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In This Issue:

# Topics Overview

# Best Customer Retention Articles

# Creating A Successful Analytical Culture

Topics Overview

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 little remodeling 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?  

To me, 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 on it.

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
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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. 

KPIs: 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 information.

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Marketing program designs, click here
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Creating a Successful Analytical Culture
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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 testing, etc.  The web has allowed companies to dip a toe into the acting-on-marketing-data 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 profitability.

"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 the "Business 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 data-driven business.

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 built in.

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 business unit.

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 world.  

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 your craft!

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 ROI?  

You are the prototype.  Please teach others.

Good luck in 2005!

Jim

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