Between all buzzwords startups use when pitching to investors and in their marketing, “data-driven” is near the top of the pile. But what does being data-driven actually mean?
Investments slow down and VCs hit the wallet. Previously trending tech startups in areas like BNPL, crypto and the delivery market are struggling to show the growth and returns they promised in their first rounds of funding.
Smaller startups with more modest goals may entice VCs to look for safer, smaller deals, but approaching an early-stage venture with a data-driven strategy is a one-sided approach — one that often works to the disadvantage of startups.
Simple but necessary mindset shifts can change the way startups and investors look at data when making important investment decisions. Here are a few tips:
Stop using unfiltered data
Using raw, unfiltered data is common among startups that don’t know how to properly filter their information, and they often end up discharging data that isn’t relevant to their business and mission.
For example, don’t show investors the total number of visits to your web page without also showing the average duration of those visits. Veterans will pick this up.
Instead of simply showing growth, you show growth against the backdrop of the funding you’ve raised.
Unfiltered data can lead to biases and do more harm than good. Many rapidly evolving AI programs have inadvertently developed racial or gender biases based on the unfiltered data fed to them. Understanding how to filter data to tell a company’s story correctly is critical to understanding where a company excels and where there is room for improvement.
To avoid this, segment your data and use outliers to your advantage.
By filtering data to accurately represent operations and performance, you can be sure you’re comparing apples to apples. Unfiltered data creates a series of imprecise comparisons, highlighting the wrong aspects of the business and obscuring critical outliers that VCs look for.