How to Measure the Health of a Startup

Here are the most useful metrics I’ve found for running a startup. These should be measured and reviewed regularly. The metrics that matter most the ones that raise questions and drive useful discussions. Try to avoid difficult to calculate metrics that are hard to build an intuition about (people don’t expect much from simple ideas).

MRR growth: You need to grow 6% monthly in order double revenue in a year. Of course, time is a factor, so venture-backed businesses need to be mindful of the time to the first $1MM of ARR.

Churned revenue: Monthly revenue churn is a headwind that slows growth and makes it difficult to sustain growth. High churn is also a signal that something else is going on which needs immediate attention.

Runway: By calculating burn rate each month you can estimate how much time you have before the business runs out of cash. Many important decisions need to be made with this in mind such as layoffs, seeking an aquisition, or spending to grow faster.

GTM efficiency: Net magic number breaks my rule a bit about avoiding complicated metrics, but it’s easy to reason about once it’s measured—for each dollar spent on marketing, how much revenue is it expected to return. A number less than 1.0 is bad (magic vending machine business model), a positive number greater than 1.0 is good, and multiples means you should spend more to grow faster.

Engineering velocity: By far the easiest number to track for engineering health is the number of commits to the main branch every week. There shouldn’t be a target set (Goodhart’s law) but if the number goes down (or up), it’s useful for the team to ask what’s going on so they can make adjustments if needed. It should also generally increase as more engineers are added to the team although sub-linearly as the company and codebase gets more complicated.

Defect rate: This will depend on the product, but having a way to know if delivery of the product is getting better or worse will help spot issues early. I’ve seen this measured as the number of bugs reported or count of a specific process that fails.

Support SLA met: No one wants to wait a long time when they need help. Tracking support SLAs weekly gives early warning if the team is falling behind or if there is a larger issue brewing that needs immediate attention.

Onboarding cycle time: Time to value is important because attention spans are short and failure to onboard is the leading cause of customer churn. This is even more important if there is an upfront implementation needed to adopt the product (what does customer success do at a startup?).

Talk to customers: I was tempted to put CSAT on this list, but it doesn’t quite capture whether or not you are doing a good job solving your customer’s problem. If a lagging indicator is churn, then a leading indicator is simply talking to your customers regularly.