Why data matters
Sidera Labs is a data driven fund, which means that we are heavy users of data both in our investing as well as in our portfolio ops work. We are often asked whether data really matters at the early stage - after all, there are very few companies with sub-10m GMV investing meaningful resources into analytics.
To illustrate why data matters, we like to take founders through why it is dangerous to rely on simple aggregate metrics like Return On Ad Spend (ROAS). These are in wide use across the industry.
The most basic calculation of ROAS involves dividing Revenues by Marketing costs:
At a high level this looks like a 2x ROAS - which isn’t great but may not seem that bad either. But let’s dig in.
We want to first make sure that we isolate revenues coming from users who are actually new:
ROAS now looks to be closer to 1x. Factoring in COGS and other expenses, we are now losing money on new customers.
It makes no sense to include customers acquired organically in assessing the effectiveness of paid marketing - so let’s take them out:
Someone with a background in customer analytics would point out that it’s not enough to look at initial purchases - some of the returning customers were also acquired through paid marketing.
It is indeed very important to split those out as well:
We see that in this hypothetical example customers acquired through paid marketing tend to be less likely to return that those acquired organically - this is actually quite typical.
The bottom line is that a paid marketing effort with an overall ROAS of 2x is actually highly unprofitable. Savvy marketing managers tend to aim for ROAS of 4x in part because they are aware that high-level metrics are usually deceptive, but to actually understand what you as a founder may be missing you need to dig into your data.
Channel attribution, LTV analysis, and customer segmentation may sound academic - but they are essential to ensuring effective resource allocation. Unfortunately for early-stage startups ineffective resource allocation often leads directly to business failure.
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