Six Sigma Marketing
Drilling Down
Newsletter
# 48: 8/2004
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
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Customer Valuation, Retention, Loyalty, Defection
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In This Issue:
# Topics Overview
# Six Sigma Marketing
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Topics Overview
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Hi again folks, Jim Novo here.
It's the end of summer and that means it's time for the annual
"try something different" issue of the newsletter, and it's
got something for absolutely everyone.
Six Sigma Marketing is a concept I've been toying with for quite a
while (Bryan
and I first discussed it a couple of years ago) and since it seems to
have leaked out into the pseudo-mainstream I figured I better attempt
to get my thoughts together on it. Below is some of my first
shot.
Six Sigma Marketing is really a "mindset" rather than any
particular tool or technique and the example below touches everything
from web metrics to the value of real-time analytics to customer
retention to why engineers are trying their hand at marketing.
By the way, this article was sparked by an exchange in the web
analytics discussion group moderated by Eric T. Peterson. If
you're into web analytics you must check out the group, it's "no
holds barred" in
there.
The core of my take on it is this: I don't think marketers should be looking for defects in "marketing programs", as some suggest.
I think Six Sigma Marketers should be looking for defects in the resulting "products" of these marketing program "plants" or
"lines" - the customers they create. Anyway, I hope you enjoy the article, and any comments on the idea of Six Sigma
Marketing are welcome, particularly from engineers.
Anyway, I hope you enjoy the article, and any comments on the idea
of Six Sigma Marketing are welcome, particularly from engineers.
Let's do some Drillin'!
Questions from Fellow Drillers
=====================
Six Sigma Marketing
Q: In the few years I've spent working in the field of Web
site analytics I've only met a very small handful of companies that are able to take immediate action based on data.
Because of this, I'm generally less excited about "real time" data than "getting the
right data in a reasonable amount of time".
But people seem to want real-time web analytics, which are of
course more expensive. Is there a case to be made for real-time,
and how would you go about justifying the additional expense?
A: There is a profit opportunity in
virtually every business for real-time analytics, but the opportunity will probably be
very different for each business. I think this idea is so important that
I'm going to spend a significant amount of time not answering this
question specifically, but using a "business model" to explain it.
I really want people
to think about the following and then relate it to their own businesses.
Engineers know about real-time, they live it. Ever seen the pictures
of a NOC
(Network Operations Center) for the telcos or the electric utilities? These engineers run the guts of
the business in real time, they are sitting
there in front of a field of screens that alert them to trouble and they
react more or less instantly, or they monitor / correct the action taken by
a robot. At a lesser scale, in every company there are IT people that walk
around with beepers that go off at all times of the day to alert them to
processes and equipment that have gone haywire. My wife was one of these
people. It's real-time monitoring and alerting, it's here and it's being
done all the time - in engineering and in IT.
It's obviously important to the business, or they wouldn't do it, because
it is pretty damn expensive. So why do they do it? Because there is a
clear idea of the value of it. If business processes go down, the
company seizes up and there are clear ramifications to this, there are
sales not booked or costs incurred that happen "in real-time". So the
monitoring is in real-time, and it works. There are amazing success stories in some other internal / operational
areas - transportation / logistics, for example, where again, the benefits
are pretty clear, because the impact is immediate. Much of manufacturing
is now done with real-time monitoring. But these are the "hard sciences",
they are internal, engineering and numbers driven and engineers understand
real-time.
So I think the question behind this question is, what does this real-time
idea look like when it is "exposed", enters the realm of the "soft
sciences" like marketing, has to be "external" and customer facing, has to
be used by people who are not engineers? People who have never even
thought about doing their job in real-time, never mind
executing in real-time?
See the average web site.
Let's take a more macro view of this, talk about the "junction of
engineering and marketing". Engineering is a real-time hard science.
Marketing is not, at least most of what people would call marketing.
Web analytics and the web in
general suffer from the problem of sitting at this engineering / marketing
junction, web sites are about engineering and marketing, both at the same time.
The challenge is, marketers don't understand what the engineers are saying and vice versa.
The engineers ask, "What do you want for reports?" The marketers say,
"What have you got?" The engineers say, "We can give you anything you
want." The marketers say, "Give me what is important." And this is how
you get stacks of web analytics reports that nobody uses for anything.
The funny thing is, there are legions of engineers and IT people who have
decided to "do something" about this problem by "learning marketing", but
there are few marketing people willing to "learn servers". What kind of
marketing are engineers and IT people willing to learn? Think about it.
The only kind of marketing that makes sense to them - direct / database
marketing. The only kind of marketing that can be measured, automated,
turned into an engineering project - complete with ROI. The implications
here are staggering - and this is also why there is so much "bad marketing"
around on the web in general. Because engineers are not good marketers, but
they have no choice, because most marketers know next to nothing about
database marketing.
For example, Pay-Per-Click bid management systems. They spider the
listings and adjust bids in real-time, optimizing for ROI. Do you
think a
marketer came up with these? Come on. Most marketers
thought search
marketing was all bull until quite recently. Engineers who knew something
about marketing, about direct marketing, came up with these systems.
They
are even managing bids by daypart now, which is a totally fantastic idea,
because (as direct marketers know) the audience changes throughout the
day. And whose idea
was this? A marketer? No. Engineers, as truly
"scientific method" types, discovered through testing that
you could get higher ROI managing bids by daypart. They were basically
"correcting defects" in the system from an engineering
perspective. This process of reducing defects has been
formalized and at the highest order is generally known as "Six
Sigma".
The challenge of real-time for marketing is to prove the value of it,
as the engineers do every day when their "alert" beepers go
off.
In the case of marketing, most of the value comes from opportunity
costs that on the surface can be difficult to measure. The defection
of a customer, for example. When did it happen? How do we know when
a customer is no longer a customer? How can we slow or prevent the
defection of a customer?
Does your company measure defection rates? Or are all customers
customers "forever", unless they call you up and say "I think you
suck, I'm no longer a customer." You have all heard the stats on the
value of increasing customer retention - costs 5x more to acquire a
customer that keep one, a 5% increase in best customer retention drops
a 25% increase to the bottom line, etc. But in the vast majority of
companies, nobody in marketing does anything about retention.
They don't even measure customer defection.
That's because customer defection is a database marketing concept,
and most marketers know next to nothing about database marketing.
The fact is customer defection is largely caused by "defects" in the
way the customer was "manufactured" in the first place, or "defects"
in the way they were "maintained". And I know more engineers that
understand these concepts than I do marketers who understand them.
And it's because, literally, marketers don't think like engineers.
If
you explain opportunity costs, customer defection metrics, and the
potential for increased profits to an engineer, they understand it
immediately. Because it's about numbers, ROI. Measurable.
It's
working or it isn't. It's database marketing, it has a start and a finish.
Alpha and Omega.
In other words, database marketing is "engineer's
marketing", it's Six Sigma Marketing, and you can approach most
database marketing challenges the same way engineers approach their
Six Sigma challenges.
The real-time challenge for "soft science" or "customer-facing" business
units, and marketing in particular, is to understand the concept of
"opportunity cost", the costs that are not so obvious, lost profits that
occur in the future because you didn't take action today. Engineers
understand these costs, because they know that a defect today means lost
revenue or increased cost tomorrow.
In other words, these soft science business units have to learn how to
manufacture customers correctly, with a low error rate. And
they have to learn how to spot maintenance problems with the
customer remotely, to anticipate defects in customer value.
Opportunity cost is like the opposite of conversion rate, it's measuring
what did not happen. What percent of visitors who bought more than 90
days ago did not buy in the past 30 days? Why? These customers must
have been manufactured incorrectly, they must be defective, because there is this other
group of
customers, manufactured by a different plant (campaign), who bought more
than 90 days ago and are still buying now, as Recently as yesterday.
So, what are you going to do about these defective customers?
The reality is it's probably too late to do anything profitable about
them, because you weren't measuring these defects, so you couldn't manage
them. You don't have "trip
wires" or "alerts" set up to "page you" when a
"batch" of defective customers is discovered, you're not even looking
at any customer defection metrics. So then two things happen:
1. You probably continued to manufacture defective customers for some time
longer than you should have, beyond when this "customer manufacturing line" (campaign or
product) should have been shut down. This is a waste of resources, time
and money. Opportunity cost. Money lost by failing to allocate
marketing
resources to the best use, to a campaign or product that manufactures
higher quality customers.
2. It's too late to take action to "repair" the defective customers with a
follow-up campaign or action that attempts to correct their flaw.
These
defective customers are now in the distribution chain, where they will
remain defects and contribute no profit or even negative profit to the
company in the
future. Opportunity cost. Money lost by not doing something
about the defects in a timely way. In customer marketing, what you do today has consequences for the
future value of the customer. Every contact can either increase
or decrease future customer value.
Now, if you have lots of customers, products, and campaigns, you can't
possibly keep track of all of this, all the potential defects that
might arise. So you need a real-time system that
alerts you to take action, the "trip wire". It scans for customers acting
in defective ways, so the line that is generating these defective
customers can be fixed, and the capital reallocated to another better
use - a campaign or process modification that over time reliably generates Six Sigma quality,
low defect customers.
But here's the difference between Six Sigma for Engineering and Six
Sigma for Marketing, and why database marketing concepts can be generally difficult for people to understand. In manufacturing, IT,
or any of the hard sciences, real-time defect alerts tell you something
is happening now, and you need to act now. A robot sees a
defect and stops the line immediately. Then the engineers try to find out why this defect happened and generally reduce these
defects over time.
Unlike the engineers, in marketing and the soft, customer-facing sciences (customer service, contact centers agent desks, sales
personnel, etc.) the transactions with customers occurring now create defective customer value
in the future. When a customer has a bad experience now, this result does not affect
customer value now, the "value defect" occurs in the future, as
the customer reduces business with the company or defects.
So unlike the engineers, you need to act now to reduce defects
in the future. This is because the value of a customer, external
or internal, is a function of customer behavior over time, and what you do
now affects the value of the customer in the future.
When business is all basically conducted face to face, this is not an
issue, you deal with it "in real-time". But when you're talking about
doing business remotely, you're talking about web sites and self-service and the like, you don't really know what is happening,
and the customer defects play out over time. And you don't know about
them because in many, many cases, nothing happens - and that is the point. You have to measure what
did not happen to see these customer value defects, and the majority of people, including engineers, are not used
to this idea. They measure what happens, not what doesn't happen.
"Doesn't happen" is generally good in the hard sciences (as in "width not outside acceptable range"), but "doesn't happen" is
generally bad on the soft side, because business is about things
happening - sales, visits, downloads, etc.
So it is one thing to monitor the initial conversion of 30 simultaneous campaigns in real-time, and make adjustments on the fly.
Some people do this, certainly in pay-per-click, either in person or using robots. But this activity is happening
now, it has value now, and you are doing something about it
now; it's manufacturing, it's engineering, that's "easier", it is a process that is very well
understood and easy to prove the value of because defect discovery and correction occurs "in synch".
But what if I was to tell you that the pay-per-click campaign set you
are optimizing
right now is creating customers with very low value in the
future. Further, the keywords with the highest conversion rate generated customers
with the very lowest or even negative value in the future.
In other words, these keywords were creating defective customers,
relative to other keywords. Would that knowledge affect what you were doing
now with optimizing the campaigns? Sure it would.
And how did I know these keywords were creating customers with low
value in the future? Because I just got "paged" by the real-time
analytics
application, telling me that the customers generated by the keywords in
question for the past 60 days had an abnormally low "likely to buy" score
relative to the rest of the customer base. These customers are quite
unlikely to buy again, they should not be manufactured any more.
They're defective.
And what would you do? You'd immediately (as in right now) lower or kill
those bids and use the money to raise bids elsewhere, right now.
Because
not to do it now would be a waste of time and money. The marketing
capital should be reallocated to a higher and better use - keywords that
generate customers with higher "likely to buy" scores.
The longer you wait, the more money that is lost. If you found this out 60
days later, when you ran "current time" analytics and found out they in
fact had not bought again, you have wasted a ton of money.
It's obvious, right? And why is it obvious?
Because the real-time analytics and metrics have turned the future into
now for you, and you can
act now, even though the action has value in the future. And as you allocated the budget money away from these keywords and
towards keywords that create customers without these defects, you
would be basically looking at your marketing through a set of Six
Sigma glasses. You are reducing defects that you know are going
to hurt you in the future. That's Six Sigma Marketing. And it is also real value creation by
a marketing department using real-time analytics. It's the kind
of value creation that can be precisely measured, and used to justify
the expense of the real-time analytics. Just like the engineers
do.
Now think of programs like this throughout the company, each handling some kind of
important customer-facing issue, each
being optimized in the same way - to maximize customer value while at the
same time driving the highest and best use of capital.
Now, do you have to use real-time analytics to be a Six Sigma
Marketer? Not at all; you don't have to use a pager to alert you
and your business doesn't even have to be online. After all,
this general approach to managing customer value was developed offline
decades ago using the telephone and direct mail. How "fast" defect detection and correction need to happen
depends on two things: the natural rhythm and speed of the business
area, and the financial stakes involved with the defect. The
faster the pace of the business and the higher the financial stakes
surrounding the defect, the more money you will lose by not correcting
defects in a timely way. It's probably a good idea to simply
start with finding the defects in your customers. You can worry
about "speed" and all the rest of it when you have something
tangible to work with.
Take the first step to becoming a Six Sigma Marketer. Measure
your customer defects, and get committed to reducing defective customer-facing
transactions. Your objective is to simultaneously increase customer
value and reallocate capital to highest and best use.
That's a concept every CFO understands.
Jim
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needing action-oriented customer intelligence or High ROI Customer
Marketing program designs, click
here
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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 Defection right here.
'Til next time, keep Drilling Down!
- Jim Novo
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