Customer Value :
Creating a Successful Analytical Culture
# 52: 12 / 2004
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention, Loyalty, Defection
Get the Drilling Down Book!
In This Issue:
# Topics Overview
# Best Customer Retention Articles
# Creating A Successful Analytical Culture
Hi again folks, Jim Novo here.
I'm not going to get into anything too granular in this last
issue of the newsletter for the year; I'm sure your brain could use a
rest. Hope your holiday season has not been too stressful and
all is reasonably well in your life looking towards 2005. It's
shaping up to be doozy around here on all fronts, including a tiny
project at home.
Instead of crunching through the tactical stuff I thought I would
share with you a few thoughts I have had on the future of web
analytics and the analytics discipline in general. I've had a lot of discussions with people lately about the
"profile" of companies successfully harnessing their
customer data to drive profit; what are they doing, what makes it work?
culture is the real issue underlying the various "failures"
associated with CRM, BPM, web analytics, supply chain analysis, and so
forth. People tends to blame these failures on the tools or the
vendors, but often the reality is the company lacks the proper culture to
succeed using the scientific method. Since this challenge
is so widespread, I thought I'd wrap up the year with a few comments
By the way, parts of this screed were originally posted to Eric T.
Peterson's Web Analytics discussion group, you can join
that fray here. We also have a couple of great article links, one on a challenge
people continue to have difficulty with - actionable segmentation of
the customer base - and a stunning case on KPI's for supply
chain management using RFID data.
Let's do some Drillin'!
Best Customer Retention Articles
Put the Horse Before the Cart
November 21, 2004 Target Marketing
I can't describe this article any better then the lead-in, so here ya go: Effective housefile segmentation begins with sound strategy and defined goals.
The ability to market to customers with different needs, in different ways, requires what marketers call housefile segmentation.
But what you many not realize is that housefile segmentation isn't so much a technique or a tool as it is the result of goals, strategy and research coming together.
Not All Metrics are Created Equal
December 14, 2004 DM Review
Yea, it's tough this time of year to find any really interesting articles out
there. Readership drops and attentions are elsewhere; editors
"save" the good stuff for January. But buried among the year-end
reviews and 2005 predictions was this article, with a fabulous case study on
supply chain Key Performance Indicators. KPI's are central to the idea of
turning raw data into actionable
If you are a consultant, agency, or software developer with clients
needing action-oriented customer intelligence or High ROI Customer
Marketing program designs, click
Creating a Successful Analytical Culture
What is the number one characteristic shared by companies who are
successful in turning customer data into profits? The company
fosters and supports an analytical culture. Web analytics and Pay-per-Click Marketing in particular have served to teach
many people the basics of applying the scientific method to customer
data and marketing - creating
actionable reporting, tracking source to outcome, KPI's, iterative
The web has allowed companies to dip a toe into the
waters at relatively low cost and risk when compared with offline
projects. And many have seen incredible ROI.
I think web analytics could be poised in the future to serve a
greater role - teaching people / companies the optimal culture for
success using analytics,
also at relatively low cost and risk. It's going to be much
harder to drive this concept but more rewarding if as users we can make this happen, because
today's web analysts (and maybe analytical apps) could potentially be
among tomorrow's leaders in a data-based, analytics-driven business world.
For example, do you think analyzing / understanding new interactive data streams
where the interface is not a browser will be any different, in terms
of the culture required to turn interactive customer data into
profitable business actions? I don't.
Look, a "request" is a request, whether a click, IP phone
call connect, cable TV remote button push, verbal command, card swipe, RFID scan,
etc. You're still asking a computer to do something. The request has a source,
is part of a sequence (path), and has an outcome. Analysis
of these requests will face challenges and provide potential benefits
similar to those provided right now in web site analytics. This is the
beginning of analyzing the interaction of computers, people, and
process. Without a doubt, no matter what form these requests
take, there will be a "log" of some kind to be
analyzed. Usability? Conversion? ROI? These
issues are not going to go away, and companies need to develop a
culture that properly embraces analyzing and addressing them.
Companies not developing this culture will find themselves continuing
to bump along the "drowning in data" road and will never optimize
their interactive customer marketing.
As I see it, here's the "culture" issue in a nutshell: as a company, you have to want to dig
into data and really understand your business. This pre-supposes
that you (as a company) believe that understanding the guts of your business
through analytics will drive actions that increase profits. If the company doesn't
generally support this idea, there is no incentive for anyone to pursue it and the company just happily
bumps down the road.
Of course most people don't really relate to the "company", but their own division or
functional silo. So you might have manufacturing / engineering groups who live
and die through analytics but marketing is not held to the same standards and thought
processes. This is where the idea of Six Sigma Marketing comes in, it's a "bridge" of sorts
that tries to say (perhaps to the CEO and CFO), "Hey folks, if the engineers can engage
in continuous improvement through ongoing analytics, so can the Customer
Service silo and the Marketing silo and perhaps others."
At a higher conceptual level, analytical culture takes root when management makes it known they are
not afraid of failure, and want employees not to be afraid of it
either. Another way to say this is experimentation and testing are encouraged throughout the company.
Failure is a regular occurrence, and is even celebrated because
through failure, learning takes place. Show me a company
with no failures or that hides failure and I'll show you a company
that is asleep at the switch, afraid of its shadow, a company soon to
be irrelevant to the market it serves.
Hand in hand with accepting failure must be continuous
improvement. Even though failure is embraced as a learning
tool, the lesson of the failure both prevents it from happening again
and results in new ideas with a higher potential for success.
These twin ideas of embracing failure / continuous improvement are at
the heart of every business successful in using analytics to improve
"Evidence" of a company with the right bones to grow an analytical
culture is this: you see the various levels of employees working in cross-functional teams with a common problem-solving mission.
Instead of people in a silo groaning about members from other silos
being present at a problem-solving meeting, people are instead asking,
"Where is finance, where is customer service?"
The most common place "analytics" live in a company is in Finance with
Analysts", who are mostly tasked with analysis related to financial controls and producing financial reports.
If marketing or customer service was willing to expose themselves to the rigor of these
analysts, they would undoubtedly be able to improve their business areas.
But that exposure takes substantial guts and confidence in your abilities, and a "culture" that
supports a scientific process. And you can't engage in this process without analytics; success and failure need to be defined and measured.
The easiest way to encourage this culture to take root is to team a department head with a Business
Analyst familiar with the area.
Often, you find this finance person already has
insightful questions that could lead to improvement, but "never asked"
because "it's not my job". And often, to make changes in a
business today, you need IT
support of some kind. That's the basic cross-functional unit -
Finance rep, IT rep, and a department head. I would also argue that if Marketing has a seat at the table in the
strategic, "Voice of the Customer" sense (as opposed to
being relegated to Advertising, PR, and Creative), then marketing is
part of the core unit. Then you add other
disciplines as needed based on the particular problem you are trying to
solve. If the culture is flexible enough, this can turn into "Business
SWAT" where the best and brightest cross-functional teams roam through the
company as "consultants", tackling the hardest business problems, which
(surprise) are usually cross-functional in nature. And "blame" is
never on the agenda, it's about "how can we help you make it better?"
You need a
culture that is clear about this idea in order for people to expose themselves to the analytics-based scientific process.
Success and failure are defined by the analytics.
If you think about it, web site management ruled by analytics is a microcosm of this
Business SWAT set-up. You have marketing, finance
(ROI component), and technology all working together based on
the data. That's why I think there is a higher mission for the web
analytics area / people; they are building the prototype that can teach companies
how to go about measuring, managing, and maximizing a
At the highest level of this culture, managers "demand" these SWAT teams
because the success rate and business impact is so high. As
the various departments or functional silos produce wins and losses, capital (budget)
flows to where the successes are and away from the failures. When managers
see this happening, they jump on board, because they want the budget flowing their way.
This creates a natural economic supply and demand scheme with a reward system for participation
One caution: when the culture gets to this level, the analytics
group must be sanitized from the reporting hierarchy. It can't
report to finance, or marketing, or IT anymore. It has to be
completely independent, which usually means reporting directly to the
CEO. There has to be confidence in the integrity of the results
of all testing based on standards. All the little
"pools" of analytical work throughout the company must be
gathered into one.
What kind of companies do you see really engaging in this kind of culture
right now? Those that for legacy reasons have always had access to their
operational and customer data and have been using analytics for years.
For these legacy players, web analytics is a "duh" effort - they get it right out of the
box, because it's more of the same to them. But many types of
businesses have not
had this access to data before and web analytics is the first taste they are getting of the power and leverage in the scientific method.
I think this "accountability" disease we've created in web
analytics and search marketing will continue to spread and infect every
The longer-term question is, can we flip this model over, can the successful
culture of cross-functional approach and continuous improvement used in web
analytics be used to create a "duh" moment for other areas of the company? Will "best
practices" and success stories create an environment where people say to
the (web?) analytics team, "Hey, can I get some of that over here?"
In other words, will the analytical culture develop?
Methinks there is more going on with web analytics than meets the eye; it's
potentially a platform for the creation of a new business culture, a culture based on the scientific
method - Six Sigma Everything. Sure, it's awkward and maybe the web is not
meaningful enough yet to many companies. But as we thrash all this out, there is
something greater being learned here.
Right now, many CRM projects can't show ROI because nobody knows what to do
with the data, how to turn it into action that improves the business.
Sounds very much like web analytics 5 years ago...and look what we
talk about now. KPI's, turning data into action. The
analytical culture playing out.
What does this mean for the people currently involved in web
analytics? If I was a young web
analytics jockey, I would be preparing for the spread of the
analytical culture, and seriously thinking about learning some of the
tools traditionally used in offline analytics - the query stuff like
Crystal Reports, the higher end stuff like SAS, SPSS, and so on.
Search the web for "CHAID" and "CART" and see if
you like what you read about these analytical models. If this kind of stuff interests you, you are
much closer to being a business analyst than you think. And
guess what? Analysts who can both develop the business case and
create the metrics and methods for analysis - like you have to do for
a web site - are rare.
It takes a particular mind set, and that mind set is not
common. Most of the people with the right mind set go into the
hard sciences, but demand on the soft side of business (marketing,
customer service, etc.) is just beginning in our data-driven
On the hard side, (with all apologies to the real engineers out
there for the exaggeration) the drug works or it doesn't, the part
fits or it doesn't. The development of softer-side marketing and
service analytical techniques is always going to be populated with a
lot more gray area than there is on the hard side, and it takes a
special skill to conceive of and develop the metrics required.
But we should be trying to bring the same analytical rigor to the soft
side of business that the hard side has always had to deal with.
The trick is to apply that rigor without damaging the mission.
For example, the whole "fire your unprofitable customers"
thing from some factions in CRM. That's ridiculous. What
you want to do is identify them and then act appropriately, whether
that means controlling their behavior, not spending additional
resources on them, or not doing the things that create them in the
first place. That's the gray showing. You don't just hit
the "reject button" on a customer.
Customer data is customer data. It's all going to end up in
one place eventually as the analytical culture spreads, and those with
the skills to apply the scientific method across every customer data
set are going to be rare and in very high demand. Don't spend
all your spare time watching the Forensic Files on Court TV.
You're a business analyst. Get out there and learn the rest of
And, please consider doing whatever you can, whenever you can, to
spread the analytical culture within your company. If most of
what your analytics involve is "online marketing", reach out
to "offline service" or another silo and ask if you can help
them with anything. What's the call they would like to take less
of, can you use the web site to make that happen - and prove that it
worked? Can you use the web site to generate offline
You are the prototype. Please teach others.
Good luck in 2005!
That's it for this month's edition of the Drilling Down Newsletter. If you like the newsletter, please forward it to a friend - why don't you do this now while you are thinking of it? Subscription instructions are at the top and bottom of the newsletter for their convenience when subscribing.
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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