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Drilling Down Newsletter - January 2001

In this issue:

#  Best of the Best Customer Retention Links

#  Drilling Down Site: Practice What You Preach

#  New Article: "Pre-CRM" Testing Techniques -
    Determining the Potential for Marketing ROI

#  Questions from fellow Drillers: RF Techniques
     in a service / static billing business.
-----------------------------------------------------------------

Hi again Folks, Jim Novo here.  Let's do some Drillin'!

Customer Retention Links
====================

The following are must read articles on measuring and
managing customer retention.  Their "free status" on the
DM News website expires 30 days after the publication
date listed.  If you don't read them by then, you'll have to
pay $25 to read them in the DM News archives.

Note: I provide links to many more articles like these as
they become available on the Drilling Down site.  If you
don't want to miss any of them, you might want to check
this page weekly for updates to the article links:

http://www.jimnovo.com/fresharticles.htm

Note to website readers: The links in the following section will not be accessible unless you subscribe to the DM News archive.  To get these links via e-mail before they go to the paid archive, sign up for my newsletter.

* Finding Your Direct Marketing Retail Mantra
January 18, 2001   DM News
It's not just me saying this stuff, folks.  Listen to another
person talking about how tracking customer behavior
with RFM will transform your business.  Your
demographic info means so much more when you
understand the behavior associated with it.
http://www.dmnews.com/articles/2001-01-15/12670.html

* Marketing Isn't Always Sell, Sell, Sell
January 11, 2001   DM News
Nice piece on topics you don't see much - "Kiss"
programs with best customers and "Go Away" programs
with worst customers.   These ideas may seem strange
to newbies in database marketing land; they're fairly
advanced programs, but extremely profitable.    Read
the article to find out "What"; read my book to find out
"How To".
http://www.dmnews.com/articles/2001-01-08/12568.html

Dot-Coms Need to Sell, Not Brand
January 11, 2001   DM News
This one's going to give the branding guys fits, but face
it - pure dotcoms are in the direct marketing business,
whether they know it or not.  Time to fess up, kids.
http://www.dmnews.com/articles/2001-01-08/12579.html

The Basics of a List Recommendation
January 9, 2001   DM News
A good intro to list selection, for those of you thinking
about renting an online (or offline) list.  What you ask for
really matters - for best response, always ask for a
Recency select.
http://www.dmnews.com/articles/2001-01-08/12520.html


Drilling Down Site - Practice What You Preach
====================

Fortunately, the book has proven quite popular in
the first 3 months and I could afford a "real" site design.
Check it out at:

http://www.jimnovo.com

Now that the site looks a little more professional, don't
be afraid to recommend it to friends or link to any of
the content!

If you use a slow connection or an alternative browser,
you will find the same content in the "old format" at:

http://www.drilling-down.com

The old format page sizes have been reduced
(in KB) even further to facilitate very past downloads.

The content on both sites will be identical.  Each page
on the new site links to the same page at the alternative
site.  If you can afford it, this is a highly suggested way
to "keep everybody happy".  As much as 40% of my
traffic comes from overseas, where connections and
browsers may not be able to handle Style Sheets,
Graphical Navigation, and so forth.


New Article: "Pre-CRM" Testing Techniques -
Determining the Potential for Marketing ROI
====================

I've received some positive interest on the topic
of "Pre-CRM Testing" - the idea there are ways
to determine if your customer base will respond
_profitably_ to CRM initiatives.  If you do some
testing, you can prove out the potential ROI case
before you drop the big CRM bucks.  This applies
in particular to Analytical CRM, the piece that
profiles customers and generates campaigns,
professing to increase customer value.

This article provides a little background on CRM
analytics in general, and provides two simple tests
you can do to evaluate the potential of increasing
customer value using these packages.  See:

http://www.jimnovo.com/Pre-CRM.htm


Requesting Reader Feedback
======================

Newsletter readers:  Are you interested
in more coverage of pre-CRM testing in this
newsletter?  The idea is you can determine
in advance the magnitude of potential
"customer side" ROI in a CRM installation.

If you can calculate the potential lift to LifeTime
Value of installing CRM, you can use this data
to help justify CRM software costs.  Drop
me an e-mail  with your opinions or specific
questions on pre-CRM testing using
the e-mail address below (click on link):

Pre-CRM Testing

Also, for those already knee-deep into CRM,
remember I'll be speaking at the Thunder
Lizard conference in Monterey, CA March
12-14, 2001.  The topic of the piece
is "CRM Rules You Can Use"


Questions from Fellow Drillers
======================

We're skipping right to the Driller Questions this month
because both this question and my answer are quite
lengthy.  Don't want to overload you with too much info.

It's an outstanding question and between the question
and the answer, covers a lot of ground I was going
to cover in this month's newsletter anyway.

This Driller knows his stuff, using advanced database
marketing techniques on the customer acquisition side.
But in a business where the bill gets paid every month
and it's about the same (electric utility), how do you get
to the R and F (Recency and Frequency) to model
potential customer defections?  Great question, and
a pithy answer.

Remember, you can use RF profiling on _any_ behavior
not just payment related activity!  If you don't know what
we're talking about with this RF stuff, see:

http://www.jimnovo.com/RFM-tour.htm

Q.  Jim,

Ordered and read your book AFTER reading EVERY
page in your website.

Your newsletter is outstanding and you seem to be one
of the few with real life experience in database
marketing with the skills to simply explain with
pragmatic examples of how RFM and LTV should be
used.

We are a technology based Call Center company
with over 70 clients - we do a lot of the "operational"
CRM stuff you refer to - Siebel, Onyx, Kana, Webline,
........, as well as a lot of custom developed SFA
solutions and data warehousing solutions we
developed -  mostly the premise of investing to collect
enough information to do the 360 view of the customer
across communication medium (email, chat, phone,
fax) and reason for calling (campaign, sales, orders,
info, customer service....)

We have a good mix of B-B as well as B-C. We
already do a lot of the demographic modeling for
list acquisition (SIC codes, size, number of computers,
Geo ....). One thing I noticed is that we do a lot of lead
generation based upon list acquisitions along with
inbound marketing campaigns that seem to address
one shot Sales, not recurring sales. For example, we
sell and service de-regulated energy for one client -
this is sell once, then service. Since they pay every
month for the service, how do you suggest the RFM
model be used for service based sales since there
is not really an R or an F??? We still have acquisition
and retention problems, but we mainly focus on
operational efficiency through technology, not
strategic use of CRM data. I would really like to be
able to add real value based upon the data collected.

I know this is not your forte, but I was just curious
if you had any opinions using CRM data in an RFM
model when the product is basically recurring service.

A:  Thanks for the compliments on the site, book,
and newsletter.  I hope they will be helpful to you as
we try to get a firmer grasp on these subjects this
year!

It's a little tough to provide you a direct answer to
such a broad question without more details, but
in general, R and F are highly predictive of _any_
action-oriented behavior.  In a "billing / service"
business like a utility, you sometimes have to hunt
a bit harder for the action you want to model as
predictive.

For example, at Home Shopping Network, use
of the automated ordering process (touch-tone
interface to the ordering system circa 1990)
was very highly correlated with Future Intent to
Purchase.  Not exactly a traditional RF action,
to be sure, but a falling RF score on use of the
interface was very highly predictive of a
defecting customer.

In interviewing customers with falling RF scores
on the interface, we found what this really meant
to them was "the thrill is gone", meaning they
felt no urgency to order anymore so used the
interface less - the "hard" data point representing
the "soft" feelings of the customer expressed
through their behavior.  In other words, the
beginning of the end of the LifeCycle.

How'd we figure that out?  It took a long time,
and we used some advanced modeling
techniques to locate the correlation.  Once
found, it became part of the RF modeling
process and put into an "RF Grid".

(For those who haven't read the book, an
RF Grid is the most advanced (and highest
ROI) implementation of the Drilling Down
method.  It combines the Recency-Frequency
behavioral measurement with customer
LifeCycle information generated by RF
Scores over time).

If you have a website or telephone "self
service" interface, falling use of it might mean
customers are getting ready to defect, or it might
mean they are satisfied and are going to stay
long term.  There's no way to tell in advance, but
the customer behavior will "speak" and tell you
which it is.

Here's what you might be able to do:

1.  Make sure you understand all the data points
available to you

2.  Isolate "best customers" - those who signed
up and stayed signed up for the longest time, with
the least cost (variable cost to you - installation,
marketing etc, _not_ in terms of total calls to the
center).

3.  Run RF profiles over time (LifeCycle) on
each piece of "action-oriented" data  available to
you, and determine which provides the highest
correlation to best customer behavior.

For example, high RF of calls to the center
might be highly positively linked (good service
leads to better customer) or might be highly
negatively linked (billing problems create repeated
calls = mad customers who disconnect).

A falling RF score might be good - less recent
and frequent calls = higher satisfaction - or may
be bad - less recent and frequent calls = customer
"apathy" or indicates they are looking for an
alternative service.

In service businesses, you generally look for
sharp changes in behavior - a drop of 30% in
usage, and increase of 50% in calls.  These are
good targets for automation since they're quite
clear cut.

Also, as you probably know, bundling, if
available, usually results in longer term customers.
The reverse is also true - customers who reject
bundling tend to be short term customers.

And finally, source of customer is absolutely
critical in this kind of business, especially since
your "markets" may be geographically
constrained.  Since you are an electronically
driven, data-dependent acquisition shop (SIC
codes, size, number of computers, Geo ....)
you have the luxury of looking at RF by
customer acquisition source.  Good customer
retention _starts_ with proper customer
acquisition, and it should be relatively
easy to look at LTV by customer source
(even without using any RF, at a simple
level - a "quick take").

Here's what I mean.  Pick a start date, say
one year ago, and take a quick look at your
highest value customers (gross billings?)
over this time and see where (what campaign,
data element, etc) they came from.  Then look
at lowest value (disconnected?) customers
from the same start point, and see where
_they_ came from.  If there are differences,
you're on your way to finding the answer you're
looking for.  In addition, once you determine
their _is_ a difference, survey a subset of each
group and try to find the commonality in the
groups and differences between the groups.
This links the data to the emotions and
provides a backdrop for improving
acquisition technique.

Don't try to do this starting from a "micro"
level and looking up.  Start with macro ideas
(geography?) then "drill down" (couldn't resist)
a layer, then another.  When you get down to
the level where their appear to be no sizable
differences between groups anymore, you're
done.  Going any lower is just "noise".

Hope this was helpful!  If it was, and you think
the book, site and newsletter are valuable,
please consider sending me your "review"
of these tools for publication on the Drilling
Down website.

Good Luck!

Jim

-----------------------------------------------------------------
NOTE:  Got a question on database or
high ROI customer marketing?  What are
you waiting for?  Ask me!
-----------------------------------------------------------------

That's it for this month's edition of the
Drilling Down newsletter.  If you like the
newsletter, please forward it to a friend;
the subscription is free!  Subscription
instructions are at the top and bottom
of the newsletter.

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, at this address.

'Til next time, keep Drilling Down!

Jim Novo

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