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Data-Driven VC
How to Extract Names From Startup Landscapes & Market Maps At Scale
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How to Extract Names From Startup Landscapes & Market Maps At Scale

DDVC #58: Where venture capital and data intersect. Every week.

Andre Retterath's avatar
Andre Retterath
Oct 26, 2023
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How to Extract Names From Startup Landscapes & Market Maps At Scale
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👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.

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Following two more qualitative deep dive pieces on cognitive and data biases involved in the investment selection process, today’s episode will cover one of the most frequently asked operational questions: How to Automatically Extract Names From Startup Landscapes and Market Maps?

Wondering why you would even want to do this? Read on, I’ll explore two exciting use cases at the end of this article. While a year ago, this episode would’ve been several pages long, the widespread adoption and powerful capabilities of LLMs and ChatGPT allow me to keep it short. So let’s dive right into this simple step-by-step guide.

1) Sign up for ChatGPT+ for $20/month (with priority access to new features such as DALLE-3 integration)

2) Copy & paste an Image of the Market Map or Startup Landscape Into ChatGPT+

3) Add the Prompt “Extract the startup names from the image above and list them in bullets based on the different categories in the landscape”

I tested and double-checked the results for 20+ landscapes and the extraction is almost entirely correct. Few minor errors but tbh in some of the cases I couldn’t even recognize the companies by their logos myself 🙄

4) Add the Prompt “Find website for above startups”

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