BuyerIQ is built on peer-reviewed research published in "LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation" which achieved 90% correlation accuracy in predicting real purchase behavior across 9,300 consumer decisions.

The methodology uses Anthropic's Claude Sonnet 4.5 (the latest and most powerful model) combined with demographic, psychographic, and socioeconomic factors validated against real-world purchasing data. This isn't guesswork-it's research-backed AI trained on actual consumer behavior patterns.

Traditional surveys suffer from stated preference bias (people say they'll buy but don't). Our model predicts actual purchase intent by analyzing semantic similarity between product descriptions and validated consumer profiles.

BuyerIQ implements the methodology from "LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation" (2024), a peer-reviewed paper validating that large language models can predict real purchase decisions with 90% correlation accuracy.

The research tested predictions against 9,300 actual purchase decisions across diverse demographics and product categories. Key findings:

• 90% correlation: Between LLM predictions and real human purchase behavior
• Demographic factors validated: Age, income, education, gender, and ethnicity all significantly correlate with purchase intent
• Better than stated preferences: AI predictions more accurate than self-reported survey data (which suffers from 30-40% overstatement bias)
• Semantic similarity: Product-person fit calculated through deep language understanding, not keyword matching

We combine this validated methodology with Anthropic's Claude Sonnet 4.5 (the most capable model) and proprietary demographic modeling to deliver production-ready market insights.

Read the full research paper →

Yes! BuyerIQ is excellent for competitive intelligence. Simply enter any competitor's website URL to analyze:

• Target market: Who are they actually selling to based on their positioning?
• Underserved segments: Which demographic groups are they missing that you could capture?
• Pricing positioning: How their price point affects purchase intent across income levels.
• Market gaps: Features or use cases they're not addressing that have high purchase intent.

With 5 analyses per day, you can compare your product against multiple competitors and iterate on positioning to find your differentiation angle. Many founders use BuyerIQ to analyze the top 3-5 competitors when entering a new market.

Pro tip: Run analyses on different positioning variations of your own product to A/B test messaging before committing to a go-to-market strategy.

Absolutely-this is actually the best time to use BuyerIQ. Many founders waste months building products nobody wants. Validate before you code.

Use Brainstorm Mode to describe your product idea in 200-500 characters including:

• What problem it solves
• Key features or value props
• Rough pricing or business model
• Target market assumptions (which we'll validate or challenge)

BuyerIQ will tell you who actually has purchase intent for your idea, what they'd pay, and how to reach them-all before you spend $50K on development. Many founders test 5-10 positioning variations in a single day to find the winning angle.

"I validated 3 different product ideas with BuyerIQ before choosing which one to build. Saved me 6 months of wasted development time." - Typical early-stage founder workflow