PvT: Which marketing solution providers are top-of-mind for you? And why? Again, that’s a broad question, but considering some of the challenges that you’ve just mentioned, can you think of solution providers that address customer engagement?

MM: Well, I have the delectable challenge that many of the vendors—technology OEMs, ISVs, marketing service providers, and solution integrators in the DAM, MOM, and related publishing technology markets, are my clients. So I am little biased towards my clients!

Now, that all said, I’m also a category champion: My job is to cheer, lead, and create energy around the next big opportunity; energize and bring new companies into the larger category of DAM, marketing operations, engagement platforms, and open-innovation processes.

That all said, I’m a little bit like a mother with a whole bunch of children. You know, mom loves all of her children. Now she might love one more than the other, but she never says. It’s really important that all of her children feel loved.

PvT: Yep.

MM: Now, so I’m not gonna be namin’ names; however, I can outline some general attributes of the leading vendor or ‘gorilla’. Probably first and foremost is that they have an integration strategy that links explicitly or implicitly to the customer-making process. So they’ve got technologies and capabilities related to pre-sales and post-sales across the customer-making lifecycle. Boom, one.

Two, that they understand that fundamentally the Web does not constitute a channel but a business eco-system. And an eco-system requires a business strategy that anticipates and rewards contributions to the ultimate end-user customer from third and fourth parties. So a business eco-system strategy really comes down to how well you understand the needs of business partners; not just strategic business partners, but perhaps most critically independent consultants and small niche boutique solution providers – 3, 4, or 5 person firms.

The third thing that really distinguishes the real gorilla or market leader is the company that really understands that purchase of its technology represents barely 10 percent of the overall commitment and value that you bring to the customer; that really is about a structured service fulfillment methodology in the spirit of satisfaction assurance. That really is an agreement by and between the vendor and the customer to build or to facilitate the customer developing or building new operational capabilities within the firm.

So that you bought my stuff and make it shelfware is unacceptable. I’m not gonna let myself off the hook until you’ve bought my stuff, you’ve deployed it, you’ve undergone all of the change management and disruption-mitigation processes, and that fundamentally you’ve created new accountabilities around the care and feeding of my technology, and that you’re now using my technology to drive strategic growth. Top line growth, be it with existing customers, or incremental business in new markets with new customers, and that I’m generating sufficient profit to offset the investment that you made in not just my technology but in my service fulfillment methodology.

Those are the 3 hallmarks, if you will, of the vendor who will succeed in this marketplace.

PvT: Fantastic. A very comprehensive answer!

How does the customer benefit?

MM: Cool! Love doing it. You know, I’d like to expand on what we just discussed, emphasizing the levels of good, better, and best—or the simple, moderate and, you know, the Mercedes version—of DAM as business strategy in global marketing operations.

PvT: Okay.

MM: Let me start by saying that enterprise DAM supports a marketing supply-chain strategy for sourcing marketing content as well as an expanding array of services for engaging customers throughout a life cycle.

PvT: Okay.

MM: Next, let’s address how firm innovate new processes within the marketing operations. I put that under the rubric of bottom-up innovation in global marketing operations. This perspective reflects some of our most current work: how companies innovate new processes using small executive peer-workgroups to create 15-day project plans that single person or small group can execute with existing resources and constraints. Specifically, this emphasizes the creation of a master project roadmap for driving innovation into operational capability.

Third, and the one that directly relates to our new white paper on operational capabilities for managing engaging customers for across an entire lifecycle.

So it would be kind of a über roadmap for how all these technologies integrate to a customer-making process model, the various integration points of these various technologies and disciplines, what are the things that you should do now, next, or later, and specifically answering one question over, and over again: How does the customer benefit?

You know, hey, this is a really cool social media technology…uh, how does the customer benefit? Oh, this new analytic tool…oy, how does the customer benefit? Oh, this new web content managr…yes, but how does the customer benefit? Oh, this new email system…how does the customer benefit?

So that’s my mantra, that’s the organizing principle, how does the customer benefit with very specific proposals from the vendor community?

And, of course, that requires that you have an integration mindset, a customer-making process model, and an innovation-services platform by which to accommodate and integrate these new technologies to new or enhanced operational capabilities.

Finally, DAM becomes integral with that innovation-services platform. In fact, digital asset management with its extreme emphasis on process and procedure for ensuring the integrity of metadata, media, and user experience (findability, usability of what you found, and permissions to do what you need to do with what your found) enables a firm to reengineer its processes of creating content and interactive services.

PvT: What type of competitive gains can companies expect from digital asset management?

MM: Well, first of all, digital asset management’s not a thing, it’s a strategy—that evolves through various what I call “process maturity stages.” For most enterprises, DAM entails operational digital asset repository. So that means you’ve got workflows by which to ingest digital assets and content, and tag these them correctly.

That means that you have content specialist, “cybrarian“, or asset services group who maintain overall quality of the both the metadata and source files—content, digital media, publishing templates, fonts, color profiles, and user accounts.

It also means that you have well-maintained metadata, descriptive taxonomy, and perhaps faceted taxonomy, by which to support very specific users in finding and retrieving what they want; and when they retrieve things, it means they’re getting the right file in the right format, including the correct permissions to use or alter the retrieved item.

Second a DAM-as-a-business-strategy entails automating activities, tasks, and workflows of digital asset creation. Automation both accelerates core business processes and lowers operational costs.

A more detailed examination of workflow reveals sub-systems for scheduling, collaboration, project management, (job jackets), review and approvals (online proofing systems—such a ProofHQ—that enable all approvers to use at one centralized commenting system, so everyone else can see everyone else’s comments), and dynamic rendering of images or database publishing of content to Websites or printed collateral. In more advanced DAM systems, firms use specialized XML databases containing product claims and pre-approved copy of marketing communications and packaging to further reduce time to market of products and promotional campaigns.

Third, DAM-as-a-business-strategy may include large file distribution, and more specifically large smart content distribution—automated packaging and publishing of finalized content into websites or microsites. Or it means that a firm can send a PDF file containing an ad to optimized for a particular magazine or newspaper—that’s been cleansed and scrubbed of all the bad PostScript data, funky TrueType fonts, and all of the pixel discontinuities or artifacts of vector and raster artwork files.

So, DAM-as-a-business-strategy become essential in orchestrating multichannel and multimodal marketing processes. Multimodal? The ability to pour content and services into engagement frameworks, engaging the particular criteria, means of consumption, and preferences of individual consumers.

Realignment of Sourcing Process in Marketing Supply Chains

When senior marketing executives really get DAM-as-a-business-strategy, they recognized smarter ways of buying creative services and marketing content as well as a whole new class of creative partners—small, nimble, and very innovative creative or customer engagement agencies—with whom to outsource or partner.

This oftentimes means renegotiating long-term contracts with advertising agencies and marketing service firms. This includes specifying the technical parameters by which creative partners will submit finished artwork, upload mastered digital assets into the DAM repository, affix the right metadata as a condition of payment.

So creative realignment—how a procures digital masters of marketing materials, ads, or online content—becomes the next phase of the process maturity model. We recently published a comprehensive white paper on collateral factories and how progressive levels of automation pay what what call productivity dividends.

At this point, many global firms punch into pan-regional localization factories such as Adnovate in The Netherlands or Arizona in Brazil. So that instead of having to manually localize or translate files in country, firms can centralize localization with highly automated systems.

This means instead of taking 7 to 11 weeks to localize print collateral for a reseller or retail channel across EMEA, I can now get that done in five to seven working days. Fabulous!

SOA Value Chains?

PvT: Who are the prime contributors to the development and support of an operational marketing and service innovation platform? And how did you start researching the technical ecosystem—what you and I now call engagement marketspace?

We started in 1995 with digital asset management and content management because no matter what else came along, you must have a media and content under management.

In 2000, we started investigating another class of vendors in the marketing automation, MRM, and marketing operations management space. Some of the vendors have make great progress.

With rare exception, they all still need to better understand DAM and, more the point, metadata management—a database and DBA for logging and tracking enterprise metadata as instantiated in all enterprise databases, including ERP and CRM, as a strategic asset.

Since 2004, we have tracked vendors that come from the CRM, business intelligence, and process analytics space.

For the last three or so years, we have tried to understand firms in marketing service provider and data enrichment vendors—lots to cover!

Of course there are whole sets of vendors in dynamic messaging and email management content space, and in the customer experience management space too/

As I stated before, there’s many different technology vectors in the marketing and innovation value chain, that ultimately support the idea of an innovation-services platform.

This calls attention to, however, the critical need for leadership within marketing to have a services integration framework and an underlying Service Oriented Architecture (SOA) enabling this integration framework. IBM does some great work there with its component business models—what I call CIO blueprints.

Services integration

However, the senior marketing executive, not the CIO, must commission and own the services integration framework—it basically specifies in one wall-mounted poster all of the services – marketing and innovation-related services – of the business eco-system from which the firm will build, buy, or rent technology or engagement services over the next five years.

Now, the CIO blueprint represent an living, evolving visual depiction of one thing: how firm intends provision services needed attracting, serving, and keeping profitable customers for life.

The CIO blueprint also makes explicit how the firm intends to marshal the resources of a global business eco-system: ‘Here’s what we bring to the customer experience. Here’s what our partners bring, and here’s how it all integrate to an end-to-end process of customer-making.

PvT: I guess that repositions marketing automation a bit player in a larger play?

MM: Well, I don’t think that the rubric of marketing automation delivers useful distinction anymore. I don’t like the term “marketing automation” because many of the research firms and vendors have abused the term, rendering it useless.

Rather, I would like to speak about marketing in terms of process maturities, and levels of process maturity for a marketing operation.

Again, the senior executive doesn’t really care about technology or marketing automation, per se, he or she is most concerned with operational capabilities and building or enhancing capabilities which will related directly to a process maturity model for marketing operation.

However, this all underscores a very strategic point: business rules and metadata enable orchestration of the technologies and processes of how firms attract, serve, and keep customers for life. Very, very few technology vendors deliver solutions for orchestrating the customer engagement life cycle. Typically, the missed or underplay the role of three SOA capabilities: digital asset management, metadata management, and marketing claims management.

Marketing claims management

This last one, marketing claims management, entails a end-to-end workflow for developing and publishing approved copywritten material—product or service claims—to a specialize XML database publishing system. I use the term broadly to include anything written, formatted, and published in printed collateral, business communications, web sites, interactive detailing or presentation systems, catalogs, microsites, newsletters, etc.

In my view of the world, marketing claims management represents a subsystem of DAM and metadata management—that in turn represent subsystems of master data management.

And all of which requires a IT governance scheme—systems, processes, and accountabilities for researching, acquiring or developing, deploying, provisioning, managing, and retiring the technologies used to attract, serve, and keep customers for life!

Key point: tomorrow’s CMOs are mid-level IT executives today getting their masters in Business Administration or Media Psychology.

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…