AI-assisted market hypotheses to guide planning, experiments, and field validation.
BuyerIQ uses product information and a language model to suggest market segments, scenarios, and experiments. Generated scores are not observed behavior or calibrated purchase predictions. External research does not establish BuyerIQ accuracy. Field validation is required: test assumptions with customers and observed outcomes before acting.
BuyerIQ generates market hypotheses and TAM/SAM/SOM scenarios to guide further research. Analysis runs asynchronously and duration varies with the request and service load. Research costs and timelines depend on scope, recruitment, and methods; AI output is not a substitute for collected evidence.
Founder includes up to 100 total paid AI requests per day for $39/month. You share the daily limit across analyses, chat, launches, and crawls, rather than offering a separate allowance for each operation.
Explore alternative positioning, pricing, audiences, and feature sets. Treat generated segment scores as hypotheses, not measured purchase probabilities or evidence of group behavior. Use comparisons to choose experiments, then evaluate them with real customers.
Use generated TAM/SAM/SOM scenarios as a starting point for market sizing. Verify the underlying sources, geography, annual units, and adoption assumptions before using figures in an investor deck or due diligence. These scenarios are not independently verified forecasts.
Generate segment hypotheses and market scenarios, then test the important assumptions with customers and observed outcomes.
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