LLMS REPRODUCE HUMAN PURCHASE INTENT VIA SEMANTIC SIMILARITY ELICITATION OF LIKERT RATINGS

Summary from the TLDR AI newsletter

AI can closely replicate human consumer choices across 57 personal care products without knowing much about the shoppers, achieving 90% of human test-retest reliability using a "semantic similarity rating" method. Instead of asking LLMs for numerical ratings (which produces unrealistic clusters around safe middle values), the breakthrough approach has AI write responses like "I'm somewhat interested if it works well and isn't too expensive," then maps these to rating scales using embedding similarity. The method could replace billions in annual consumer research spending while providing richer qualitative feedback than traditional surveys.