We analyzed more than 26 million negotiations to integrate research on first-offer anchoring and impasses and ask: when do the benefits of ambitious first offers outweigh their impasse risk? How high should the first offer be before it is too high?
We use linear and logistic regressions, and machine learning analyses to empirically test past assumptions of linearity and the midpoint bias. We show moderation by price certainty and buyer demand, and we create machine-learning-based classification models to predict whether a negotiation ends with an agreement or with an impasse.
This website:
Building on these analyses, this website provides free first offer advice.
Negotiators can get machine-learning based suggestions for how high their first offer should be. Negotiators can receive individual advice, based on how expensive a product is, what kind of a product it is, and how risk-sensitive they are to an impasse.
This tool translates our empirical findings into practical recommendations and actionable strategies for negotiators by providing evidence-based first-offer recommendations.