How Founders Evaluate VCs: A GPT-Based Extraction of Value-Criteria from Online VC Reviews
Research
Authors
Oliver Specht, Jonas Wilinski, Jürgen Christopher Thiesen, Christoph Ihl
Abstract
Venture Capital (VC) investments positively impact startup success, enhancing operational performance through factors like collaboration and value-added services. While research on investment decisions primarily focuses on investors’ selection criteria and decision-making processes, our study addresses the gap in founders’ perspective. Using Generative Pre-Trained Transformers (GPT) for text classification on a dataset of 8,561 online VC reviews, we extract 9,229 unique value-criteria from founders’ perspectives. A text-embedding cluster method categorizes these criteria into 26 categories. By analyzing additional startup lifecycle data, we determine which value-criteria are crucial at different startup stages. Our findings reveal that investors’ “general social skills” are the most important value-criteria across all startup stages, while more mature startups prioritize more self-serving criteria focused on growth and long-term relationships. Additionally, we observe that founders mostly fulfill the value-criteria by investors, with “general advice” being particularly well-executed.
Tags
Venture Capital Founders NLP GPT