Drilling Down Newsletter - May 2001 -
Overture Optimization, Recency Promo
In this issue:
# Best of the Best Customer Retention Links
# New Recency-based Tutorial on Web Site
# Optimizing Discounts Using Recency
# Practice What You Preach:
Online Advertising Effectiveness?
Tell Me About It...
# Questions from Fellow Drillers
Hi again folks, Jim Novo here. This month we've got great
customer retention article links, and a new tutorial on the web
site. We're going to take a look at discount
"laddering" using Recency, and take a brief run at some
puzzling WebTrends stats on search engine traffic. And, we'll
run through two quick questions from subscribers to the
Let's do some Drillin'!
Customer Retention Links
No "must read" expiring articles on the DM News site this
month; here are 3 great customer marketing articles you may have
missed from other sources.
Note to web
site visitors: These links may have expired by the time you read
this. You can get these "must read" links e-mailed to you
each month 2 weeks before they expire by subscribing to the newsletter.
Track: Is the Net Too Measurable?
May 1, 2001 eMarketing Magazine
Best article in a while on customer analysis. This article is a
good overview of what's going on, including comments from some of our
peers who are now using a few of the techniques described on the
Drilling Down site. I love it when they talk Recency and
Frequency (I need to get out more).
May 2, 2001 DM Review
A very simple explanation of what the 80/20 rule really means.
As I've said many times before, there is no such thing as an average
customer, and in many cases, using this metric will just get you into
trouble. This article covers simple decile analysis, the
beginnings of the work you should always do Pre-CRM; it will save you
time and money, guaranteed.
May 2, 2001 Darwin Magazine
More from Darwin - I think I'm going to like this mag. Great
story on Best Buy, and about KISS-ing CRM, which I keep trying to
hammer home on the site. These guys are not doing anything very
fancy, just the nuts & bolts of tracking behavior and looking for
"trigger points" - the subject of my book.
New Recency-based Tutorial on the Web Site
Well, I've taken your advice (thanks for the input, by the way) and
put up a tutorial that goes through a simple real-life example of how
to use one of the Drilling Down techniques. The tutorial,
called Comparing the Potential Value
of Customer Groups, demonstrates one of the 3 key
concepts vital to a successful customer retention program - attaching
future value to a customer based on their source and behavior.
The example used is Comparing the Potential Value of new customers coming
from 2 different ads, and follows the customers all the way through
the LifeCycle, LifeTime Value, and ROI issues. I think you'll
dig it; let me know if you do! See:
What are the 2 other key issues? Managing offers for maximum
response at lowest cost and setting up an "early warning
system" to flag potential customer defections. I'll talk a
little about managing offers next, and as for setting up an early
warning system to flag potential customer defections, well,
you'll have to get the book for that! See:
Optimizing Discounts Using Recency
For those who don't know what "Recency" is all about (are
there any left?), allow me a short introduction before we get to the
managing of discounts using Recency.
You will generally see response rates fall as a function of Recency
- the number of weeks or months since the last interaction with the
customer. This relationship is a very smooth curve and
quite predictable once you establish the "slope" of it for
your business. The response rate by Recency will look something
Time since contact = 1 month,
Response rate = 20%
Time since contact = 2 months,
Response rate = 10%
Time since contact = 3 months,
Response rate = 4%
Time since contact = 4 months,
Response rate = 1%
Again, the "absolute" response rates will be different
depending on the business, media used, and offer, but the
"relative" response rates will follow a decelerating curve
as shown above, that is, the less Recent the customer, the more
dramatic a drop in response rate you will get.
In terms of using this information for promotions, you will find
some point along the curve where you will get "breakeven,"
meaning the cost of the campaign will equal the benefit
generated. For example, let's say you offer a discount or gift
in your retention / lapsed customer campaign and need a response rate
of at least 4% to pay back the campaign cost.
The implication for your campaign in the Recency information above
is this: don't bother to promote to any customer who hasn't made
contact in over 3 months, because you're wasting your money; response
will be too low to pay back the cost of the campaign in the "over
3 month Recency" group of customers.
This Recency effect is very stable over time, allowing you to
predict in advance what response to a campaign will be, once you do an
"establishing" campaign to see what your response rate curve
is for any particular offer at each Recency level. With me so
far? Recency will predict response rate.
What many people don't know is if you "ladder" discounts
according to Recency, you will boost overall response while cutting
costs. Let's say you usually e-mail everybody a 10%
discount. If you were using a ladder approach for a test, it
might look like this:
Time elapsed = 1 month,
Response rate = 20%, discount
Time elapsed = 2 months,
Response rate = 10%, discount = 10%
Time elapsed = 3 months,
Response rate = 4%, discount
Time elapsed = 4 months,
Response rate = 1%, discount
Using this approach, you are allocating the most "bang for the
buck" discount-wise where you need it most - the least
Recent customers, and pulling back on some discounting where you don't
need it as much - the most Recent customers.
Now, as I said above, your response rates will vary depending on
the offer and your business, and you have to test these ladders to
find the optimum profitability for each level. The interesting
and quite useful benefit of this approach is the "automatic"
overall customer retention effect discount ladders have.
Using a ladder of this type means your promotional budget is
automatically working harder and harder to keep a customer active with
you as they drift further and further away from you. The less
Recent a customer is, the less likely they are to buy or visit again,
and by using a discount ladder you are counteracting this LifeCycle
process with stronger discounts as the defecting customer behavior
If a most Recent customer does not respond to the 5% offer, as they
get less Recent, they "automatically" get offers rising in
value, and at some point, many will take it. The customers who
run through this system without taking any offers were likely lost to
you as a customer already, and not worth the extra expense to try and
keep promoting to them. Clean, simple, easy to implement.
And if you don't have any formal customer retention program, much
better than what you're using!
Practice What You Preach:
Online Advertising Effectiveness?
Tell Me About It. (Webtrends)
Well, I got some positive feedback on the last Webtrends
article so I figured I would toss in another. I don't want
to sound like a shill for WebTrends, but I don't know how you manage a
web business without detailed log analysis. WebTrends is
not nearly as good as the system I used for the CBS/SportsLine
"points for page views" loyalty program, but then again, not
many of you probably need something with that much horsepower.
Or do you? Let me know...
Take my current little pet peeve - I'm getting ripped off on
advertising, it would seem. Or am I? Oh, not on the
response rate side, I get great response rates with Google AdWords and
GoTo. I'm talking about the quality of the visitors
generated. It seems that visitors coming from my ads might be of
a lower quality than free visitors coming directly through the
Check out this little chart, all based on visitor sessions:
|Ad Visitors |Search Visitors
Avg. Visit Length
% 1 Page
% >10 Page Visits
% > 19 minute Visits
% Downloading Book Sample
% Bookmarking Site
% Newsletter Subscribes
Hmmm, he said. Not much to make a decision on here, but the
differences are striking enough to warrant further investigation I'd
say. The page viewing activity seems to indicate the ad-driven
visitors are of higher quality (lower one page visits, higher percentage of high activity users) but the
"engagement behavior" of the search-driven visitors
(downloading, bookmarking, subscribing) is far more valuable, as these
visitors are most likely to turn into book buyers. What's really
going on here? We'll "drill down" another level next
month and try to find out.
If you'd like to see more on web log analysis
in future newsletters, let me
Questions from Fellow Drillers
Q: I have a large client with an opt-in e-mail campaign. We
found that the majority of customers who subscribe to these e-mails
have never clicked on the offers they contain, and about one third
have never even opened an e-mail. Can you direct me to any
industry best practices/tactics of dealing with these inactive
A: Well, I don't know about any "industry best practices"
on this topic for e-mail, but I can tell you what is done offline -
threaten 'em and then purge 'em. There is evidence for this
working online, as it has been done successfully by people online
wanting to maintain high list quality and responsiveness (the same
reasons it is done offline).
There also seems to be some evidence that a "hey, if you're
not going to read the e-mail, we're going to stop sending it"
threat in the subject line, when applied with a "click here to
confirm you want to keep getting this e-mail" in the body, actually
converts people who were previously inactive to active openers,
readers, and responders.
Again, this is what is seen offline. That's why you get
catalogs with the similar "This is your last catalog if you don't
buy" threat. It's a winner either way for the marketer; you
make some additional sales from dormant targets and you stop spending
effort on the ones who really don't care about your offers in the
first place. More revenue, less cost. The Drilling Down
mantra, for sure.
Q: You seem to provide practical methods for turning data into
useful customer information. Do you think the lack of this
expertise is the biggest reason why data-driven marketing is not more
A: Well, I don't know about not widely used. The $110 billion
catalog industry is built on data-driven marketing. There are
some people on the web doing a good job with it, though most of those
are catalog operations. But yes, in general people are confused
about which data is important and how to use it. There just are
not many people around with practical hands-on experience.
Dealing with data is also highly math-oriented, and a lot of people
don't feel comfortable with running numbers. These are the
reasons I wrote the book. Techniques like mine are explained in
some books, but either at too high of a level to be of practical use
or with such mind-numbing detail and math you go crazy reading
it. One day I thought to myself, Hey, you can strip this
all down into a very basic approach, and really show the average
person how to make a lot more money in customer marketing - by giving
them the "dummies version" of advanced database marketing
techniques. And to get rid of a lot of the math, I use graphical
displays of behavior so "getting the results" is much
easier. In a nutshell, that's the book.
That's it for this month's edition of the Drilling Down
newsletter. If you like the newsletter, please forward it to a
friend! Subscription instructions are at the top and bottom.
Any comments on the newsletter (it's too long, too short, topic
suggestions, etc.) please send them right along, with any other
questions on customer Valuation, Retention, Loyalty, and Defection to
'Til next time, keep Drilling Down!
Copyright 2001, The Drilling Down Project by Jim Novo. All
rights reserved. You are free to use material from this
newsletter in whole or in part as long as you include complete attribution, including live web site link and/or e-mail link.
Please tell me where and when the reference will appear.