Multiple, Related Customer Models
# 57: 6/2005
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
Get the Drilling Down Book!
In This Issue:
# Topics Overview
# Best Customer Retention Articles
# Using Multiple, Related Customer Models
Hi again folks, Jim Novo here.
This month, we're looking at using multiple models for the same
customer. For example, sometimes one model is best for the early
stages of the LifeCycle, and another model is better for the later
stages of the LifeCycle.
We also have a couple of great customer marketing article links.
The first is Don Peppers spinning database marketing his way; they
really do a good job of reinventing this stuff. The second
speaks to an idea many disagree with but I promise you, analytics will
someday move out of the silos and into an "analytics
department" reporting directly to the C-level.
Trust me on this one. The more heavily your company relies on
analytics for success, the more likely this "analytical
rollup" is to occur.
On to the Drillin'...
Best Customer Marketing Articles
Rules for Increasing Customer Value
June 4, 2005 InsightExec
Don Peppers expounds a bit on the Peppers and Rodgers Return on Customer (ROC)
model. Same old stuff from a databased marketing perspective, but I have
to give them credit, they do have a knack for inventing new, more understandable
ways to tell the story!
Secret to BI Success
June 14, 2005 SearchCRM.com
Back in the old days we called it the "Research and Analysis
department"; looks like today's name is "BI competency
center". No matter, it's the same idea - get analytics out of the
silos and into a single, powerful group reporting directly to C-level operations
or finance. Highly
profitable problem-solving is cross-functional; the power to find new ideas
and solutions is magnified many fold when all the analysts work together. Six
Sigma Everything, baby.
Questions from Fellow Drillers
Using Multiple, Related Customer Models
Q: We recently purchased your book
A: Thanks for that!
Q: and we are ready to start building some RFM
analysis. We are a search marketing business - we have a
large customer /prospect base. We have limited knowledge about
them and we are keen to start on the journey.
A: OK...let's see what you've got.
Q: We are hoping to extract database (approximately 25k
names) of the last 6 months records and do some RFM analysis on key
customer groups. Specifically:
TEST GROUP A - people who initially purchased one of our trial
products - we want to know what is their RFM score.
TEST GROUP B - subscribers to our "tool kit" product at $50
/ month - we want to know what is their RFM score.
Q: What kind of data are we talking about? Is it
web site visits, clicks on emails, transactional / subscription data,
all of the above?
A: Before setting up the model we have a couple of
questions we hope you can shed some light on:
1. How do we treat subscription - our business has a mix of
one off and subscription business - if someone "buys" every
month with a subscription, is that included in Recency &
Frequency? Any insight you can provide us would be great - we
found some info on this in the book but unsure given ours is a mix of
subscription and one off.
A: Well, let me start off by saying that your primary
goal is to understand the customer LifeCycle so you can use it to
increase your profits. If you can understand the LifeCycle, you
can discover the most profitable ways to acquire customers and
stimulate demand from them. Which behavioral model (RFM,
Recency alone, Latency,
Grids) is best suited for this task is something you will have to
discover. You're probably jumping the gun a bit (I'm guessing)
to hop right on to using the RFM. Before thinking about the
models, you should probably do some thinking about segmentation - what
logical groups of customers do you have, and what is likely the best
model to score each segment with?
I'll walk you through some of the thinking...
First, it is perfectly acceptable to use different models on
different segments, in fact, often more desirable. The one-off
business - if you
mean the purchase of products sequentially over time - is suitable for
RFM analysis, it's a "retail" business segment. The
most Recent and Frequent buyers of these one-off products are the most
likely to purchase another one.
As you map promotional response to RFM score, you will see that
there is a score that represents customer defection - response falls
off rapidly below this score. This score is your "trip
wire", it basically tells you that unless you get people with
this score to purchase again, you have likely lost them.
Further, if you include the original source of the customer in the
scoring process, you will find certain sources tend to create
customers with consistently high RFM scores and others tend to create
customers with consistently low RFM scores. This fact should
allow you to better balance marketing spend, shifting spend from low
score to high score customer sources.
The subscription business is something different, and probably
requires a different approach. For example, you might look at
"average subscription length" to determine a "trip
wire" for customer retention efforts. If the average
subscription length is 8 months, you know that in the eighth month of
any sub's tenure, you should be proactive in retaining them. So
for example, subscribers in their 8th month should be offered a
renewal "bundle": "Renew for another 3 months and
get 20% off". This will in effect drag a bunch of potential
8 month defectors into 11 months, where they have a better chance of
"sticking" with subscription.
Two models for two distinct segments.
But, if I understand your business model, you have a fairly typical
direct marketing of services approach - you acquire customers through
free or low priced offers (these are also the one-off products?) and
once customers gain confidence, you attempt to upgrade them (these are
the subscription products?). So what you really should be paying
attention to is the "flow" of the customer through this
expected LifeCycle, then use the models to alert you to opportunities
to increase profits along the way.
One way to do this is to deconstruct the LifeCycle of best
customers. Extract your best customers and look at the event
sequences. What series of events occurred, and what was the
timing of these events, that lead to the creation of these best
Then, use this real world LifeCycle pattern to
improve the profitability of your marketing efforts. This
approach is the basis of my LifeCycle Grid model, and it's extremely
powerful because you are using the two rules of High ROI Customer
Marketing to your highest and fullest advantage:
1. Don't spend until you have to
2. When you do spend, spend at the point of maximum impact
So, to follow through with the example above: Let's say you are
your two models on the two segments - the RFM model / one-off segment
the Average Subscription Length / subscription segment. If the
is as described above, best customers probably come in through the
one-offs, migrate to being high RFM score customers in the one-off
then convert to a subscription and end up in the subscription segment.
This conversion to subscription is clearly a "tipping point"
of some kind -
the point of maximum impact. Well then, when does this occur?
Further analysis of best customers shows that the conversion to
subscription typically occurs when a one-off customer achieves a RFM score
of 444 or higher, and the conversion to subscription takes place on
within 30 days of a customer achieving this 444 RFM score. Knowing this, what can you do?
Think about it.
First, when a customer achieves a 444 RFM score, you know this
high potential to become a best / subscription customer. So it
worth it to you to focus on these customers, do something special for
stroke them in a special way beyond the regular e-mail newsletter.
about calling them and thanking them for their business? Sending
special e-book? Adding a new software service free? Divert
low ROI marketing activities to pay for this High ROI marketing
activity. Same budget, higher profits.
Second, you know there is a clock ticking. You have 30 days to
this customer to a subscription customer. After 30 days, they
becoming less and less likely to become a subscription customer.
You now have all you need to fulfill the two rules of High ROI
1. Don't spend until you have to
2. When you do spend, spend at the point of maximum impact
You have just created a dynamic, action-oriented, custom-built,
LifeCycle-based behavioral model for a particular segment. A model
customized to your business and one that self-adjusts to customer
dynamically. What does that all mean for you?
It means that if it takes somebody a year to hit 444, that's fine, you
don't waste a lot of effort marketing subscriptions to them - they are
ready anyway. If someone hits 444 in 2 months, you are tipped
off to act
on subscription marketing in a big way. Instead of treating
the same, regardless of their behavior and potential value to the company,
you are allocating resources to customers based on a model that
to increase your profitability.
And because it is all driven by simple numbers and time stamps, you
completely automate not only the scoring and "trip wires" but the marketing
as well. Same marketing resources, deployed in a smarter, more profitable
Then you take the next segment, then the next, then the next.
you find that if a one-off buyer has not bought a subscription within
year of first one-off purchase, they are highly likely not to *ever*
subscription. Well, stop marketing subscriptions to them at the
trip wire. Market one-offs, or create a new product that would
this group. Develop a model for each segment, and automate.
Q: 2. Do you capture RFM score monthly and track - if so does
mean you need to apply a date stamp for e.g. to the score?
A: You can look at RFM scores on a sequential basis if you have a plan of
action to take advantage of that knowledge. Rising scores indicate rising
potential value to the company - these are best buyers in the making.
Falling scores indicate the beginnings of customer defection.
This is the
customer LifeCycle playing out in front of your eyes.
You could use this data to manage marketing activity at the individual
level, though it's pretty granular and would take a lot of resources;
pretty advanced stuff and in the beginning, better to stick with
However, in the aggregate, you could create reports that look at the
"delta" from month to month, basically predicting the future
value of the
business - is it rising or falling? With this, you could answer
question: Is our marketing creating customers with high future value?
approach is similar to the "delta grids" in the LifeCycle
Grid part of the
book, it's a "migration" report showing you how customers
are moving though
For example, you could create a report that answered this question:
Of all customers with a score of over 55X (rocket fuel customers) 6
ago, where are they now?
This result isn't particularly significant **by itself**.
tracked on a monthly basis over time, if you saw increasing defection in
the high end and growth in the low end, trending towards something
this (compare with above):
15% 55X (down 20 % points)
15% 4XX (down 10 % points)
20% 3XX (up 5 % points)
25% 2XX (up 10 % points)
25% 1XX (up 15 % points)
that would literally mean the future sales (potential value) of your
customers is falling; something you are doing (probably in marketing
service) is working against you. Put another way, sales in the
be lower on a per customer basis than they are today. However, if you saw retention in the
high end and defection in the low
trending towards something like this (compare with first chart above):
40% 55X (up 5 % points)
30% 4XX (up 5 % points)
10% 3XX (up 5 % points)
10% 2XX (up 5 % points)
10% 1XX (up 0 % points)
that would literally mean the potential value of your customer base is
growing - you are acquiring higher value customers and / or retaining a
higher percentage of high value customers. Sales in the future
higher on a per customer basis than they are today.
That kind of crystal ball on future sales and profit can be very valuable indeed!
That's it for this month's edition of the Drilling Down newsletter.
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'Til next time, keep Drilling Down!
- Jim Novo
Copyright 2005, The Drilling Down Project by Jim Novo. All
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