September 11, 2006

Four Questions With David Raab, President, Client X Client

This week, I am pleased to have David Raab take part in our "Four Questions" segment on MineThatData.

David is President of Client X Client, a company that provides technology, analytics and services designed to achieve optimum yield per customer. David is one of the leading minds in the Database Marketing field, with nearly one hundred contributions to DMNews.

Let's begin the interview.

Question #1: You are one of the most respected analytical minds in the field of Database Marketing, having consulted with many great brands. Now you are President of Client X Client. What are some of the new challenges you now experience?

The industry has changed greatly since Database Marketing first became identified as a discipline fifteen or twenty years ago. Back then, we spent a lot of time explaining the basic concepts of how to build and use a marketing database, particularly when talking to people outside of traditional direct marketing. Today, the basic premise--that assembling information about individual customers lets you build more profitable relationships--is conventional wisdom across many industries. Similarly, in the early days, people were just starting to develop software to implement Database Marketing principles, so much of my work involved examining the different products and helping people to understand which capabilities were truly important. Today, the core functions of a good customer management system are widely understood and many marketers have hands-on experience with them. So, although I still spend a great deal of time looking at software and talking to vendors, the real challenge is helping clients make the best use of system capabilities. This means dealing more with marketing and business management issues, and less with technical concerns.

Question #2: Your company links the customer experience to actual business results via something called "The Customer Experience Matrix". Can you explain how this product helps businesses understand how customers behave?

The key point about the Customer Experience Matrix is that it gives companies a comprehensive overview of how they are treating their customers, across all channels and all stages of the customer life cycle. That's much harder than it sounds, because most companies are organized into functional groups responsible for a particular type of activity--say acquisition or customer service--and often further divide responsibility by having separate groups for each channel such as Web or direct mail. Each group does the best job it can, but without understanding its overall impact on the customer, all it can measure are internal metrics like response rate or cost per call handled. The Customer Experience Matrix uses all the database technology we've built in the past two decades to finally tie together all the interactions so companies can see how a change in one activity in one channel has an impact on later activities in other channels. The concrete example I always use is how a change in customer service levels has an impact on future sales--something that Dell Computer has recently illustrated in real life. What the Matrix does specifically is to measure the change in each customer's future value after a given type of interaction, so the company can assess whether the net impact of the interaction is positive or negative. But, to tell the truth, we're finding that companies get excited about the Matrix even without the detailed financial analysis because it lets them see, for the first time in a single place, the messages and business rules they're delivering across all their different interaction points. This lets them spot inconsistencies and opportunities that would otherwise remain buried.

Question #3: Put on your "consumer" hat. Are there companies that you believe do a really good job of building a relationship with you, personally, and why do you believe they do a good job?

Interesting question. Marketing is all about segmentation, and I happen to fall into the segment of consumers who are extremely utilitarian in most business relationships. This means I have almost no interest in building a "relationship" with most companies, at least in the conventional sense of an emotional commitment that would lead me to go out of my way to use one company's products over another's. There have been particular companies I have been very enthusiastic about at particular times--I can think of specific airlines, telephone companies and auto manufacturers--but only because they had products that happened to meet my needs very well at a particular moment. There are other companies in those same industries that have treated me so poorly I will never do business with them again unless I have no choice. But in both kinds of situations what drove my "loyalty" was the products themselves, not any type of personalized relationship. It's theoretically possible that I could enter into a "learning relationship" with a company that would know enough about me to make them eaiser to do business with than a competitor, but in practice I haven't seen anyone offer service that's customized enough to make much of a difference. In other words, for me at least, a company is only as good as its last interaction: while I'll cut an incumbent vendor some slack just to avoid the effort of making a change, there is very little else to hold me in place.

Question #4: In what ways would you say that consumers have benefited from advances in analytics and CRM software?

Notwithstanding my previous answer, there are consumers unlike me who do value personalized business relationships, and they have benefited from the analytic and CRM software that lets companies develop and maintain such relationships with them. But I think the more common value is the ability of companies to use such software to predict consumer actions and needs, and to make offers that are tailored to them. I have certainly appreciated and responded to product offers that reached me at appropriate moments, and many studies have shown the value of targeting based on detailed analysis of customer activities. Yet the biggest benefit of all, I think, is one that has become so common we almost take it for granted: we expect companies to have CRM systems in place that make our transaction history and account information instantly accessible should we need them for some form of service such as tracking a package or changing a reservation. Perhaps the best evidence for that expectation is the annoyance we feel when a company fails to meet it. The fact that we actually feel annoyed--instead of just surprised--shows it's a real consumer benefit. Again, this comes down to the point that value is based on operational performance, not better marketing or emotional relationships.

And that concludes our interview with David Raab. Thanks, David, for providing us with great comments and insights!


  1. Anonymous7:41 AM

    Kevin . . .

    A question for David:

    You have made some very interesting and forward-looking observations about database marketing's evolution. One comment is particularly evocative and leads me to a question:

    "The Customer Experience Matrix uses all the database technology we've built in the past two decades to finally tie together all the interactions so companies can see how a change in one activity in one channel has an impact on later activities in other channels."

    My question:

    Are we, David, entering a period of database integration that allows us to build structures similar to "automatons" or "stick men" whereby we push or pull on one element and automatically see the outcome flow before our eyes and see the true effect on all other elements in the business, in effect a Universal Sextant or something like a multichannel Global Positioning Satellite system that details and precisely pinpoints financial outcomes, optimal mailing levels, ecommerce saturations, and all other marketing, operational and financial variables?

    If we are reaching this point, we are nearing the most revolutionary and evolutionary state for all of the multichannel milieu. If such elegant models can be reliably built across all channels, we will have reached near-optimization of our formulaic-oriented "go-to-market" business model, and financial success and market dominance will rest with those smart enough to invest in such structures. Do you see this very beneficial, but shape-changing, evolution of the database technologies emerging soon?

    Thank you, David, for your most intriguing thoughts; thank you, Kevin, for making them possible to the wider audience.

  2. Anonymous10:17 AM

    Jeff et al . . .

    Thanks for a very enlightening series of comments. Wonderful thoughts!

    Perhaps my singular concern for the feasibility of this evolution is the incapability and incapacity of many of the catalog owners and CEOs, as well as some of the web-based heads, to understand and embrace such data advances. Over my many years, I have seen customer retention percentages at five years go from 16% retention (84% attrition) to 16% retention; similarly, I have watched the percentage of direct marketing companies that can perform something so basic as full RFM analyses rocket from the 10% percent level to a now whopping 10% level. Nothing changes in the outcome results. Two of our greatest hurdles are provincialism and apathy. Is it, perhaps, still too easy to make an acceptable profit? Does it have to get difficult in order to stimulate customer conservation? Or are the solutions, indeed, more bother than the potential economic benefit?

    If the advances you and David describe can be communicated (and that means visually) to CEOs, owners and centers of influence (investment bankers and private equity groups)perhaps a few large organizations will finally react and a critical mass will develop that--at long last-overcomes the breathtaking waste we create daily in this industry due to apalling inefficiency.

    Or, perhaps I have been tilting at windmills too long.

  3. Anonymous6:12 PM

    Don and Jeff,

    We certainly won’t reach multi-channel nirvana, where we can manage based on the precise long-term ramifications of every company decision, overnight. But we can already take some small steps in that direction, and those steps will have positive results which will encourage larger commitments.

    Usually I talk about two preconditions for customer experience optimization: a modeling framework to make predictions, and an operational framework to execute decisions. But, based on Don’s comment, I think I’ll add a third: a management framework that lets companies understand the value of the optimization effort and how it works. Without that high-level understanding, they will never make the investment in the other frameworks.

    If I can outdo Jeff in shamelessness by plugging my own firm, ClientXClient does offer a free sample of what a Customer Experience Matrix system might look like. I’d be happy to send a copy to anyone who wants it—just email me at Don, you’ll be pleased to learn that one of things provides is a set of sliders that lets people examine the impact across their business of changing selected variables such as the proportion of customers from source vs. another. Although it’s just a simplistic example, we’re hoping it will help senior managers to understand what’s possible and why they should consider building something similar for their own businesses.

  4. Anonymous9:50 PM

    It's neat that technology allows folks to have a discussion like this.

    It has been my experience that an awful lot of analytical solutions provide incremental benefits that are very hard to separate from ordinary business metrics.

    For instance, assume that a direct-to-consumer business has an annual retention rate of 50%. Analytic solutions may increase retention by one or two percentage points. Combine that change with the +/- three point change that routinely happens in our businesses, and it becomes nearly impossible, without elegant testing, to separate the benefit of the analytic solution. It is especially hard to explain it to the CFO, or to the Merchant, who justifiably wants to take credit for improvements in the business.

    I have had much more success implementing change by verbally communicating what analytics tell us about our business than by actually implementing analytic solutions.

  5. Anonymous4:33 AM

    David, Kevin, Jeff . . .

    Thank you for these interesting insights.

    Kevin, you have revealed one of the primary values of consulting: Facilitating understanding of problems by the owners/senior decision makers.

    Personally, I don't "Do Stuff." What I do is to reveal problems and opportunities and attempt to translate that into the language of potential future business valuation that owners will understand, which is the only thing that will create intentional action.

    What I need is an evaluative tool that creates -- again, in a visual and financial manner -- the potential scenarios and cost/benefit analyses for the various options of any solution approach. I have developed for my use a Universal Suite of Multichannel Marketing Metrics, but it doesn't go far enough and it is not easily applied across all companies.

    As an example, if an effort is made to improve customer retention by 2 points, and that effort requires 24 months and $1 million, what are the impacts on the 1, 2 and 3 year earnings, the operational ratios, staffing, circulation, as well as on the overall business valuation.

    Some of these model formulator software programs exist in the investment banking and the private equity investment world, but they have not been extended into our highly specialized niche.

    You are all doing pioneering work and it is good! Considering all of the employees and extended families that will benefit from this work, it's noble!

    Thanks . . .

  6. All,

    I was also struck by Don’s comment that it might be “still too easy to make an acceptable profit”, but mostly because I felt very few business owners would agree. But, on reflection, I do see the point: even though people work hard, they are mostly doing small variations on what they’ve done before. It usually takes a crisis before companies or individuals are willing to make major changes in how they operate.

    We’re dealing here with fundamental constants in human nature and organizational behavior. Technology can make changes easier and make it easier to show the value of those changes in advance. But it can’t make people who are comfortable become willing to try something new. This is why every study of innovation ends up concluding that a senior “champion” is necessary for success. All we can do as consultants and technologists is to help those champions succeed by giving them sound ideas and good tools to execute them. We can’t create the champions in the first place.

    I don’t find this frustrating because there are always some champions somewhere who are eager to innovate. They and their companies are the leaders who try new things and prove they work. They grow and prosper as a result, and ultimately everyone else in their industry feels enough pain to make similar changes or go out of business. Then those of us who have been developing and preaching about new ideas will be ready to help them, and they’ll be happy to see us.

    To get back to a more practical level: business modeling isn’t that hard. I’m sure Don or any of us can capture the key dynamics of a business on the back of an envelope, and can build a model detailed enough for most purposes in a few hours in Excel. There definitely is software to do more sophisticated types of modeling—for example, specialized circulation models for publishers, and more generic simulation models for other types of businesses. One product I find particularly intriguing is DecisionPower (, which does SimCity-type “agent based modeling” of interactions between a company and its customers. (I have no business relationship with DecisionPower and haven’t evaluated it in depth.) It’s true that building sophisticated models takes a lot of effort, but I really wonder how many business managers would be convinced by a sophisticated model if they are not already predisposed to accept the results. We all know how easy it is to make numbers come out however you want. I’d guess that in most cases, business models are used to support a course of action that someone has already decided make sense. And in those cases, a reasonable-but-simple model will probably be just as useful as something much more complicated.

    - David


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