## Answers

Nov 13, 2017 - 12:41 PM

Jason Cohen (the founder of A Smart Bear software and WP Engine) actually wrote a post about this very topic. Here's what he says:

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Here you don’t have the budget to “spend as much as possible,” and you’re keen on getting a reasonable return on investment reasonably quickly, and you can’t just “spend to acquire the data.”

If you do have data, here’s my deep dive on cancellation rates and LTV.

But since you don’t, in my experience (and in a non-scientific survey of some of the 100 startups currently officing at the fabulously Capital Factory co-working space in Austin), a good

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Here you don’t have the budget to “spend as much as possible,” and you’re keen on getting a reasonable return on investment reasonably quickly, and you can’t just “spend to acquire the data.”

Here’s my way.

Here’s my way.

*(Tune the exact numbers below if you disagree with my assumptions, but the process should be valid for anyone interested in chasing profits with a small budget.)*

**LTV = MRR x 20**

**MRR****(****M**onthly**R**ecurring**R**evenue) is the amount you charge a customer every month. Actually, it’s the*average*amount for*all*customers, which is typically a mixture of different quantities of customers at different tiers, special add-ons, etc..**LTV**(**L**ife-**T**ime**V**alue) is the total amount of money you expect to collect from a customer over their entire tenure with your company. In general you compute this as simply “MRR x [expected months]” meaning the*average*number of months a customer sticks with you. Some customers cancel in one month, some cancel in a year, some in five years, and some never cancel! So it can be difficult to compute LTV accurately for small companies, and impossible to know for young companies (where e.g. five years hasn’t elapsed yet to see exactly how many customer stuck it out that long).If you do have data, here’s my deep dive on cancellation rates and LTV.

But since you don’t, in my experience (and in a non-scientific survey of some of the 100 startups currently officing at the fabulously Capital Factory co-working space in Austin), a good

**pre-data rule of thumb is 20 months**.**Here's the entire post from his blog (also covers the well funded startup case)**
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