Frequently Asked Questions

BuyerIQ is an AI-assisted hypothesis generator. It uses supplied product context rather than a panel of survey respondents:

1. Input: Supply product details, pricing, website content and relevant user-reported observations.
2. Generation: A language model proposes segments, scenarios and experiments. Processing time varies.
3. Evidence: Distinguish observed inputs, dated sources, assumptions and generated hypotheses.
4. Field loop: Test assumptions, record field evidence and use it to inform a new immutable company version. Prior versions remain history, not proof of accuracy.

User-uploaded data and field notes can be incomplete or unrepresentative. Model knowledge is not live retrieval, and generated explanations are not independent verification.

No. A 0–100 heuristic compatibility score is not a purchase probability, conversion rate or measure of product-market fit.

There is no published product-specific predictive accuracy benchmark. Meaningful calibration requires real, consented outcomes and remains future work:

• External research does not validate this application.
• Representative held-out outcomes and meaningful baselines are needed.
• Evaluation must report calibration, errors, uncertainty and limitations.
• Arithmetic and content tests do not measure prediction quality.

Learn more about our methodology →

BuyerIQ supports B2C and B2B customer-discovery planning, with usefulness dependent on the evidence you provide:

• Pre-seed founders: Organize assumptions and plan interviews before building.
• Product managers: Frame feature hypotheses and evidence gaps.
• Growth teams: Propose segments and positioning tests.
• Investors & advisors: Identify questions for independent due diligence.
• Marketing teams: Draft audience and channel hypotheses.

B2B hypotheses emphasize role, seniority, industry, company size, buying committee, budget authority and procurement constraints—not invented demographic differences.

Yes. An early idea can be a useful starting point for planning customer discovery.

Use Brainstorm Mode to describe your product idea, including:

• What problem it solves
• Key features or value propositions
• Rough pricing or business model
• Target market assumptions (which still need field validation)

BuyerIQ suggests who you could interview, pricing questions and possible channels. It cannot establish who will buy or what they will pay.

Report depth depends on your plan. Paid reports can include:

Generated reasoning is not evidence that a segment will buy. Founder A/B output is planning, not execution tooling; integrated workflows are coming soon. Run experiments in your own tools.

Surveys collect responses from real people. They can have sampling and stated-preference biases, but they provide a different kind of evidence from generated text.

BuyerIQ generates hypotheses from supplied context. It does not measure respondent behavior or replace interviews, surveys and observed purchase outcomes.

Key differences:

• Evidence: Generated scores are not survey responses.
• Timing: Generation time varies by depth and service load.
• Validation: Collect consented outcomes and review sample limitations.
• Use together: Plan research with hypotheses, then test them in the field.

Full comparison: BuyerIQ vs Surveys →

Try a free limited preview. Founder is $39/month or $374.40/year.

Paid AI usage has a shared daily allowance, not a separate allowance per feature:

• Founder: up to 100 paid AI requests per day.
• Report sections and export availability depend on your plan.
• Refinement and other paid AI operations share the same allowance.
• Manage an existing subscription through billing management rather than starting a second checkout.
• Company history and public sharing have retention caveats; see the Privacy Policy.

View full pricing details →

Yes, where public content is accessible. Supply only content you are authorized to use. A website supports hypotheses, not access to private customer behavior:

• Target market: Who might the product serve?
• Segments: Which needs may be under-addressed?
• Pricing: What prices and dates need source verification?
• Market gaps: Which possible gaps should customer research investigate?

Competitor requests share your paid AI allowance. Verify important facts against dated sources; model memory is not live retrieval.