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Startup founders should not only be ‘data-driven’ but also data-driven • TechCrunch

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November 22, 2022
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Startup founders should not only be ‘data-driven’ but also data-driven • TechCrunch
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Anne Lai joined Bullpen Capital in 2020 as a general partner and has invested in and advised over 30 early to late stage companies.

among all The buzzwords startups use when pitching investors and marketing is “data-driven” at the top of the ladder. But what does being data-driven really mean?

Investments are shrinking and VCs are tightening their wallets. Already trending tech startups like BNPL, crypto and the delivery market are struggling to show the growth and returns they promised in their initial funding rounds.

Smaller startups with more modest goals make VCs more secure and seek smaller deals, but approaching early-stage ventures with a data-driven strategy is a one-sided approach—often to the detriment of startups.

Simple but important mindset shifts can change the way startups and investors look at data when making major investment decisions. Here are some tips.

Stop using unfiltered data

Using raw, unfiltered data is common among startups who don’t know how to properly filter their data, and often end up downloading information that isn’t relevant to their organization and mission.

For example, don’t show investors the total number of visits without showing the average duration of those visits – veteran investors will pick this up.

Instead of simply showing progress, show your progress based on the funding you’ve raised.

Unfiltered information can lead to bias and cause more harm than good. Many fast-growing AI programs have inadvertently created racial or gender biases based on unfiltered data fed to them. Understanding how to sift through data to properly tell a company’s story is critical to understanding where a company shines and where it needs to improve.

To avoid this, defragment your data and leverage it to your advantage.

Filtering data to accurately show operations and performance ensures you’re comparing apples to apples. Unfiltered data creates a series of inaccurate comparisons, highlights the wrong aspects of the business, and depletes the critical externalities that VCs are looking for.



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