One reason startups use crazy and bizarre names like NegaCycl and Filtrzzz is to ensure that their name is unique, making it easier to acquire the .com domain name and Twitter handle for their startup. Another reason is to make their startup sound kewl and theoretically make the name more memorable in the minds of users and potential investors.
Dakwak, Wibki, Zeef, Funifi. These aren’t random words: these are funded startups which were featured at TechCrunch Disrupt Startup Alley 2013. And then you have startups such as Lyft, SCVNGR, and Fastly, which have all raised tens of millions of dollars in venture capital.
Do startups with these short, low-vowel names actually raise more money than startups with traditional names?
First, let’s take a look at the association between the length of words in the English language and the number of vowels that they contain:
In the English language, the majority of the words have 8 letters, with 3 of those letters being vowels. (8,3) is also the center of the density distribution for the heat map, spreading outward.
Let’s compare the vowel distribution of normal English words to the distribution of the names of startups that have successfully raised venture capital, in order to identify just how many funded startups have quirky names:
Wait, the two distributions are nearly identical! Both graphs are centered at about (8,3), radiating outward. This implies that the number of startups with uniquely-constructed names are outliers and not the typical names for startups.
But that doesn’t answer the core question: sure, fewer funded startups have weird names relative to the amount of total funded startups, but do they raise more money on average than startups with typical names?
There is no discernible pattern for the average amount raised, unlike with the previous two charts. For the vast majority of the possible combinations of name length and $ vowels, the range of capital raised is between $5M and $25M. There are higher values at the lower-end of the graph (low length, low vowels), but that can be attributed to the relatively low amount of startup data for those combinations to smooth out the average. (e.g. the $78M spike at 3 length, 2 vowels is due to the always-lovely AOL and a $1 billion investment from Google, and there are only 15 other startups in the segment.)
In fact, the statistical correlation between name length and funding, number of vowels and funding, and ratio of length to vowels and funding, are all effectively zero.
Sure, quirky startup names may make it easier to find a domain name, but it won’t necessarily give an edge in the investment process.
I am currently looking for a job in data analysis/software engineering in San Francisco. If you liked this post and have a lead, feel free to shoot me an email.
Since I currently do not have a full-time salary to subsidize my machine learning/deep learning/software/hardware needs for these blog posts, I have set up a Patreon, and any monetary contributions to the Patreon are appreciated and will be put to good creative use.