Predicting entrepreneur fundraising success from focus group EEG data

TL;DR

This study shows that brain activity measured from a small group during entrepreneurial pitches can predict how successful those pitches will be in securing funding.

Contribution

The study introduces EEG-based metrics as novel predictors of investment outcomes in entrepreneurial fundraising.

Findings

Alpha asymmetry in the first 10 seconds of a pitch predicted investment interest and amounts better than self-report or text data.

Correlated neural activity among viewers increased during pitches and predicted deal success.

EEG signals offer early indicators of fundraising outcomes and communication effectiveness.

Abstract

We examined how electroencephalographic (EEG) brain activity responded to entrepreneurial pitches for venture funding and whether EEG signals from a small laboratory focus group (N = 28) could be used to predict subsequent investment outcomes. Specifically, we tested whether EEG signals of frontal alpha asymmetry and correlated EEG activity across evaluators (i.e., neural similarity) were associated with investment interest expressed by a larger population group (N = 497), as well as with the likelihood that a pitch secured a deal and, if so, the size of the investment. We found that alpha asymmetry in the first 10 seconds of a pitch predicted population-level investment interest and investment amounts, above and beyond standard self-report and textual measures. Furthermore, correlated neural activity among viewers—a measure of communication effectiveness—ramped up over time during the pitch presentation and predicted deal outcomes. These findings suggest that EEG signals in evaluators viewing entrepreneurial pitches provide early indicators of aggregate investment interest and fundraising outcomes. Together, our findings illuminate a future roadmap for reverse engineering entrepreneurs’ pitches using brain signals to enhance funding success.

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