The Age of Acquisition

The Age of Acquisition

This graph is beautiful. One look at the correlation between the age that a donor is acquired and their LTV is like taking that first sip of coffee in the morning. Ahhh. The r² on this relationship is over 0.85. That means that age alone accounts for 85% of the variation in the LTV. Of course, upon your second sip of coffee you might choke on this graph. Most organizations are acquiring donors well into their 60s or 70s. A donor acquired at age 50 has twice the LTV of one acquired at age 65. Think about that. Twice. The. Value. Of course, this is just one organization. Your organization might be different. What this really means for this organization is that they can spend twice as much to acquire an age 50 donor, realize more net revenue while still maintain acceptable long-term ROI ratios. If this graph isn’t making you re-think your donor acquisition approach, well, perhaps you need to wake up and smell the coffee. *** UPDATE *** This blog generated a lot of feedback. Primarily around the channel acquired. So, I re-ran the analysis to control for channel acquired. The graph below is of those donors only acquired by direct mail and excluded any donor whose first gift was $10,000 or more. Alas, not as beautiful as the one above, but still, the r² on this relationship is 0.50 and a 50-year old DM acquired donor is worth 1.76 times that a 65-year old DM acquired...
Modeling – Art vs. Science (What is a Model – Part II)

Modeling – Art vs. Science (What is a Model – Part II)

My first full-time job was as a Statistical Analyst building credit scoring models at a company that no longer exists. Now virtually all of those models are built by FICO and my old company was absorbed by them years ago. It was a great first job and one reason was because I certainly learned what it takes to get a loan or a credit card and what NOT to do if you wanted good credit. I learned that having a credit card or two is good, but having 24 credit cards that are all maxed out is bad. That’s where some of the art part of building a model comes in. I talked about the science of building a model in my last blog, but one of the exciting parts of building a model for us analysts is more of an art — finding a new variable that hasn’t been used before. For example, in building a model to tell if you’re a good credit risk, it may be bad if you have a lot of debt, or it may be a good thing because you’re a high earner and you have a loan for a house and two cars and a boat. A bigger risk is your debt ratio – you total amount of debt divided by your total amount of credit. If that’s too high and you’re maxed out, that’s bad. In fundraising, sometimes the variables that are less obvious may tell us that you are more likely to be a major donor or planned giving donor or that you’re more likely to reactivate from being a...
LTV SchmeLTV

LTV SchmeLTV

If there is one metric our industry is fixated upon, it’s LTV (long-term value). And, like so many other things, though it started out as such a good idea, it is in serious need of a tune-up. Now don’t get me started about the 7-ways to Wednesday that LTV is calculated. You’d think we would have come up with standard measurement for LTV. My problem is our industry has blindly assessed the same LTV to a donor (usual by channel acquired) while disregarding the most critical driver to LTV . . . LIFE EXPECTANCY. We did a study for one of our clients on their new donors acquired last fall. The average age for a direct mail acquired donor was 75-years old. According to life expectancy tables, a 75-year old’s life expectancy is 11 years. Compare that to a life expectancy of 30-years for a 50-year old. Without taking life expectancy into consideration and assuming all donors’ LTVs are equal, we avoid going after younger donors because they are “too expensive” to acquire than are older donors. Yet, when you calculate life expectancy into the equation, the numbers show you can actually afford to spend more acquiring younger donors because the LTV is actually much higher. If you aren’t using life expectancy when you are calculating your LTVs, you might be making big mistakes in your acquisition...