The business model for our software goes as follows...
Different levels of customers (standard, pro, enterprise) at different pricing levels with a yearly purchase. This doesn't make calculating LTV (Life Time Value) too difficult.
However, the yearly "upgrade" fee for this software (which will be valuable because the technology it works with changes) will be set at ~50% of the initial purchase price of the software. This means that a customer in year 2 will have a lower value (in revenue) than a new customer.
How can we predictably calculate (estimate) customer LTV with this many variables?
I am a believer in keeping things as simple as possible for both us and customers but this seems to be the way this particular industry prices its products.
Why ask this?
We are setting a revenue goal to hit over the next 2 years and a major aspect of monitoring this will include being able to roughly predict a customer LTV.
Thanks for the input folks. I look forward to hearing everyone thoughts.
Feel free to comment for more clarification if it is needed.
Track them as distinct cohorts over their lifetime.
In month 1:
X new standard customers at Price1
Y new pro customers at Price2
Z new enterprise customers at Price3
In month 13:
X * % upgrading * Price1 * 50%
Y * % upgrading * Price2 * 50%
Z * % upgrading * Price3 * 50%
Recommend you avoid too much 'science'. Your LTV will go up or down on two factors:
1) Loyalty: Do you really solve their problem and is your product AND your support excellent? Do they recommend your product/service?
2) Future upgrades: Ideally you add higher value features to increase revenue per user in future years.
Convince investors of the above. Don't let them nitpick your spreadsheet. (You should nitpick internally to have ready answers.)