Drilling Down Newsletter # 25 - October 2002 -
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
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In This Issue:
# Topics Overview
# Best of the Best Customer Marketing Links
# Tracking the Customer LifeCycle: Recency
# Questions: LTV of a Luxury Car Buyer
Hi again folks, Jim Novo here.
This month we've got the usual "best of" Customer
Marketing article links, the second installment of the series on
Recency, and a fellow Driller wondering what the LTV of a luxury car
buyer might be. The surprising thing is I knew the answer!
For some reason October always ends up as a monster issue, so let's
get right to it and do some Drillin'!
Best Customer Retention Articles
This section flags "must read" articles moving into the paid archives
of trade magazines before the next newsletter is delivered.
If you don't read these articles by the date listed, you will have to pay
the magazine to read them from the online archives.
Note to web
site visitors: These links may have expired by the time you read
can get these "must read" links e-mailed to
every 2 weeks before they expire by subscribing to the newsletter.
New Approaches to Analysis
Expires September 28, 2002 DM News
I'm all for that, but the challenge seems to be more along the lines of doing any
analysis right now. I don't really need any more acronyms, thank you, but
this article spins a couple of interesting twists on the RFM
** Improve Use of Quantitative Methods
Expires September 28, 2002 DM News
Well, I'm for that too. This article is interesting because it uncovers a
little-talked about trend: the guys in the white coats running a lot of this
data mining stuff sometimes don't know anything about business, and that is
where you get "failure". Look inside almost any CRM failure and
you will see the lack of customer knowledge was the root cause of failure.
*** How to Build a Reactivation Strategy
Expires October 8, 2002 DM News
I usually prefer to put the most effort into "before the defection"
work, but win-back or first cousin reactivation can work OK if you go after the
right people using advanced RFM.
Tracking the Customer LifeCycle:
Real World Examples
If you are new to our group and want to review the previous
LifeCycle metric - Latency - that discussion is here,
along with the Real World examples
Hair Salon and B2B
The concept of Recency as a human behavioral metric goes back to the early 1900's. A whole body of research was conducted, building on the work done by Pavlov and his famous dogs. Just before feeding time, Pavlov would ring a bell, then feed the dogs. By repeating this over and over, the dogs began to associate the ringing of the bell with being fed, to the point of salivating when the bell rang - even if there was no food present. Stimulus and response; the bell rings and the dog salivates.
Edward Lee Thorndike took this idea a step further with humans and proposed the Law of Effect - the response to any particular situation, if followed by a rewarding experience, will become the likely response to the situation. Now, you
may think to yourself "wow, how brilliant - duh" but he was the first guy to say it, so there.
J.B. Watson, building on the work of Pavlov and Thorndike, was the first to formalize the idea of Recency. He noted a man was more likely to get up from his chair when a woman entered the room if he had done so Recently; the more Recently he had done this, the more likely it was he would do it again. Apparently, he was able to get a hold of some bums who didn't stand up when a lady walked into the room for comparison. The point is, these "behaviorists", as they were called, studied human behavior and watched for patterns.
These patterns were then used to predict human behavior.
Recency found its way into the psychological literature in many ways, because it simply kept popping up on the radar screen. When studying the ability of a subject to remember a list of words, two effects were found: Primacy and Recency. When a list of words was spoken, subjects had far better luck remembering the first and last words spoken than ones in the middle. Primacy refers to words at the beginning of the list - those spoken first. Recency refers to words at the end of the list - those spoken most Recently, or last.
Why is there a Recency effect? One theory: there is simply something about human behavior and decision-making that draws us to the familiar - that which has happened to us Recently. These events are fresh in our minds; we understand all the details and implications of them, and they tend to strongly influence our behavior going forward - positively or negatively. A Recent bad experience can be just as powerful as a Recent good experience -
Here is the way I look at Recency in the context of marketing: Recency simply reflects the power of the customer
LifeCycle. As customers pass through different stages of their relationship with you their needs change, and keep changing until they don't need you any more. At this point, the LifeCycle ends and customer value accrual
(positive or negative) stops.
Note: A LifeCycle does not cover
a human lifetime, and LifeTime Value is based on
the LifeCycle, not a human lifetime. Until you know the
LifeCycle of a customer, you cannot compute LifeTime Value, because
you don't know where the "LifeTime" ends. So please
stop worrying about LifeTime Value, and concentrate on first things
first - understanding the customer LifeCycle.
But I digress; where was I? Yes... Recency.
Think of it this way. If I have just engaged in a transaction with your business, something has changed or occurred in my life that caused me to need your products or services and to reach out for them. Some event has taken place that changed my outlook or need for your business. Perhaps something I own needed to be replaced. Perhaps I got a new job and can buy more stuff. Perhaps I moved and now need
a different set of services than before.
The point is, there was a triggering event and it changed my behavior. Going forward, there is no reason to believe this change is not permanent until through my behavior I tell you things have changed again. If this event caused me to need your products or services, it is likely I will need them again and again, unless something changes. And the point where this need is greatest is the point closest to the triggering event. Right after this event, I need your products or services the most. As time goes on, I need your products or services less and less, because I either have what I need or I find substitutes - better quality for the price, a higher level of service for the price, and so on.
If the above scenario is true, then the more Recently I have engaged in a transaction with you, the more likely I am to engage in another transaction with you - relative to those who have not engaged in a transaction as Recently as I have. People who have not transacted with you for a long time are simply less likely to transact with you again, relative to those who have transacted with you Recently.
Please note the use of the word "relative". We are not talking about absolutes here; we are talking about comparisons of one customer to another. A customer who has transacted with you Recently is more likely to transact with you again
relative to a customer who has not transacted with you in some time. In fact, customers can be ranked by their Recency (number of days or weeks since the last transaction); this ranking in effect sorts all your customers by their likelihood to transact with you. Those in the top 20% of the Recency ranking are far more likely to transact with you than those in the bottom 20% of the Recency ranking.
If Recent customers are more likely to transact, then two other ideas follow:
1. The more Recent they are,
the more likely they are to respond to promotions
2. The more Recent they are,
the higher their potential value to the business
The first idea is just common sense. If a customer is are more likely to transact they are more likely to respond when contacted about a transaction - you are in effect pushing customers who are already predisposed to transact right off the fence. Like
shootin' fish in a barrel, so to speak. If you are more likely to go rock climbing than somebody else, if somebody asks both of you if you want to go rock climbing, you are a lot more likely to say yes than the other person. No science to that, just logic. This assumes, of course, you can actually tell who is more likely to go rock climbing. Oh, but you can, remember? The person who has gone rock climbing more Recently is the one more likely to go rock climbing again. This does not mean the person will go, just that they are more likely to go rock climbing
relative to the other person.
The second idea is just as logical, but perhaps a bit mysterious at first. Customer transactions normally increase customer value. A customer who is more likely to transact and more likely to respond has the potential to contribute more value to your company by transacting than a customer who is less likely to transact and respond. So it follows that the more Recent the customer relative to others, the higher potential value they have, because their likelihood to transact and contribute value is higher than others less
Recent than they are.
Got it? Good. Next time we will explore some different
ways to look at Recency, and cover some situations where you have to
look at it a bit differently - namely, in some services and long sales
cycle businesses where the context of what is "Recent" has
to be defined.
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Questions from Fellow Drillers
Jim's note: If you still don't know what RFM is
and how it can be used to drive increased profitability in almost any business,
Q: Do you happen to know approx. calculations of LTV for the
car-industry? I wonder what this might be for a person that buys
every a new car every 3 - 5 years, including service profits, etc.
A: The only published, verified study I know of on this was done by
General Motors for their Cadillac division. To quote:
"Each new customer that comes through the door of a Cadillac
dealership represents a potential LTV of more than $322,000. The
figure is a projection of the number of automobiles the customer
is likely to purchase over his or her lifetime, as well as the
services those automobiles will require over a lifetime."
Take that number and extrapolate based on the average margin on
sales and service for any other car, and you should get pretty close.
Looks to be somewhere around 6x - 8x the original purchase price,
Assuming service costs on a car are basically the same whether the
car is cheap or expensive (perhaps a bad assumption, in the case of
Jaguar, for example), there is not a direct relationship between
initial price and LTV; it's a bit more "flat" than direct. That is, for lower
priced car lines, the LTV is higher than implied by 6x-8x price; for
higher priced cars, the LTV is lower than implied by 6x-8x price.
I'm not a fan of it, but some would include the value of customers
recruited by the original customer in LTV. If you include the
value of the recruited customer in the LTV, then what is the recruited
customer worth? It's double counting the profits.
However, if you are looking at cost **to acquire** a new customer,
then you can factor recruitments in, because the sum of the original
LTV and the recruited LTV's represents the maximum you can pay for new
customers. The point is, both the original customer and the
recruited customer each
have their own LTV, which can be summed when looking at the cost to
acquire a new customer. When asking the question, "What is
the LTV of the customer?", the recruitments should not be
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That's it for this month's edition of the Drilling Down Newsletter. If you like the newsletter, please forward it to a friend - why don't you do this now while you are thinking of it? Subscription instructions are at the top and bottom of the newsletter for their convenience when subscribing.
Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them
right along to me, along with any other questions on customer Valuation,
Retention, Loyalty, and Defection right here.
'Til next time, keep Drilling Down!
- Jim Novo
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