The Value of a Customer

 

There is an old saying – “If it’s too good to be true, it probably is”  this saying along with “You get what you pay for” are truths many of us have had to learn the hard way.   With the new USPS mandated Move Update deadline rapidly approaching, many companies are looking at their options for purchasing NCOALink^® and alternative Move Update services. 

Some NCOA vendors are offering (including Listcleanup.com) an all you can eat at one price option.   Now, shopping for the cheapest price seems like a logical solution, except when you consider the value of a customer.   Given the significant increases in NCOA volumes projected by the addition of Standard Mail in the new requirements, is it not logical that some vendors are going to have challenges in delivering on advertised turn times?    If the average mail house or lettershop’s monthly mail volume is traditionally 80% Standard Mail, then volumes for many of the NCOA providers could be quadrupling over the previous First Class volumes.  

So, when your customer calls and wants to know why their mailing went out later than promised, do you think they are going to be satisfied with the answer  - our company selected the lowest cost NCOA provider and they failed to return the file to us when promised?

It's a fact, smaller companies would be out of business if they utilized data quality management processes like their bigger brothers!  My mailbox is full of Fortune 500 companies' duplicate mailings of irrelevant offers.  Even basic work like Move Update (National Change of Address) do not seem to matter to companies like Allstate Insurance, Ford Motor Company and Countrywide Mortgage (no wonder a bailout was needed).  It is time for all of us to look at our marketing database, asses data quality from even the lowest common denominator; "does that person live at that address (NCOA)?" and "does that address even exist (CASS, DPV, etc)?"  Only after this basic assesment can marketers pretend to have a chance at driving a true marketing ROI. 

At the DMA Conference in Las Vegas this week, I heard a common question.  "Why set up a Marketing Database?  We have a CRM platform."  Then I begin to ask the questions.  How long does it take to get data from IT to complete the data processing for your marketing campaigns?  How difficult is it to utilize business intelligence to develop campaign triggers or report on marketing results? Where does the marketing information reside in your CRM platform?  I often hear "by the time our business intelligence group recieves data and completes data analysis the relevance of the marketing opportunity discovered by our market research has passed!"  The reason this is happening is simple;  you have data management occuring at the enterprise level in order to run the back-end of the business, not specifically marketing data that captures the essence of the customer interaction required for integrated marketing activities. We service several Fortune 500 clients, those with a true marketing database are able to successfully execute campaign management, triggered marketing and deliver great marketing ROI.  Those of our clients that rely on enterprise level information management are only able to manage campaigns as "one-offs,"  the results often a fraction of those with a true marketing database.  It is a simple question with a simpler answer, in order to optimize marketing ROI you must have a database built for that purpose.

What times we live in  ... the cover title of DIRECT magazine proclaims "Mad Money" in August 2008 and "What Downturn?" in September 2008 as Wall Street registers its first dip below 10,000 in years just a week before the October 2008 DMA Conference.

How is it that those headlines could co-mingle?  Were the circumstances related to the DIRECT articles simply darting in and out to be replaced by an economy that arrived as quick as the season's first turn in weather?  Was data on the Dow's decline misleading?  Or were there people at Wall Street or DIRECT that simply missed the story?

As practictioners of direct marketing, and particularly as experts with data analysis, we are much better positioned than our public to make sense of these paradoxical times.  We recognize that both our headlines are true -- the economic downturn is striking, but there is still room for success if we can cull through data and identify that event, that moment in time, that each consumer returns to purchase products.  

Of course our margin for error is getting smaller - a lot smaller. To be prepared for precision marketing, we need to sharpen our data management - search for new sources, perform thorough data processing to cleanse it more thoroughly, incorporate data analysis services to elevate our knowledge about consumers and generally do all we can to optimize our marketing information.

Recognizing the challenge suggested by today's headlines, the vital ingredient is to conduct integrated marketing, to link all that data management to the point in time that clean data is relevant -- the seemingly narrower and narrowing point in time that each consumers' purchasing window is actually open.  And that, dear reader, implies that marketing must evolve to event driven marketing solutions. 

Mad Money will be on display at the DMA next week when the convention center opens its Starbucks and $4 coffee stands right in front of marketers, marketers who are staring this economy straight in the face.  But the product will be right, the prospects will be thirsty and the timing will be right.  Marketers will smell the coffee and buy that event driven solution.  Now, we just need to fix that Dow ...

It’s amazing how much money is spent launching new products these days.  One auto manufacturer recently spent over $85 million on a new launch.  Even in a fully integrated marketing campaign, you know broadcast still got the bulk of that budget.  But it seems to me that they could have given away several cars a day for a year and really generated some viral buzz! Yet along the marketing continuum, hands on experience with brands is of increasing value these days – especially in large ticket categories.   

User generated content has been touted for some time now.  And for good reason, in the right scenarios it can be very effective.  But another less noticed variation has been around since about 2001. It's called an Ad Builder. For companies who have distributed channel partners including franchisees, dealers, retailers, and so on, an ad builder solution allows them to create and distribute their own content, all while enhancing the Brand. Something most UGC can't guarantee!

Marketing has undergone a paradigm shift. New tools, new technologies, new approaches and new data have opened marketers’ eyes that there is indeed a cause and effect and predictability in customer’s actions. It is discernable in the marketing data, as Davenport notes: “Most business functions, even those, like marketing, that have historically depended on art rather than science—can be improved with sophisticated quantitative techniques.” ¹ In a paper, “CRM from ‘art to science’” Jackson² sets forth a new framework for treating marketing as a science:

Early research and methods concerning customer relationship work often focus on more intuitive approaches to customer management. Many of the initial theories, such as one to one marketing and value-based management, were less analytical in their approach. Likewise, too often companies that have implemented customer relationship management (CRM) systems have done so with an unstructured approach (art) as opposed to a structured and by-the-numbers approach (science).

 
Historically, marketing is known as a social science, rooted in psychology and sociology. However, as has been recently discovered, customer behavior is actually quite quantitatively predictive:

Marketing…has always been tough to quantify because it is rooted in psychology. But now consumer products companies can hone their market research using multiattribute utility theory–a tool for understanding and predicting consumer behaviors and decisions. Similarly, the advertising industry is adopting econometricsstatistical techniques for measuring the lift provided by different ads and promotions over time.³

It is only recently that the marketers have discovered new data mining methods which are proving to be highly robust and reliable. “Over the last 10 years, a paradigm shift has occurred in the statistical analysis of marketing data.” ⁴

At the same time, consumers themselves have undergone their own paradigm shift…from being marketed to, to taking control of what messages they hear, when they hear them and what channels of communication that companies are able to use to communicate with them.“ The consumer is deluged with messages. The average consumer sees about one million marketing messages a year-about 3,000 a day. One trip to the supermarket alone can expose you to more than 10,000 marketing messages!” ⁵Customers will no longer tolerate this mass media or mass customization approach. Customers are individuals, not transactions or demographics. "Customers are demanding that marketers communicate when and how it is convenient for them. Underlying right-time marketing are analytic and predictive capabilities that determine the optimal interaction strategies, automation and incorporation of repeatable best practices” ⁶

One of the key shifts that has occurred is the need to treat customers as individuals and not as segments or clusters: “Successful direct marketing initiatives require firms to predict the behavior of specific individuals.” ⁷

Today’s managers are very interested in predicting the future purchasing patterns of their customers. Faced with a database containing information on the frequency and timing of transactions for a list of customers, it is natural to try to make forecasts about future purchasing.These projections often range from aggregate sales trajectories (e.g., for the next 52 weeks), to individual-level conditional expectations (i.e., the best guess about a particular customer's future purchasing, given information about his past behavior). There is a great deal of interest, among marketing practitioners and academics alike, in developing models to accomplish these tasks.

A new approach to customer data analysis is needed. Customers must be analyzed and treated as individuals.Today it is possible to analyze individual customer behavior and act on it with custom marketing materials, with the right message at the right time. It is intuitively obvious: “The secret to achieving a good marketing ROI is simple: Give customers more of what they truly want and less of what they don’t.”⁹With marketing data analytics and business intelligence, we can figure out what this is and optimize for it.

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¹ Thomas H. Davenport, "Competing on Analytics," Harvard Business Review 84, no. 1 (2006).

² Tyrone W. Jackson, "CRM: From 'Art to Science'," Journal of Database Marketing & Customer Strategy Management 13, no. 1 (2005).

³ Davenport, "Competing on Analytics."

⁴ Greg M. Allenby, David G. Bakken, and Peter E. Rossi, "The HB Revolution," Marketing Research 16, no. 2 (2004).

⁵ Seth Godin, Permission Marketing (New York: Simon & Schuster, 1999).

⁶Dan Goldstein and Yuchun Lee, "The Rise of Right-Time Marketing," Journal of Database Marketing & Customer Strategy Management 12, no. 3 (2005).

⁷ Greg M. Allenby, Robert P. Leone, and Lichung Jen, "A Dynamic Model of Purchase Timing with Application to Direct Marketing," Journal of the American Statistical Association 94, no. 336 (1999).

⁸ Peter S. Fader, Bruce G. S. Hardie, and Ka Lok Lee, ""Counting Your Customers" The Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science 24, no. 2 (2005).

⁹ V. Kumar, Rajkumar Venkatesan, and Werner Reinartz, "Knowing What to Sell, When, and to Whom," Harvard Business Review 84, no. 3 (2006

Sophisticated new automated marketing systems designed by Conclusive aspire to reflect the highest form of marketing prowess—selecting and executing communications for customers as if your best sales representative was always there. 

That description (as if your best representative were there) might sound a bit "Back to the Future," but think about it—advertising and marketing departments have for years sought to present the best marketing communiciations possible to their customers, but have historically issued a relatively small number of messages and imagery in their communications in order to be realistically economic. For years we've recognized that type of communication strategy was suboptimal, if only because one or a small number of communications could never speak adequately, much less optimally, to all the members of a large customer base. To communicate most effectively with a customer base, one would have to be prepared with a nearly limitless set of communication options for each individual consumer. It would be as if [indeed] your best sales representative(s) was on the virtual showfloor greeting each customer, selecting their messages according to the very wide set of factors that might be influencing each of those customers' choices.

What might the "best" sales representatives be looking for? Well, they'd be observing each consumer as they enter the store, recognizing how they dress, what they drive, whether they had children at their side . . . they'd notice what seemed to interest each consumer and they'd align their own efforts to sell the store products that most closely matched the combination of the consumer's interest and situation (i.e. factors that might lead them away from their initial interest, such as what they wore, what they drove, and those children . . . ). Frankly this is how the best sales and marketing departments operated a century ago—they just had no scaleability to apply their "best practices" to more than a consumer or two at a time!

So advertising and marketing evolved to determine central messages that could appeal more economically to larger numbers of consumers. Hence mass marketing flourished. The trouble was, that evolution brought the messages further and further from each individual consumers' interest. Now with the emergence of deep databases and technology that position us to more elegantly overcome marketing's "scale" issues, its time to evolve back!—back toward "human" marketing that lets us conduct careful and thoughtful custom communications for  thousands upon thousands upon thousands of individual customers as if we were meeting each individually on our virtual showfloor.

What is Conclusive's plan for this marketing future? The key is structuring marketing solutions to simulate human practices—leveraging any and all knowledge known to the marketeer, building "rules" that can determine the most appropriate communications to issue each consumer based on their interactions with us, and enslaving technologies that can execute those predetermined communications automatically when customer interactions are detected. Conclusive have meaningful assets in all these areas and has begun building an as-yet-to-be-named next generation solution that captures the essence of the "best" salesperson in a scaleable marketing automation platform. 

On our website, we call the ingredients Data Management, Data Intelligence and Data Delivery. Together, it can also be called Event Driven Marketing, Knowledge-based Marketing or Interaction-based Marketing. Funny though, to me (despite all the new terms) all this sounds so old as to be new.