The Web Retailing Example - Drilling Down
Newsletter # 29: January 2003
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
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In This Issue:
# Topics Overview
# New Case Study
# Free E-Mail Class: Simple Customer Models
# Best of the Best Customer Marketing Links
# Tracking the Customer LifeCycle: Recency
# Questions: Loyalty or Affinity?
Hi again folks, Jim Novo here. We've got a couple of new items -
a case study and a free e-mail class on using simple customer
models. For regular features, we have the annual explanation of
how the free "Expiring Articles" service works, the first
segmentation of the IMissAsia customer base by Recency, and a fellow
Driller who wants to know the difference between a loyalty an affinity
So, let's do some Drillin'!
New Case Study
I am constantly asked for new case studies. They are difficult to
get published because the issues I work on for companies with are often
highly confidential, competitive issues.
Jason Weaver was one of the first people to buy my book, and over
the years we have become "friends" even though we have never
met - funny how the web works, isn't it? Jason steers the list
management of a non-profit childcare organization that relies on
direct response for fund raising.
Using one of the customer scoring techniques in the book, Jason
predicted which 10% of all donors would be most likely to
contribute. And then a mailing to this group generated total
donations 192% higher than the same mailing to a control
You can check out the case study here.
And if you are of a mind and the means to, please consider donating to
Free Tutorial by E-mail:
Simple Customer Models
As you might know, I released a new version of the Drilling Down
book late last year, adding 9 Chapters covering even simpler High ROI
Customer Models than in the original book. These 9 Chapters were
taken from the over 320,000 words now up on this web site, and really
read like a "how to" class on using simple customer models
to create High ROI Customer Marketing. For this tutorial, the 9 Chapters are
delivered in 10 e-mails over a 30-day period, one e-mail every 3 days.
If you would like to read the "best of the best" on this
web site, edited into a logical, serial, "book-like" format,
send any e-mail (blank OK) to the address below after removing the red
capital letters NOSPAM from the address:
Best Customer Retention Articles
As happens every year, publishers go to sleep during December and
don't publish much of the "good stuff" because they know
people are not paying attention. There are no "Expiring
Articles" to point out to you in this newsletter.
So let me just take a minute here in the first newsletter of the year to
describe what this section is usually about. There are offline
database and direct marketing trade mags like DM News, Catalog
Success, Target Marketing, etc. that publish a ton of case studies with lots of metrics
and "how to" articles.
When they put these articles on the web, they set them up so
they "expire" and move into a paid archive after 30 days.
This section of the newsletter, and the very short "Article Links
Update" that goes out between the monthly newsletters, serves as
a reminder that certain "must read" articles are about to
expire and move into the paid archives. This gives you one last
chance to read them and copy out any stuff you need at no cost.
All is not lost for this issue, however. A slew of great stuff on other
sites has come out the past couple of weeks. You will find these
links on my "Fresh Articles" page with quality rankings and
a brief (frequently sarcastic, sometimes joyous) overview of each.
I sift out the best stuff (case studies, metrics) from all over the
web and post links to it on this page two or three times a week.
So on this round, just check out the Fresh
I don't think you will be disappointed. We'll start up the
"Expiring Articles" thing on the next cycle - if the trades
come up with anything worth reading, that is.
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
along with the Real World examples Hair Salon and B2B
Software. The previous piece on Recency is here;
this series on Recency starts here.
Recency: The Web Retailing Example
Recall from last month the owner of IMissAsia.com was pondering a falling response rate to the newsletter. But who is not responding to the newsletter? Or who is responding?
Is it new customers? Is it repeat customers? Is it "best customers"?
The owner realized there was no definition of the different kinds of customers, so the question of
"who," from a "types of customer" perspective, could not be answered.
If different types of customers were defined, the owner might be able to understand what is happening.
What the owner needs to do is not only define the customers, but also to define them relative to the newsletter.
What percent of new customers respond? What percent of "old customers" respond?
What percent of "best customers" respond?
When thinking about defining new customers, customers, best customers and so on, one concept keeps coming up, and that is "how
How long has it been since the customer last made a purchase? Surely this concept must have a direct bearing on defining customers; at some point a customer who has not purchased in a long time is no longer
really a customer, the owner thinks.
Also, at some point a customer who made a first purchase is no longer a "new customer" - they're just a customer.
A "best customer" would also need some kind of definition involving last purchase date.
For example, customer #1 who purchased $500 in the past month must be more valuable than customer #2 who purchased $500 2 years ago and has not purchased since.
It seems to the owner customer #1 is much more likely to buy again than customer #2; if this is true, customer #1 has a higher value to the business, because customer #1 has a higher likelihood to buy even more.
This "future value" makes customer #1 more valuable than customer #2.
The owner's brain was starting to hurt thinking about all these possibilities, and
it seemed like time to quit thinking and "do something" about it.
Since last purchase date seemed like the most critical element, the owner decided to classify the IMissAsia.com customers by last purchase date, and then take it from there. Perhaps the data would spark some ideas on how to think about and define customers.
The owner decided the easiest way to do this would be to put customers in monthly "buckets" of 30 days each - last purchase date 0 - 30 days ago, last purchase 31 - 60 days ago, last purchase 61 - 90 days ago, and so forth.
By creating a standard classification like this, the owner could compare the number and percentage of customers in each bucket month to month, and see what was happening to the customer base.
The owner was not quite sure what to do with this information, but knew one thing - if the percentage of customers purchasing Recently was low and the percentage not purchasing in a while was high, that could not be a good thing.
The owner completed the calculations and found the following percentages of customers in each "Last Purchase Date" bucket:
What Percentage of Customers Last
Purchased How Many Days Ago?
The owner of IMissAsia.com was devastated.
Things looked bad, the owner thought, but what did this information really mean, and what could be done with it?
It appeared as if the customer base was "sliding downhill" or aging; the largest group
are customers who have not purchased for a very long time, almost like people would buy, then give up, and fall down to the bottom of the "purchased recently" barrel.
The owner used to think of all customers as pretty much equal, they were just
and all equally likely to buy at any time.
But to see this, the customer base kind of looks like a pyramid in
time, with very few people at the top and a huge number at the bottom.
What did it mean?
Fellow Drillers, I encourage YOU to do a "30-60-90," as I call it, on your own customer base.
You will find it looks very similar in form to the one from IMissAsia.com.
Pick any activity - purchases, visits, board postings, game plays - and rank
all your customers, not just a group you choose, by how long it has been since they engaged in that activity.
You will find your very own activity "pyramid" in your customer database.
Compared with IMissAsia.com, it may be "flatter" or it may be
"taller," but you will generally see a much smaller percentage of customers in the most Recent group than you will see in the least Recent group, very often by a factor of 10.
Of course, the real question is, what can you do with this information, how can you change this state of affairs, and how much money can you make doing it?
We'll get to that issue next month, when the owner of IMissAsia.com uncovers the dirty little secret of Recency for you.
Will you be ready for it?
To read the next installment of Recency: The Web Retailing Example,
I can teach you and your staff the basics of high ROI customer
marketing using your business model and customer data, and
without using a lot of fancy software. Not ready for the expense
and resource drain of CRM? Get CRM benefits using existing
resources with Simple CRM. -------------------------------
Questions from Fellow Drillers
Q: Jim - interesting site.
A: Thanks for the kind words!
Q: How would you define the difference between an affinity
and a loyalty program.
A: Well, I'm not sure they are all that different from a
customer perspective, but one could think of the difference in this
In a loyalty program, you are going directly to the customer and
want them to be directly loyal to you. In an affinity program,
you are typically going to an *organization* the customer is already
loyal to and hoping some of that loyalty rubs off on you.
This often involves cutting a special deal for the organization's
members, and even giving the organization a piece of the profits.
Affinity deals tend to work if there is a strong relationship
between your products and the mission or make-up of the organization.
If I can imply the underlying business we are talking about from your
e-mail address, that would mean knowing that tech types make great
cell customers and going to a software association and making a deal.
Here is an example of that kind of thing, scroll down the page to see
the "Preferred Vendors":
If you think pet owners make great cell phone customers, you go to
the ASPCA and do a deal. When a non-profit is involved, affinity
is usually called cause-related marketing.
I'll say again, for affinity to work, you have to know of a logical
bond between your best customers and the group. For a product
like wireless, something that universal, affinity may be more
expensive to execute than loyalty and not provide the same bottom line
Finally, for an interesting blend of affinity and loyalty, check
out the case study on my site, which in fact in on wireless; click
It's a classic loyalty program, with an affinity twist: many of the
rewards were locally based. In this case, the affinity was
to the Philadelphia / NJ area, and we used local rewards to fulfill
and reinforce this affinity.
Hope that helps!
That's it for this month's edition of the Drilling Down newsletter.
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If you're in a tight spot on a customer marketing program or CRM
initiative (it just doesn't pay out / can't prove it makes money) and
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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
'Til next time, keep Drilling Down!
- Jim Novo
Copyright 2003, The Drilling Down Project by Jim Novo. All
rights reserved. You are free to use material from this
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