Beyond the lipstick of messaging

PvT: And from your point-of-view, how will marketing’s contribution to the organization evolve?

MM: Marketing is really about what I’ll now call engagement with customers and stakeholders that affect the purchase, consideration, trial, and ultimately loyalty and advocacy of customers.

Marketing remains core, fundamental to the value and purpose of a company. However, marketing must evolve beyond messaging—you know the old saw, lipstick on pigs.

Unfortunately, most senior marketing executives lack fundamental skill sets to innovate new services, especially digitally provisioned services.

Most senior marketing executives lack – are utterly bereft of what I call IT service management chops. And yet, the marketing executives that will have the big wins over this next 5 or 10 years will essentially be senior IT execs and CIOs that understand the concept of customer-making, the primacy of brands as a way of engaging customers in the value proposition, and more specifically, the provisioning of online interactive services as a core innovation to the customer-making process.

That’s why most chief marketing officers of major companies today will simply be out of the game in 3 to 5 years. They will have to retire out or do other sorts of boutique consulting because fundamentally they are suited up for hockey when everyone else is doing ballet.

Not good news, huh?

PvT: No, not at all. Not at all, and I’m sure most marketers would not want to hear that, so.

MM: Well, as I mentioned it before, William Gibson, has this great aphorism: The future arrives unevenly distributed, i.e., some people get it, some people don’t, those that don’t end up feeling a lot of pain and hurt as a function of being laggard on innovation-adoption curve and, more specifically, the future that arrived yesterday. We need to play a little catch.

Customer-making mindset, plus systems

PvT: Okay. So what do you consider as the core elements of a tightly integrated marketing model? And that’s sort of a loaded question…

MM: It sure is. Well, not to belabor the points that I’ve already made. First, you need to have a customer-making mindset; you must integrate the systems and compensation of pre-sales and post-sales to customer-making process benchmarks.

Second, you need to have the analytic discipline and rigor to be able to identify your ideal customers and predict lifetime or long-term value. You must understand your customer.

Third, you need to develop the operational capability of listening: mood of the market, voice of the customer, and patterns of engagement.

Fourth, you to put into place agile methodologies for the development of content and services used promotional reach and engagement.

Now some companies people start with the social media and social networks; they start with a voice with which some customer might connect and begin a dialog.

Social media enables a firm to initiate emotional connection with its customers, and get hints about what’s really going on, and then using those intuitions and soft perceptions drive a broad-spectrum analytic practice and develop true rigor about who is your customer.

So, you know, it can mean a Yin and Yang kind of thing where they feed on each other. It should result in a positive feedback loop: listening begats better content and services that in turn produces “earned media” in the form of praise and recommendations in the Web 2.0 mediaspace, that you inform above the line mass market creative strategies, and so on.

So to unpack your loaded question, the fundament challenge confronting the marketing executive today entails building operational capabilities within the context of an operational marketing platform—a business process-management platform for marketing-related activities.

Unlike marketing automation tools for “doing the marketing process”, the operational marketing platform must also support the rapid, agile development and provisioning new interactive services—essential software applications, service mash-ups, and widgets.

With good listening tools and process, combined with collaboration and scheduling systems, the operational marketing platform becomes an innovation-services platform

That idea nicely summarizes how innovation and marketing have converged in terms of a core competency, vis-a-vie this platform.

Innovation and marketing. All else is cost!

PvT: In your opinion, what operational changes can organizations make to get a better picture of that customer? You’ve addressed several big topics. However, many organizations have very siloed systems, making it difficult to access needed data. For example, a retail customer may be quite different from an online customer, and rather than integrating that data they keep that data separate, in separate databases. What are some of the things that you think organizations can do, or should do, to address the issue?

MM: Well, let me go back to what I call the axiomatic assumption of the commercial enterprise, and then from that examine some of the propositions or key premise of commercial activity.

Peter Drucker, God bless him, said, ‘The firm has no other purpose than to find and serve customers. Only 2 things add value: innovation and marketing. All else is cost.’

So there you have a quintessential operating principle. There is no other purpose than to find and serve customers. That’s what I call a customer-making process.

So you can put Band-Aids on cancer but if, fundamentally, you do not have a mindset of customer-making, which is, ‘I am building systems, processes, and accountabilities for managing the process of attracting, serving, and keeping customers life, then everything kinds gets muddled, confusing, and a big hairball of politics and turf.

Customer benefit

First, we like to put it into more simple terms: “How does the customer benefit?

Whatever operational or tactical changes that a firm wants to consider, we recommend that that they ‘solve backward’ from customer-making as an integrated analysis-driven process.

Now, there are many companies that aspire to that, but for lack of leadership and the inertia of their business, they encounter a lot of difficulty. We believe that they simply need a better, more fun way of innovating new operational capabilities—yep, from the bottom up with those folks that actually know first-hand what’s going on.

Second, if you accept that innovation and marketing represent the two primary drivers of wealth creation and value, it then follows that customers 30 years or younger will no longer experience the world as online and offline, it’s just the world.

There’s no first life and second life, it’s just life. And as a function of that they start to interact with customers with what I call a digital third hand.

Digital third hands

Now a digital third hand is quite literally how they have developed the cognitive ability and the muscle-memory reflex of interacting in a purely digital world.

In our digital world, we experience an appetite for interacting with brand and communities of brand users that have fundamentally altered marketing and innovation—new business requirements that marketing and innovation must now satisfy.

One, consumers that are 30 years and younger today, for the most part are no longer represent singular economic actors, rather, they represent a clique, a crew, or a pod of 4 or 8 people – their best friends with whom the text message each other 50 times a day!

These younger adults tend to select their best friends not just on shared values and sense of humor; rather on the basis of cognitive specialties—what John Garner talks about as multiple intelligences and cognitive-skill specialties—that offset and complement others in the crew or pod.

This means that somebody in the group will be really good with data, arithmetic, and logic. Somebody else will have aesthetic or design sense—fashion, design, and color. Another person will be really good with interpersonal dynamics, empathy, and support.

This means that marketers must give up the conceit of marketing to an individual demo-psychographic profile.

Rather, we must learn how to market to a pod or crew with collective IQ many times greater than any one individual consumer.

This means that the collective unit will detect any hint of bullshit, manipulation, coercion, or underhandedness, and heap immediate retribution on offenders: the highest form of which is willful apathy and deliberate dis-engagement. Wow. Try marketing in that!

Some marketer will also suffer a public reprimand in front of millions of consumers on YouTube and the mainstream pick-up of outrageous videos.

So, as a function of digital third-handed customers, who then through instant messaging and SMS, and other kinds of presencing thing, be it Twitter or whatever, not only must you market to the pod, but you must market to the cognitive diversity that defines that pod.

Requirement for multimodal content

So that means that you need multimodal content things like Podcasts, and webinars, and newsletters, and interactive calculators if there’s a return on investment.

You need to do customer interviews so people can associate into the narrative, into the journey of customer-making.

So marketing, on one hand, becomes much more integrated, it becomes much more multi-channel and multi-modal in terms of the cognitive styles it must satisfy.

The third thing that happens is that these pods start to form larger networks – federal networks, and out of this they start to organize themselves in terms of movements or de facto unions.

And oftentimes a c-captain – a community captain – will appoint him or herself as the leader of this loosely gathered federal nation of interested people. So they will start – how can I say – exerting far greater influence than quote-unquote “a single loud-mouth” had in the past.

Marketing performance

PvT: You just mentioned analytics. How important is it to integrate marketing and customer data across the organization versus at the local level?

MM: Well, analytics is generally a can of worms that once you open it you never find a can large enough to get all the worms back in.

Analytics has become central and critical to success in the always-on, 24-by-7 integrated, online-offline brand theater.

When we start talking about analytics, we discover that 80-90 percent of the data that a marketer needs does not reside, or exist at all, in their CRM systems.

So many marketing organizations spent the last six to ten years getting organized around what I’ll call tactical CRM – your sales force automation platform. I am astounded how many firms still struggle with CRM as operational capability.

Many firms have separate or loosely connected operational CRM used by the customer service or call center. I am also amazed with the number of these system that contain little more than a transaction record about previous purchases and logged complaints.

A number of firms that have not yet integrated tactical CRM from sales operations with the operational CRM of their call centers and customer interaction centers.

I just chalk that up to the penalties of execution—everyone’s heads down hitting their numbers with little extra time or incentives to innovate something better.

Integration of multiple CRM systems represents a major undertaking for most firms, and it requires developing huge data model by which to specify – in very concrete table-to-table or data-element-to-data-element level—specifically how to transform data into high-level business information that supports specific business decisions.

Most companies that I’ve run across have incomplete or just simply wrong data maintenance procedures in place. So, as a function of that they end up with glorified mailing lists with very little useful analytic data beyond who bought what and why.

One version of the customer truth

Often first major initiative in data integration entails creation of customer master.

While simple in name, the development of a customer master represents a Herculean accomplishing: one-version-of-the-customer-truth.

As this starts by developing a data model of what constitutes a customer relationship—and I stress the relational aspects of the customer and way beyond basic name and address—we often discover that multiple individuals with multiple roles and responsibilities within a single customer object.

In this data-centric view of the world, a household or business entity constitutes the cornerstone of a customer relationship—to which you can associate a number of individual buyers and influencers by context.

Right there, many CRM implementations fall down: they make no meaningful distinction between an account, an contact, and customer object—the business entity or household—that represents the economic context for many buyers, transactions, interactions, and influencers.

So, let’s say we have a customer master—one version of the customer truth expressed in clean, uniform data!

This invokes 90/90 rule which state after you have completed 90 percent of the work (i.e., building your customer master), then you another 90 percent more to complete—the second 90 percent!

That almost always requires the purchase of external enriched data overlays to your customer master.

This will take to you companies such as Acxiom, D&B, Experian, Epsilon, InfoUSA, Merkel, etc.

Enriched data overlays of households might include credit histories and scores, the model and year of cars in the household, names of other members of the household, marital status, plus things like educational levels, current job position, annual income, total credit available and the equivalent of a business profile.

By the way, one of the most interesting developments as it relates to the customer data master, relates to the emergence of an XML standard from business reporting called XBRL (XML Business Reporting Language) that mandates that all public firms must publish their annual reports, 10-Ks, and 10-Qs in explicit 2000-element XML schema. While just a side show for now, XBRL will transform database marketing into true one-to-one engagement. Gosh, we take another hour unpacking that idea. But here’s the seed of a big idea: Every system of record in the next 5 years will adopt XBRL for all its publishing and reporting functions, creating a level of hyper transparency within business operations that will boggle the mind.

Segmenting for profit

So let’s get back to customer masters and enriched data overlays. Now you have the ability to really start to slice, and dice, segmenting customers and markets.

However, you can’t slice and dice your customer database using the relational database or the tools of a CRM system. You can start there. But, soon enough you will need more speed and better visualization.

At this point you need to bring in specialized, analytic databases—wicked fast columnar databases—for plowing through 5 or 50 million customer records with a response time of several seconds; as opposed to using a relational database that might take hours or all night to complete one complex query.

So specialized analytic databases with train-of-thought visualization tools use the enriched overlay data to begin understanding things like price sensitivity, unmet needs, and other sorts of buying criteria within dozens or hundreds of micro-markets—what analysts call consumption cohorts.

This fast-cycle analysis enables a practitioner to think in terms of predicting long-term value of individual or small clusters of customers.

With time and practice, a good analyst can profile the ideal or most profitable customer sets, specifically identify them by name, engagement criteria, and media consumption preferences..

Now, everything we have discussed to this point deals with database analytics. Four more analytic disciplines now come into play: Web analytics, messaging or email analytics, social media analytics and content analytics (or semantic analysis of one’s inventory of content and advertising)

Web analytics, site performance, and customer experience management will continue to evolve into an integrated suite—all good but fairly narrow sets of data.

Closing the loop with messaging

Messaging or email analytics really start to validate with quick call-and-response or probe-and-validate procedures of newsletters and emails specifically targeted to those segments that your predictive modeling identified.

In practical terms, this means that you need to have something far more than just the mail list manager or a newsletter system. You need to have really powerful analytics process driving each newsletter.

A creative and analytics team starts by building newsletters with Lego-blocks of content and data that correspond to a specific set of segmentation and targeting criteria.

So as I send out 15,494 emails to those individuals that I know are interested in Mexican cruises with Salsa dancing lessons, I want also want to see the response level to other recreational ideas, venues, and offers.

This will require that each email embeds personal URLs, sometimes called ‘Purls’, so that each click through takes the recipient to an individualized landing page—built just in time, just for them—that validates the messaging effectiveness or lift and associates that event’s data to a preexisting user database record.

This closes the loop in terms of my analytic profile, engagement criteria, and consumption of the media.

Now, most of the time that kind of closed-loop feedback information remains locked up in the newsletter or messaging system, and very rarely, if at all, comes back into the customer master or the creative teams driving other media creation processes.

So, as Website, database, and messaging analytics come together, guess what happens: Gee, given all these really fresh insights that our multi-channel analytics has developed, how then we inform the strategic communications teams in our agencies and our tactical content teams pushing content into the various websites—brand touchpoints that passively activate engagement as visitors land.

I have met hundreds of executives who struggle with breach: how do we get the advertising, web, direct response, and field marketing teams on the same page, using a common set of analytic insights to create effective engagement? How do make creative briefs more interactive and driven by same-day analytic insights.

Part of the underlying problem, we have discovered, lies in the very structure of what most creative and marketing professionals call content—the process of creating content and the operational capabilities of managing multimodal content.

But, I skipped to the end of my argument about the evolving integration of five analytic disciplines: Web, database, messaging, social media, and content analytics.

Getting social with analytics

So let’s pick up with social media analytics.

How do you use technology to quantify three really important dimensions of the Web 2.0 mediaspace (blogs, tweets, forums, and social networks).

How can you track, in near real-time, the mood of the market, the voice of the customer, and their individual patterns of engagement?

Social media analytics takes you further upstream into the buying process—much further up in the buying process where people are still developing awareness and consideration.

For that you need to have a really effective voice-of-the-customer program coupled with social media monitoring.

A good voice-of-the-customer program entails long-form interviews with 50 to 300 customers a month, transcribing exactly what they said about the process on discovering, considering, buying, using, and disposing (where applicable) a featured product or service—what we call the ‘customer journey’.

Of course we now see powerful new systems coming to market that automatically transcribe call-center interactions with customers—requests for information or service—all social content to feed a voice-of-the-customer content analytics process.

With semantic tagging of voice-of-the-customer content and mapping that against segmentation and engagement profile, something quite amazing emerges: each step of the customer journey.

So as a customer transits from no awareness to awareness, consideration, trial, purchase, commitment, repurchase, loyalty, and advocacy—as they transit customer engagement lifecycle—you will have actual dialog of real interviews with people at each of those stages, and, more powerfully, how they transit each stage of the customer engagement life cycle.

With just a few hundred of long-form interviews, a team will use a text mining engine map keywords and phrases of the voice-of-the-customer content and develop a taxonomy of desire: awareness, consideration, trial, preference, as well as things like dissatisfaction and satisfaction, wow, or disgust.

And as you develop this library, this taxonomy of engagement supports all kinds of goodness, including which AdWords to buy, how to optimize content for search engine discovery, and the structure of engagement.

This taxonomy of engagement also supports what practitioners call the basis of conversation—the details of how your customers talk about themselves, their lives, and what makes a contribution, including your products and services.

This all syncs up with social media analytics, usually the work of social agencies or monitoring services with specialized spidering tools that crawl through the 50 to 100 million blogs and forums and hundreds of millions of social network profiles and billions of tweets.

Social media monitoring then mines them these sources for keywords and phrases that correlate to your markets and competition, generating a dashboard with statistics on awareness, consideration, trial, etcetera, by your various customer segments, and more specifically what your customers are saying about your brand, what it means to be in a relationship at various stages of the brand lifecycle.

The voice-of-the-customer basically mines interviews about how customers talk about being in a relationship with you, and then the social media monitoring tells you how to validate which brand stories connect brands and consumers.

Agile methods for content creation

This all brings to the last analytic discipline in my rant: content and how marketers will have to reengineer their processes of creating content and and manage multimodal content.

First, it starts with the principles of digital asset management: systematic reuse, do it once, get it right up front, tag and classify everything for speed discovery and retrieval, optimize media components for database publishing and content transformation processes, build and use templates, etc.

Second, adopt the principles of agile software development. A bit much to go further here…