors in your market — customers by segment, competitors, and press — as AI agents that respond to your move and to each other. For a price change, a rebrand, or a market entry, you get a report with churn risk by segment, the likely social-media narrative, competitor counter-moves, and the net revenue direction. It is hosted and runs in the browser with no setup.
Why this is hard to predict
Price and positioning moves are irreversible in reputation terms — customers remember. Statistical forecasting can’t model "how will our agency segment feel about a 20% increase," because there is no historical column for a reaction that hasn’t happened yet. A multi-agent simulation can.
How MiroFish predicts it
- 1
Describe the move
The exact change (e.g. "raise Pro from $29 to $39 on March 1"), who you care about, and the tension that makes it hard.
- 2
World modeling
Your segments, competitors, and channels become interconnected agents in a knowledge graph.
- 3
Multi-round simulation
Agents react, complain, defend, and undercut across rounds — second-order effects (press picking up churn, competitors responding) emerge naturally.
- 4
Structured report
Churn risk by segment, reaction narrative, competitor moves, net revenue estimate, and recommended mitigations.
Example prompt
What you get
- Churn / backlash risk broken down by customer segment
- The most-likely reaction narrative and where it spreads
- Competitor counter-moves to expect
- Net revenue direction with the key drivers
- Mitigations ranked by impact
Frequently asked questions
How is this different from statistical forecasting?
Statistical forecasting extrapolates historical numbers and works when the future resembles the past. Market-reaction prediction models the actors and how they respond to a novel event — which is exactly where statistics has no data. They are complementary: simulate to map the reactions, then quantify the ones that matter.
What can I predict market reaction for?
Price changes, rebrands, market entry, feature launches, policy shifts, PR responses — any move whose outcome depends on how people react to people.
Is it accurate?
Reports are calibrated probability estimates, not guarantees. They are most reliable at directional insight — which segments react, in what direction, and the main risks — which is what protects the decision.
Want the full method? Read the deep-dive: on the MiroFish blog →
Run it on your own scenario
No install, no API keys. Credit packs from $2.99 — results in minutes, credits never expire.
Start predicting