What do you like best about the product?

As a university chair at the Technical University of Munich (TUM), we rely on Bright Data’s LinkedIn dataset to advance our research on entrepreneurship rankings, specifically assessing the impact of German academic institutions. Using this dataset, we match founder profiles with startups and universities to analyze key factors such as prior experience, gender distribution, cultural diversity, and geographic spread.

The quality and depth of the LinkedIn data have been critical in providing accurate, up-to-date insights into the entrepreneurial landscape. Thanks to Bright Data, we’ve been able to offer a data-driven perspective on important trends like female leadership and the geographic distribution of entrepreneurial activity linked to academia.

Bright Data’s platform is reliable, easy to integrate, and offers the comprehensive, real-time data we need to ensure our research stays relevant. We highly recommend it for any institution looking to perform rigorous, data-backed analysis.

A special thank you to the Bright Initiative for their generous support of our project. Your contributions have been invaluable in helping us drive impactful academic research.

What do you dislike about the product?

While we wish access could extend beyond just public LinkedIn data, this is a limitation beyond Bright Data's control. That said, the platform is reliable, user-friendly, and provides comprehensive real-time data that keeps our research relevant and impactful.

What problems is the product solving and how is that benefiting you?

Matching startups to academic instituions while providing details about founder profiles