Hey Google, how valuable is that startup? Internet search queries and new ventures’ valuation—insights from B2B and B2C sectors

Abstract Valuing startups is inherently challenging due to high uncertainty and information asymmetry, which undermines the effectiveness of conventional valuation methods and compels investors to rely on intuition or qualitative judgments, often leading to inconsistent or manipulated valuations. This study explores the potential of internet search query data, particularly Google Trends, as a third-party signal to increase the accuracy of startup valuations. Grounded in signaling theory, we analyze valuation data from U.S. startups in two industry segments—B2C food delivery and B2B money lending—paired with their Google Trends data. Regression analysis reveals quadratic models with strong explanatory and predictive power, demonstrating that Google Trends data can reliably estimate a startup’s market value by contextualizing its search query data within its competitive landscape and incorporating a few known valuation points. This indicates that anonymized and aggregated search query data from reputable search engines (e.g., Google, Yandex, and Baidu), when analyzed in relation to competitors’ search data, act as credible third-party signal of market interest and serve as a form of certification of a startup's unobservable quality. Our research contributes to the literature on third-party signaling, startup valuation, and the use of digital signals in business decision-making, with practical implications for more transparent and data-driven valuation processes.