Seminal resources in the Shark Tank analysis space
Primary data from the American TV series Shark Tank (Seasons 1–16), covering over 1,440 startup pitches and 53 attributes per pitch to uncover what are the factors that influence whether a pitch gets a deal or not
Pitch transcripts from Seasons 12-15 of the Shark Tank series for language analysis.
This project from Carnegie Mellon uses the same Kaggle dataset as this study to explore how features relate to investment outcomes on Shark Tank. Their statistical tests find no strong, consistent predictors of getting a deal based on these structured features alone. This motivates a shift from solely structured data towards transcript language analysis to unveil the driver of pitch success.
An interactive visualization site analyzing investment patterns in Shark Tank India Seasons 12, showing how industry, location, and investor behavior vary across pitches through rich exploratory charts.
A static data analysis article examining correlations between founder demographics, industry type, and investment outcomes on the U.S. show, emphasizing descriptive insights and bias patterns without offering interactivity or prediction.