Six Operational Metrics All Startups Should Care About

1. Customer Acquisition Cost / CAC

Also known as “Cost to Acquire” (CTA), this is your total sales and marketing expenses for a specific time period, divided by the number of new customers in that time period.

Formula: Program and advertising spend + Salaries + Commissions and Bonuses + Overhead per period (month/quarter/year), divided by the number of new customers from that period.

Lower is better. This might be the single most important metric on this list, especially in the early stages of your company. If you can’t acquire a customer profitably you won’t be in business long. That said, the optimal number depends on your business: spending $100 to get a $50 customer is a bad idea, but spending $100 to get a $500 customer is like having a money-printing machine. (See Lifetime Value below) In any case, knowing this number intimately and managing things operationally to improve it is absolutely essential.

PRO TIP: Be honest in what you assign to the cost side of this number. If your CEO is spending 25% of her time doing sales, add 25% of her compensation to the top of this ratio. Your business will not benefit from unreasonable optimism.

2. Churn Rate

This is the number of customers who quit in a given period, expressed as a percentage. So if you have 100 customers and ten quit each year, your churn rate is 10%.

Formula: number of customers who quit during a given period (month/quarter/year), divided by the number of customers at the beginning of that period.

Churn rates are usually expressed in annual terms, although sometimes one has to extrapolate from shorter periods to estimate an annual number. Lower is better.

* Note for very early-stage startups. For new companies this number can be tricky to determine. Sometimes you’re not charging up front, so a customer doesn’t ‘quit’ per se, they just evaporate. In some non-subscription models, customers can pay nothing for a while and then wake up and become customers again. In those cases, you’ll need to make reasonable guesses about churn rate until you have hard numbers to work with – and you should seek to get hard numbers as quickly as possible.

PRO TIP: be honest in your estimates. In fact, take your most reasonable estimate and discount it by 50%. Your business will not benefit from unrealistic optimism, and it’s always better to outdo your forecasts than come up short. If by being conservative your model doesn’t pan out, determine the absolute minimum number that can make your model work and then move heaven and earth to prove you can hit that number reliably. Change things quickly if you can’t.

3. Lifetime Value / LTV

This is the total amount of margin generated by a given customer from the time they start to the time they leave.

Formula: Revenue paid by customers in a period, minus gross margin, divided by the number of customers

Higher is better. LTV is expressed on a customer-by-customer basis.

* Note: In certain models where different customers pay different rates, you should both 1) average all this out, and 2) break out LTV, Churn and CAC by distinct revenue tiers. You may find that certain customers are more profitable than others, and need to adjust your efforts accordingly.

4. Ratio of Lifetime Value to Customer Acquisition Cost

This is the lifetime lalue of a customer divided by the cost to acquire them

Formula: Lifetime value of a customer / the cost to acquire that customer

Higher is better. A high LTV:CAC the more value your sales and marketing efforts are delivering. You could be spending $10 to get a customer who quits after paying $10 for a month of service. In that case your LTV:CAC is 1:1. A low or negative ratio means that you’re spending all the value a customer generates to acquire them and you’ll soon be out of business.  The higher the ratio, the better quality customer your marketing efforts are delivering. LTV:CAC is also a reflection of product quality: your marketing maybe killing it, but your product or support or pricing are making them leave. Or the opposite may be true: you may be acquiring great customers, but at too high a cost. A poor showing in this category should make you look deeper on both sides of the ratio to see what’s going on.

5. Time to Payback

This is the number of months it takes to earn back your acquisition costs for a given customer.

Formula: CAC / Margin-Adjusted Monthly Revenue

Lower is better. “Margin-adjusted monthly revenue” means the amount a customer pays you minus the cost of servicing them. If you’re selling $100 product that costs you $95 to deliver, your “margin-adjusted monthly revenue” is $5. And if it cost you $20 to acquire them your time-to-payback is 4 months.

For most businesses, it should take less than a year for the revenue from a given customer to pay back its acquisition costs. Of course this presumes that a customer will stay for more than a year and that you can deliver services profitably during their lifetime. In non-subscription models, think of your time-to-payback as your sales cycle: the time from capturing a customer’s information until they make enough of a purchase to cover their acquisition cost. If initial purchases don’t cover your CAC, you should be driving repeat purchases as cheaply and quickly as possible.

6. EBITDA Percentage

This is your operational revenue minus all your operational costs, expressed as a percentage of overall revenue.

Formula: Everything you make from actual operations – everything you spend on actual operations,
divided by overall revenue from actual operations

Higher is better. This is the only formal accounting measurement on the list, and by far the one that matters the most to a startup, operationally. EBITDA takes out all the extraneous accounting-level stuff like taxes and depreciation which have little to do with your operational performance. You may still go out of business with a good EBIDTA number, but it won’t be because of how you’re running the show.

* Note for very early-stage startups. For some time out of the gate, of course, this is most likely a negative number. When planning, the sooner EBITDA moves into positive territory the better; the higher it gets over time, the better.

Working with Metrics: Goal Setting

When it comes to startup planning, these metrics should be baked in as drivers of your financial modeling. In other words, make these manual variables in your spreadsheet that link to your other numbers. Then play with them and figure out how things look under various scenarios. Once you’re operating, setting next-month or quarterly goals that are within reach should be a regular occurrence. This also gives you something against which you can peg bonuses or other incentives, or against which you can hold people accountable.

PRO TIP: never hand a goal to a manager that they haven’t bought into – unless you’re willing to accept the consequences. Unreasonable goals can actually demotivate people. If you assign a goal they don’t hit and there isn’t a consequence, your next goal will be meaningless. The best practice is to have your people help set their own goals, knowing how they will affect the entire company.

* Note for very early-stage startups. Your most important early operational goal should be to establish what these numbers look like in real life as quickly as possible. Put a stake in the ground for CAC in your first month, and then work to beat it in your second, etc.

Working with Metrics: Measuring the Rate of Change

This is the relative improvement or decline of any of your metrics over time. Operationally, regularly measuring the things that matter in the same way every month can give you important clues as to how you’re doing. Once you’ve come up with a standard way of obtaining and calculating the metrics above, roll the calculations back in time as far as you can and write them down. Every time you calculate your most recent numbers, compare them directionally to where they have been and adjust your activities accordingly.

Thanks to Hubspot for the inspiration!

Michael Sattler

With a career spent in founding and technical leadership roles with new and enterprise-level organizations, Michael Sattler is a veteran in technology strategy, operations, and product management. He’s spent decades in B2B and B2C SaaS product development, software and application design, engineering operations, new venture creation, and innovation practices.

He has scaled and managed technical teams from 2-50+ across three continents, led large-scale cross-functional program management, and founded or co-founded six companies.