# Crystal ball fundraising: Lifetime Value

By ** **

On September 26, 2011 At 2:00 pm

Category : acquisition, database, individuals, strategy

Responses : **7 Comments**

Some time ago on the KISSmetrics blog a case study was shown on how to calculate the Lifetime Value of your customer (let’s say donors in our case). You might have seen below infographic already, but it’s such a great and clear example I want to make sure as much fundraisers as possible have seen it.

It’s not the calculation that is so interesting, because with some common sense (and a skilled data analyst) you can put something similar together yourself. What is most interesting is that this infograpic underlines the importance of using Lifetime Value (LTV) in your acquisition strategy.

In fundraising we’re always struggling with acquisition. I yet have to meet the fundraiser who says that it’s going easy and smooth year after year… It’s always difficult for everyone! Having said that, most of us are still recruiting new donors and even growing income. How come? Because we invest in the future.

Acquisition normally means large financial investment. How much do we think is reasonable to invest? How much are we willing to put in? This should not be a gut feeling, but a well thought calculation: the Lifetime Value calculation.

If we have to spend **$190** to recruit one donor, most of us will think this is not worth it. It’s bloody expensive to begin with, but what happens in the future?

By calculating our donors’ LTV we are projecting how much future income we expect to receive from them. When an average donor stays on board 12 years and has an anual value of $120, than the most simple definition calculates a Lifetime Value of **$1,440**.

**Is the $190 dollar that you have to invest for recruitment still not worth it?**

Again, it’s not about the exact numbers, it’s about how we look at investment over the longer term. Have a look at the infographic below and tell us what you think!

++ Click Image to Enlarge ++

Source: KISSmetrics marketing blog: How To Calculate Lifetime Value

Dear Reiner,

An excellent piece on LTV. I would however like to point out a couple of flaws in the approach of Kissmetrics. First of all I think the first two LTV calculations are incorrect because they leave out margin and/or retention. I also think that it’s wrong to calculate the average of three calculation varieties.

Second, I think the cost spend on a “good customer” should not be 2000 USD since this is exactly the difference in net margin, which makes the “good customer” as profitably as the “average customer”.

On our Follow That Customer website (followthatcustomer.com) you can find templates for LTV calculations under Downloads. A different approach to LTV, based on Arthur Hughes’ excellent ‘Strategic Database Marketing’ book can be found in the Follow That Customer book itself.

Kind regards,

Ed

I had a quick look at the example, and rather than saying, as Ed Sanders does, “has a couple of flaws” I say: those calculations don’t make sense.

I completely agree with the point that the article wants to make:

forecast the value of a donor on the long term, or you won’t be able to justify acquisition expenditure. But I am very skeptical about the example shown, for reasons that are too long to discuss here.

Don’t copy that method.

Thanks Luca! 🙂

@Everybody: meet Luca, the

skilled data analystI was referring to in the 2nd paragraph.@Luca, can you please the 101fundraising readers with your view on how to calculate LTV? In the comments, or perhaps in a seperate blog post?

@Everybody:

sorry for being so rude, I commented without introducing myself: I am Luca Schippa, Fundraising Analyst for Greenpeace International. Pleased to meet you!

@ Reinier:

well, now that I spoke up, I will better go all the way, and submit a new post 🙂

I will work on it in the next days.

Kind Regards

Great subject!

I am gonna dive into it now….

Good day everybody,

for clarity, I will explain here briefly why I criticized the case study.

There are basically 3 things that I find questionable:

1) It confuses weighted with unweighted averages:

the author of the case study switches from a weighted to an unweighted average. That’s not correct: you need to choose if you want work with weighted OR unweighted averages. Mixing them up can be very misleading.

2) it misapplies complex mathematical tools.

The author uses, in part of the study, a so called “classic LTV” formula that is not intuitive.

That’s because, to understand it, you need to have some knowledge of the math of series (see on Wikipedia ), the sum of infinite sequences of numbers. And, yes, the formula in itself is correct.

The problem is that it’s been applied in the wrong context, and using the wrong parameters. To cut it short, it looks like we assume that 75% is Starbuck’s client retention over 20 years, thus 24% of the customers will still be a client in 100 years from now… That’s good coffee indeed!

3) it averages together 3 different indicators, to get to the final result

This speaks for itself: you can’t compare apples to oranges, and you can’t average apples with oranges as well!

Kind Regards

I didn’t get the “traditional LTV equation”

where the r is the annual interest rate, and the churn looks like a 20-years value.

If both are annual, where is the power (series)?