A popular modern marketing valuation tool is the notion that each customer has a customer lifetime value (CLV) to the organization, i.e. the expected lifetime net present value of the customer
to the company. If you have estimates of the CLV of certain types of average customers
(e.g. the CLV of different types of banking cardholders), then statistical results
showing things like market share can be valued by using average value per customer.
See, for instance, Bauer & Hammerschmidt, (2005) for more detail on CLV.
If you know customer lifetime value (or the like), then you can use such calculations
to extend extrapolation to any variable that involves changes in the customer base.
For instance, say that you have a customer base of 1 million customers, and that a
statistical analysis forecasts a growth in this base of 3% in the next year. This
is a change situation, so you must isolate what has altered. The change is the new
3% of customers, i.e. 3% of 1 million that have been added, which is 30,000 new customers.
If the average customer lifetime value (CLV) is estimated at $10,000, the financial
value of the new customer base is 30,000 new customers * $10,000 = $300,000,000.