Strategic Insights from Calculating Lifetime Customer Value

Last week’s post looked at the calculations and mechanics of developing a Lifetime Customer Value (LCV) model. This post reviews some of the insights that can be determined from LCV calculations for better marketing, sales and business decisions.

Consider the following sample analysis using the same LCV model example from last week's post for reference.

Acquisition costs for a new customer are high and profitability in the first year is usually low or possibly negative. In the example, the ROI in the first year of acquiring a new customer is ~26% whereas the ROI for the next 4 years for those same existing customers is ~92%. More remarkable is the Sales & Marketing ROI in the acquisition year is ~42% and ~297% over the next 4 years. While this insight may be intuitively obvious in general, it is knowing exactly what your numbers are that will enable you make informed strategic decisions for improving performance.

“If you cannot measure it, you cannot improve it.” – Lord Kelvin (William Thomson)

Consider LCV per customer – in the example, total revenue over 5 years is $88,279 of which $12,000 (13.6%) is realized in the first year. LCV per customer in profit terms is $26,093 over 5 years of which $2,500 (9.6%) is realized in the first year. The point here is that many B2B companies invest a huge amount of resources, time and effort to acquire new customers, but rarely seem to show that same determination and enthusiasm for generating returns from existing customers in subsequent years. But the vast majority of the revenue potential and profitability is only realized in those subsequent years.

This raises some interesting questions:
  1. Are your marketing and sales resources aligned with generating the maximum lifetime value from your customers relative to your specific LCV data?
  2. Are these resources appropriate relative to the lifetime values? The type of marketing campaign and sales activity to acquire a new customer is quite different from marketing and selling to existing customers.
  3. Knowing your LCV revenue and profit profiles, are you using the right marketing and sales channels?
  4. In last week’s post I recommended calculating LCV by customer or market segment. You may also consider a separate dimension by product line if applicable. Having the market segment and/or product line slices of the LCV data provides more granular and specific insight for making even better and more relevant strategic decisions.
Customer retention is a significant factor in determining Lifetime Customer Value revenues and profitability – I’ll explore that in the next post.

Your comments are always welcome.
Copyright © 2009 The Marketing Mélange and Ingistics LLC. http://marketing.infocat.com

2 comments:

Unknown said...

Mike, great posts. The retention cost in your model is an interesting number. I see you have it going down over the lifetime of the customer. Might that be a bad thing?

For an example, if you are a software company and the cost of supporting your customer is going down, could that be a reflection of fewer customers on maintenance and probably not using your services and therefore not costing you anything? On the flip side, nor are they bringing you any revenue. If your costs for retention are going down dramatically over the years is that a sign that you are losing your base? A very bad thing in the software world.

Also, I think companies might want to think about the marketing costs for retaining customers especially as so many of them are trying to go back into their base as a source of revenue in tough times. I know your list of costs in the model wasn’t intended to be all inclusive, but I thought I’d remind people of that very real cost of retention.

Looking forward to the next post in this series!

Melissa

Unknown said...

Melissa, thanks for the comment - good observations. The retention cost calculation in the model is directly related to the remaining customers based on a standard $ allocation per customer. As the number of retained customers decrease, the total retention cost (budget) decreases. This reflects what commonly happens, but as you point out, it may not be what should happen. More on this in the next post.