What are the most common mistakes founders make when they build their first unit economics model?
The short answer
The classic traps are using blended CAC to hide bad paid channels, ignoring the cost to serve and support, assuming churn stays flat forever, and treating a hopeful LTV as fact. Founders also forget refunds, payment fees, and their own time, which makes every number look rosier than reality. As a starting point, build your model to be embarrassingly conservative, because a plan that survives pessimistic assumptions is the only one worth raising or spending against.
Go deeper, your way
2 hand-picked resources, 2 link-checked. Pick how you want to dig in.
📄 Article
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Why we picked it
The reference primer on the metrics and market-sizing logic investors use, including bottom-up market sizing that keeps founders honest about how big a market really is. Canonical a16z source.
Why we picked it
Where the a16z essay defines the metrics, this one reads like an audit checklist for the model you just built. It names eight frequent errors in plain language, from forgetting the hidden costs that understate CAC to inflating retention with no data behind it, so you can run your own numbers against the list line by line. It is framed squarely around the founder's financial model, which is exactly where these mistakes get baked in.
Founders routinely understate CAC by leaving out salaries, tool costs, sales commissions, and agency fees, then wonder why real spend never matches the model.
A blended CAC hides the truth: segment by channel, because organic and paid, or Google Ads and events, have very different economics that a single average papers over.
Two quieter traps are assuming CAC keeps improving forever (early adopters are cheaper than later customers) and inflating LTV with retention assumptions your data does not support.
