Wanted: Data-Driven, Digital CMOs

There was a time, not so long ago, that the firm’s CMO basically acted as the chief brand steward, running a marketing department that focused on maintaining brand equity and making sure the company was sending out the right message to the masses. Data and analytics? They were usually scoffed at … That was the purview of the down-and-dirty world of the direct marketer, right? Direct marketers were the ones who obsessed over response rates, cost per order, lifetime value and so on.

There was a time, not so long ago, that the firm’s CMO basically acted as the chief brand steward, running a marketing department that focused on maintaining brand equity and making sure the company was sending out the right message to the masses. Data and analytics? They were usually scoffed at … That was the purview of the down-and-dirty world of the direct marketer, right? Direct marketers were the ones who obsessed over response rates, cost per order, lifetime value and so on.

Well, suffice it to say that those days are over—marketing in today’s multichannel environment is about much more than just cute creatives and killer copy. Today’s marketing is increasingly digital and data-centric. A recent article appearing in Ad Age explained that “real-time data-driven decisions, enabled by technology, have made the marketer’s job much more measureable and accountable.” Interestingly, the same article also points out that the average tenure of a CMO is a meager 28 months. No coincidence.

What it boils down to is that today’s CMO is expected, de rigueur, to be a pro when it comes to all things digital. We have two important trends to thank for this fact. The first one of these trends is the general transition to digital. Look, it’s no secret that over the past few years there’s been an incredible shift of marketing spend from traditional over to digital media. It’s the scale and speed of this transition that’s so breathtaking.

According to a June 2012 survey by RSW/U.S., 44 percent of marketers report that they are now spending at least half of their budgets on social and digital media. This represents a 42 percent increase from 2009 alone! And this is not the end of the process. I think it’s safe to say now that the proverbial tipping point has been reached—this trend will only accelerate in coming years.

Anyone who’s worked in the digital marketing arena knows that success in the space all really boils down to data: Impressions, clicks, conversions, opens—this is the vocabulary of the digital world. Well, guess what? Today’s CMO needs to have a deep understanding of these terms, what they mean and how the underlying technologies work—at least on a high level—and be generally comfortable playing in the digital space. Think about it: without a significant digital background, how on Earth can a CMO possibly be expected to run a marketing machine where at least half of the marketing dollars are being spent in the digital space? Not happening.

The other major trend is the inexorable fragmentation of the IT infrastructure within enterprise firms. Basically, what’s happening is that because technology has evolved radically over the past 10 years, it’s giving different stakeholders at companies the ability to purchase and use technology outside of their organization’s firewall, and often without IT’s involvement. Very often, in fact, IT is even without IT’s knowledge!

This is huge shift. Just a few short years ago, mind you, software was what you ran on your computer or on the company mainframe, and it was pretty much always purchased and managed by IT. Well, those days are most definitely over. What’s happened is that the emergence of the SaaS/Cloud model of software delivery has turned that world on its head.

Today, any marketer with a credit card can sign up for, say, a CRM tool or a marketing automation tool and be off to the races in seconds flat. Ask any marketer and they’ll explain how this has been a huge boon to their departments, liberating them forever from the clutches of IT.

Now, of course, a big reason for this excitement is the oftentimes frosty relationship between marketing and IT. Personality types side, in its essence this rocky relationship actually has a lot to do with conflicting mandates. It’s the IT department’s mandate to act as the stewards of the firm’s information and technology infrastructure. Essentially, it’s their job to keep internal systems running and make sure they’re secure. That’s about it. No, it’s not their job to build you a new landing page, or set up a new email campaign for this fall’s reactivation campaign.

Today’s marketing department, on the other hand, is much more focused on operations than anything else. Today marketing is about creating, testing and launching numerous marketing campaigns across various channels using different tools, and evaluating their performance using real-time analytics. And running an operationally focused marketing team requires the ability to build, dispatch and analyze lots of campaigns in rapid succession. Until recently, this heaped loads of pressure on the IT folks, who groaned under the strain. So you can see why marketers have cheered and embraced the emergence of Web-based SaaS marketing tools.

Okay, I got a little sidetracked there, so I’ll get back to the central point, which is that because marketing is rapidly becoming the de facto owners of their own IT infrastructure, this mean that they now control the technology itself and the data contained therein. It’s a big responsibility, requiring marketers to manage and safeguard this vital corporate infrastructure and information, taking on the dual roles of chief marketing technologist and data steward. But with this responsibility comes great power—to use these awesome tools and information to really, truly understand who customers and prospects are, and send out highly personalized and effective marketing campaigns with demonstrable ROI.

But evaluating performance in this environment means not only using new marketing tools and digging through mountains of data. Just as importantly, it also means understanding what it all means. In other words, just because you’re a CMO does not mean you don’t need to know how many opt-ins you have in your company database, or how many fans on Facebook.

And guess what? It’s hard to be comfortable with digital if you’ve never played in the space. But how many CMOs are also digital pros? Not too many. So not surprisingly, firms are finding that it’s incredibly difficult to find leaders with the hard-to-find combination of senior management leadership and digital marketing experience. Given this reality, it’s not too surprising to discover that many companies are running through CMOs in a conveyor belt-like fashion.

Do you know any data-driven digital pros with senior marketing leadership experience?? If so, bet your bottom dollar these executives will be cashing in big time in coming years.

—Rio

Reducing UAA Must Focus on New Movers

In a recent post, I addressed the issue of undeliverable as addressed (UAA) mail, and how brands, businesses and other mailers lose more than $1 billion a year by not getting their mail addressed properly. It’s a solvable problem. Both the USPS and the DMA have made public commitments to reduce UAA as an industry goal, both of which would help marketers and their bottom lines. Progress toward UAA reduction, however, has not been uniform.

In a recent post, I addressed the issue of undeliverable as addressed (UAA) mail, and how brands, businesses and other mailers lose more than $1 billion a year by not getting their mail addressed properly. It’s a solvable problem.

Both the USPS and the DMA have made public commitments to reduce UAA as an industry goal, both of which would help marketers and their bottom lines. Progress toward UAA reduction, however, has not been uniform.

Recently, Charley Howard, who is the vice president of postal affairs at Harte-Hanks (disclosure: Harte-Hanks is a client), discussed this concern in a monthly e-newsletter he writes for the company called Postology. Charley wrote about UAA, and explained why UAA reduction goals have been slow to materialize. One of the key reasons has nothing to do with mailers, and everything to do with mail recipients: Too few Americans are filling out National Change of Address (NCOA) forms as they had previously. In fact, less than 50 percent are now doing so, and its ramifications on UAA volume are profound.

Frankly, mailers must supplement their use of NCOA with proprietary change-of-address/new move data from commercially available sources in the private sector. There’s just no way around this. However, by taking advantage of such services (as all direct mailers should), there is a risk that the USPS, ironically, will penalize the mailer. Charley explains the paradox here, used with permission:

USPS New Moves Source Is not Enough
“In addition to … postal-approved methods for Move Updates being applied to mailing files, there are those in the industry that additionally supplement postal moves with a Proprietary Change of Address (PCOA) service offering (for example, Harte-Hanks offers such a service). The sources of this move data tend to come from utility, telecommunication and publishing companies. In recent years, PCOA has developed into a near necessity because of the diminishing numbers of people who fill out the USPS Change of Address form.

When NCOALINK started in late 1986, more than 90 percent of all moves were captured. Today the use of COA cards has fallen to less than 50percent of moves. How can the USPS ever hope to reach its goal of cutting UAA mail by 50percent if its own source for Move Update data has fallen below half of all moves? Forcing mailers to go outside the Postal Service to attempt to obtain the balance of the moves contains some postage risk, however.

During Mail Acceptance, mail samplings are run through the MERLIN detection machine. The scanned records are passed by the USPS’s COA data to test for Move Update compliance of 90%. There is a chance of failure through the use of proprietary sourced moves. Here is an example. Say a grown child leaves home to go to college or to get a job and an apartment. The child files the COA with the USPS. Assume 9 months later the child returns home for whatever reason and no COA is filed. The USPS COA has the first move but not the second. The mail owner, using a PCOA, has obtained the second move back to the original address and is using it in the current mailing. MERLIN would show this as a failure because the move the USPS has on record is not reflected in the mailing. The service provider would have to fight this ruling to prove that it has the more current data.

The real problem here is that the USPS’s own COA data is inadequate to achieve the desired results. It is inadequate to even validate the thoroughness of Move Update compliance. The USPS needs to recognize that along with less use of the mail by younger generations, comes little to no use of COA as a stand-alone product. Therefore the USPS needs to supplement its own data with outside sourced data to become the sole repository of moves, once again. The USPS needs to invest in better data to save more in the end – and only then can UAA be reduced in line with Postal Service management goals.”

This opinion in its entirety reflects Charley’s view—and not necessarily my own or that of Harte-Hanks. But, I do believe that using PCOA should be recognized in some fashion by USPS, so mailers can be rewarded for keeping their mail off the UAA track and in the recipients’ hands. Putting the onus on the mailer to explain how its list is more up to date than the USPS’s on change-of-address concerns seems to be a burden that does not reflect today’s list hygiene realities. Either USPS should incorporate PCOA sources in MERLIN, or it should provide some sort of seal of approval on what private sector sources are already doing to help mail reach the intended recipient. Let me know your points of view in your comments here.

Helpful Links:

Direct Marketing Association on UAA Reduction

USPS Strategic Sustainability Performance Plan, FY 2011 (see page 65)

Harte-Hanks Postology (June 2012) on UAA and Move Updates (live link as of June 14, 2012)

Nextmark’s List Search Platform (search using “New Movers” or “Change of Address”)

An example of a recently released “New Move” file (disclosure: Alliant is a client)

MDM: Big Data-Slayer

There’s quite a bit of talk about Big Data these days across the Web … it’s the meme that just won’t quit. The reasons why are pretty obvious. Besides a catchy name, Big Data is a real issue faced by virtually every firm in business today. But what’s frequently lost in the shuffle is the fact that Big Data is the problem, not the solution. Big Data is what marketers are facing—mountains of unstructured data accumulating on servers and in stacks, across various SaaS tools, in spreadsheets and everywhere else you look in the firm and on the cloud.

There’s quite a bit of talk about Big Data these days across the Web … it’s the meme that just won’t quit. The reasons why are pretty obvious. Besides a catchy name, Big Data is a real issue faced by virtually every firm in business today.

But what’s frequently lost in the shuffle is the fact that Big Data is the problem, not the solution. Big Data is what marketers are facing—mountains of unstructured data accumulating on servers and in stacks, across various SaaS tools, in spreadsheets and everywhere else you look in the firm and on the cloud. In fact, the actual definition of Big Data is simply a data set that has grown so large it becomes awkward or impossible to work with, or make sense out of, using standard database management tools and techniques.

The solution to the Big Data problem is to implement a system that collects and sifts through those mountains of unstructured data from different buckets across the organization, combines them together into one coherent framework, and shares this business intelligence with different business units, all of which have varying delivery needs, mandates, technologies and KPIs. Needless to say, it’s not an easy task.

The usual refrain most firms chirp about when it comes to tackling Big Data is a bold plan to hire a team of data scientists—essentially a bunch of database administrators or statisticians who have the technical skills to sift through the Xs and 0s and make sense out of them.

This approach is wrong, however, as it misses the forest for the trees. Sure, having the right technology team is essential to long-term success in the data game. But truth be told, if you’re going to go to battle against the Big Data hydra, you need a much more formidable weapon in your arsenal. Your organization needs a Master Data Management (MDM) strategy in order to succeed.

A concept still unknown to many marketers, MDM comprises a set of tools and processes that manage an organization’s information on a macro scale. Essentially, MDM’s objective is to provide processes for collecting, aggregating, matching, consolidating, quality-assuring and distributing data throughout the organization to ensure consistency and control in the ongoing maintenance and application use of this information. No, I didn’t make up that definition myself. Thanks, Wikipedia.

The reason why the let’s-bring-in-the-developers approach is wrong is that it gets it backwards. Having consulted in this space for quite some time, I can tell you that technology is one of the least important pieces in the puzzle when it comes to implementing a successful MDM strategy.

In fact, listing out priorities when it comes to MDM, I put technology far to the end of the decision-tree, after Vision, Scope, Data Governance, Workflow/Process, and definition of Business Unit Needs. As such, besides the CTO or CIO, IT staff should not be brought in until after many preliminary decisions have been made. To support this view, I suggest you read John Radcliffe’s groundbreaking ‘The Seven Building Blocks of MDM: A Framework for Success‘ published by Gartner in 2007. If you haven’t read it yet and you’re interested in MDM, I suggest taking a look. Look up for an excellent chart from it.

You see, Radcliffe places MDM Technology Infrastructure near the end of the process, following Vision, Strategy, Governance and Processes. The crux of the argument is that technology decisions cannot be made until the overall strategy has been mapped out.

The rationale is that at a high-level, MDM architecture can be structured in different ways depending on the underlying business it is supporting. Ultimately, this is what will drive the technology decisions. Once the important strategic decisions have been made, a firm can then bring in the development staff and pull the trigger on any one of a growing number of technology providers’ solutions.

At the end of 2011, Gartner put out an excellent report on the Magic Quadrant for Master Data Management of Customer Data Solutions. This detailed paper identified solutions by IBM, Oracle (Siebel) and Informatica as the clear-cut industry leaders, with SAP, Tibco, DataFlux and VisionWare receiving honorable mention. Though these solutions vary in capability, cost and other factors, I think it’s safe to say that they all present a safe and robust platform for any company that wishes to implement an MDM solution, as all boast strong technology, brand and financial resources, not to mention thousands of MDM customers already on board.

Interestingly, regarding technology there’s been an ongoing debate about whether MDM should be single-domain or multi-domain—a “domain” being a framework for data consolidation. This is important because MDM requires that records be merged or linked together, usually necessitating some kind of master data format as a reference. The diversity of the data sets that are being combined together, as well as the format (or formats) of data outputs required, both drive this decision-making methodology.

For companies selling products, a product-specific approach is usually called for that features a data framework built around product attributes, while on the other hand service businesses tend to gravitate toward a customer-specific architecture. Following that logic, an MDM for a supply chain database would contain records aligned to supplier attributes.

While it is most certainly true that MDM solutions are architected differently for different types of firms, I find the debate to be a red herring. On that note, a fantastic article by my colleague Steve Jones in the UK dispels the entire single-versus-multi domain debate altogether. I agree wholeheartedly with Jones in that, by definition, an MDM is by an MDM regardless of scope. The breadth of data covered is simply a decision that needs to be made by the governance team when the project is in the planning stages—well before a single dollar has been spent on IT equipment or resources. If anything, this reality serves to strengthen the hypothesis of this piece, which is that vision more technology drives the MDM implementation process.

Now, of course, an organization may discover that it’s simply not feasible (or desirable) to combine together customer, product and supplier information in one centralized place, and in one master format. But it’s important to keep in mind that the stated goal of any MDM solution is to make sense out of and standardize the organization’s data—and that’s it.

Of course there’s much more I can cover on this topic, but I realize this is a lot to chew on, so I I’ll end this post here.

Has your firm implemented, or are you in the process of implementing, an MDM solution? If so, what process did you follow, and what solution did you decide upon? I’d love to hear about it, so please let me know in your comments.

How to Make a Billion: The Costs of ‘Undeliverable as Addressed’

The USPS recently shared some interesting data on the volume and cost of undeliverable as addressed (UAA) mail. That tab was $1.3 billion in 2010, and that was just the cost to the Postal Service, which has to incorporate these costs into its rate-setting. All this UAA is money down the drain to the mailers—who designed, produced and labeled it and applied its postage—and to the Postal Service that has to deal with its final disposition.

The USPS recently shared some interesting data on the volume and cost of undeliverable as addressed (UAA) mail.

According to the USPS, “Total UAA volume dropped from 9.3 billion pieces (4.71 percent of total mail volume) in FY 1998 to 6.9 billion pieces (4.11 percent of total mail volume) in FY 2010. (This reduction, while significant, falls far short of previous Postmaster General Jack Potter’s goal of reducing UAA mail by 50 percent by 2010.) Historically, UAA mail runs in the range of 4 percent to 5 percent of total mail volume, and the percentages of total volume vary by class of mail. Periodicals mail, for example, has a UAA percentage of about 1.5 percent, while Standard Mail usually runs about 6.75 percent. Interestingly, the volumes of UAA mail that the USPS forwards or treats as waste both experienced declines, but the volume of UAA mail that the USPS returns to sender actually increased.”

All this UAA is money down the drain to the mailers—who designed, produced and labeled it and applied its postage—and to the Postal Service that has to deal with its final disposition.

That tab was $1.3 billion in 2010, and that was just the cost to the Postal Service, which has to incorporate these costs into its rate-setting. Add to this bill the cost of 7 billion pieces that went nowhere near the intended recipient—and that’s a fortune off the bottom line. Some of this is inefficiency. Marketers in particular—primarily who use the Standard Mail category—must do a better job in data hygiene and the use of postal addressing and preparation tools.

It may be helpful, and profitable, for mailers to make sure they are undertaking every feasible effort to keep their mailing lists clean—and to avoid this hefty bill. The Direct Marketing Association has an online tool to help marketers make sure their list hygiene and data management efforts are up to par.

It’s called the Environmental Planner & Optional Policy Generator, and it’s based in part on the DMA’s “Green 15” Environmental Principles. But the green focus is dual in nature. Avoiding mail waste through proper data management also applies green—as in money—back to the bottom line! Consider these suggested activities from this planner to get back some of this billion-plus that are lost to UAA:

________________________________________________________

I. LIST HYGIENE AND DATA MANAGEMENT

Our company continually endeavors to manage data and lists in an environmentally responsible manner with a focus on reducing the amount of duplicate, unwanted and undeliverable mail [to both consumers and businesses]. To achieve our goals in this area [If applicable to the goals and/or nature of your organization, please select one or more of the following options.]:

A. We Maintain Suppression Lists

  • We maintain in-house do-not-market lists for prospects and customers who do not wish to receive future solicitations from us (as required by DMA’s Commitment to Consumer Choice).
  • We maintain a more detailed suppression file that enables customers and prospects to opt off our organization’s marketing lists on a selective basis, such as by frequency or by category.

B. We Offer Notice & Choice

  • We provide existing and prospective customers with notice of an opportunity to modify or eliminate future marketing contacts from our organization in every commercial solicitation (as required by DMA’s Commitment to Consumer Choice).
  • We provide periodic notices and opportunities for prospects to opt in or opt out of receiving future marketing contacts from our organization.
  • We provide customers incentives (such as the offer of a discount on their next purchase) for notifying us of duplicate mailings and incorrect addresses.
  • We offer customers a choice to receive communications from our organization electronically.

C. We Clean Our Lists Prior to Mailing

  • We use the Direct Marketing Association (U.S.) Mail Preference Service (MPS) monthly on all applicable consumer prospecting lists. In addition to use of MPS, we maintain clean, deliverable files by using (Please check all that apply):
    • ZIP Code correction
    • Address standardization
    • USPS National Change of Address (NCOA)
    • Other USPS products such as
      • Address Element Correction (AEC)
      • Delivery Sequence File (DSF)
      • Address Correction Requested (ACR)
    • Predictive models and RFM segmentation
    • Other: (Please specify.)
  • We use the DMA “Deceased Do Not Contact” list to eliminate names of deceased persons from mailings.
  • We use the Foreign Mail Preference Service on applicable mailings to the United Kingdom, Belgium or Germany.
  • We use the mail preference services of other foreign national direct marketing associations, where applicable.
  • We [ encourage/ require] our client mailers to use MPS.
  • We [ encourage/ require] companies and organizations that rent our list of customers to screen consumer names through MPS, and to maintain their own do-not-rent and do-not-mail in-house name suppression lists.

D. We Merge/Purge Our Data

  • We match outside lists against each other to prevent duplicates.
  • We use match definitions in merge/purge that minimize duplicates.
  • We match outside lists against other commercially available suppression files where appropriate.

E. We Test Market Offers

  • We test a sample of a list before mailing or marketing to the entire list.
  • We test different versions of advertising and marketing offers, in mail and other media, to select those offers and media combinations that receive the best response.

For more information, see DMA Environmental Resource Guide, “Mailing List Management: A Key to Waste Reduction,” pages 63-70.

________________________________________________________

Now the entirety of the UAA issue is not attributable solely to less than adequate data management, but it is likely a good portion of it is. We know the DMA Board of Directors—in adopting its first environmental public goal which in part commits to reduce UAA by 25 percent from 2009 to 2013—very much intends for marketers to avoid losing these billions down the line.

The Postal Service is working closely with mailers and, vice versa, to tackle other ways to manage UAA and to reduce its volume. Certainly, Intelligent Mail barcodes will help, with the ability to track mail whereabouts in real time as it moves through the USPS’s processing and handling. “Return to Sender” UAA is the most costly for the Postal Service to handle, because of the return handling costs—that, too, needs attention.

In the very least, marketers also should work with their mail service providers most closely to design mail pieces for postal automation compatibility, to apply proper data management practices (as indicated by DMA, for example), and—as the USPS embarks on its network consolidation effort—to track their mail most precisely through the mail stream. A billion dollars and more are in the balance.

Helpful Links:
DMA First Public Green Goal, concerning List Hygiene

DMA Environmental Planner & Optional Policy Generator

New Paper Recovery Data Shows Impact of Recession, Digital Media

New data from the American Forest & Paper Association regarding paper recovery rates in the United States has some good news—and not-so-good news—regarding U.S. recycling collection. As marketers, we need to pay close attention to these rates, and take active steps to support increased recovery, since such recovery can have positive impact on recycled paper supply and pricing, as well as other marketplace concerns regarding our print communications and paper packaging.

New data from the American Forest & Paper Association regarding paper recovery rates in the United States has some good news—and not-so-good news—regarding U.S. recycling collection. As marketers, we need to pay close attention to these rates, and take active steps to support increased recovery, since such recovery can have positive impact on recycled paper supply and pricing, as well as other marketplace concerns regarding our print communications and paper packaging.

The good news is that the paper business has continued to increase recovery rates for all types of paper, achieving a record 66.8-percent recovery for the nation [see the first image in the media player at right].

For printing and writing grades, recovery rates slipped from its 2009 recovery percentage peak of 61.0 percent, now registering a 56.8-percent recovery rate, but still ahead of the pre-recession recovery rate [see the second image in the media player at right].

In both the overall market for all grades combined, and the printing & writing grades market, the peak year for paper consumption (the bars on both of the preceding graphs) was pre-recession 2007, a high point we have yet to re-attain in both categories as our economy has returned to tepid growth.

However, by looking at just printing & writing grades consumption, the falloff from the 2007 peak, and the lack of recovery, is far more pronounced than in the paper market overall—fully a 23.7-percent drop from 2007 to 2011. This is certainly a sign that while the recession prompted a pullback, digital media has brought on a migration from print communications, and most certainly in postal mail. That data is supported by declining U.S. Postal Service First-Class Mail volume data, and near-minimal growth in Standard Mail.

Thus, the generally higher recovery rates are generated by higher recycling collection activity or perhaps a more expansive recovery infrastructure, but also by source reduction—there’s just less printing and writing papers being generated.

Certainly, the role of direct mail is changing in an increasingly mobile, digital age—and thankfully, we’re getting a good percentage of what we do consume recycled. We need to do better.

Helpful Links:

The Great Marketing Data Revolution

I think it’s safe to say that “Big Data” is enjoying its 15 minutes of fame. It’s a topic we’ve covered in this blog, as well. In case you missed it, I briefly touched on this topic in a post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey,” which I published a few weeks back. For those of you who don’t know what it is, Big Data refers to the massive quantities of information, much of it marketing-related, that firms are currently collecting as they do business.

I think it’s safe to say that “Big Data” is enjoying its 15 minutes of fame. It’s a topic we’ve covered in this blog, as well. In case you missed it, I briefly touched on this topic in a post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey,” which I published a few weeks back.

For those of you who don’t know what it is, Big Data refers to the massive quantities of information, much of it marketing-related, that firms are currently collecting as they do business. Since the data are being stored in different places and many varying formats, for the most part the state they’re in is what we refer to as “unstructured.” Additionally, because Big Data is also stored in different silos within the organization, it’s generally managed by various teams or divisions. With the recent advent of Web 2.0, the volume of data firms are confronted with has quite literally exploded, and many are struggling to store, manage and make sense out of it.

The breadth of data is simply staggering. In fact, according to Teradata, more data have been created in the last three years than in all past 40,000 years of human history combined! And the pace of data is only predicted to continue growing. You see, proliferating channels are providing us with an unprecedented amount of information—too much even to store! In a marketing sense, the term Big Data essentially refers to the collection of unstructured data from across different segments, and the drive to make sense of it all. And it’s not an easy task.

Think about it. How do you compare email opens, clicks and unsubscribes to Facebook “Likes” or Twitter followers, tweets or mentions? How does traffic your main website is receiving relate to the data stored in your CRM? How can you possibly compare the valuable business intelligence you’re tracking in your marketing automation platform you’re using for demand generation, against the detailed customer records you’re storing in your ERP you use for billing and customer service? Now throw in call center data, point of sale (POS) stats … information provided by Value Added Retailers (VARs), distributors and third-party data providers. More importantly, how do they ALL compare and relate together? You get the picture.

Now this begs the next question; which is, namely, what does this mean to marketers and marketing departments. This is where it gets very interesting. You see, unbeknownst to many, there’s an amazing transformation that is just now taking place within many firms as they deal with the endless volumes of unstructured data they are tracking and storing every day across their organization.

What’s happening is firms are rethinking the way they store, manage data and channel data throughout their entire companies. I call it the Great Marketing Data Revolution. It’s essentially a complete repurposing and reprocessing of the tools they use and how they’re used. This wholesale repurposing aims not only to make sense out of this trove of data, but also to break down the walls separating the various silos where the information is stored. As we speak, pioneering companies are just now leading the charge … and will be the first to reap the immense benefits down the road when the revolution is complete.

Ultimately, success in this crucial endeavor demands a holistic approach. This is the case because this drive essentially requires hammering out a better way of doing business by reprocessing across these four major steps: Process Workflow, Human Capital, Technology, and Supply Chain Management. In other words, doing this right way may require a complete rethinking of the direction that data flows within an organization, who manages it, where the information is stored, and what third-party suppliers need to be engaged with to assist in the process. We’re talking a completely new way of looking at marketing process management.

With so many moving parts, not surprisingly there are many obstacles in the way. Those obstacles include legacy IT infrastructure, disparate marketing structure scattered across various departments, limited IT budgets and, of course, sheer inertia. But out of all the obstacles companies face, the most important may be the dearth of data-savvy staff and marketing talent that firms have on staff.

Firms are having a difficult time staffing up in this area because this transformation is actually a hybrid marketing and IT process. Think about it. The data are being created by the firm’s marketing department. As such, only marketing truly understands not only how the data are being generated, but more importantly why they’re important and how this information can be put to actionable use in the future. At the same time, the data are stored within IT’s domain, sitting on servers or stacks, or else stored in the cloud. And because the process involves a complete rethinking and reprocessing, it really needs a new type of talent—basically a hybrid marketer/technologist—to make it happen.

Many are deeming this new role that of a Data Scientist. Not surprisingly, because this is a new role, employees with these skills aren’t exactly a dime a dozen. You can read about that here in this article that appeared on AOL Jobs titled “Data Scientist: The Hottest Job You Haven’t Heard Of.” The article reports that, because they’re in such high demand, Data Scientists can expect to earn decent salaries—ranging from $60,000 to $115,000.

Know any Data Scientists? Are you involved in a similar reprocessing transformation for your firm? If so, I’d love to know in your comments.

Deciphering Big Data Is Key to Understanding Buyer’s Journey

Long before a sale is won or lost, customers and prospects embark on what can be called the “buyer’s journey.” This journey is a complex evolution spanning the entire lifecycle of the customer-vendor relationship, beginning with identification of the underlying business issue or need, and culminating in vendor selection.

Long before a sale is won or lost, customers and prospects embark on what can be called the “buyer’s journey.” This journey is a complex evolution spanning the entire lifecycle of the customer-vendor relationship, beginning with identification of the underlying business issue or need, and culminating in vendor selection.

Along the way, the prospect engages in a wide breadth of activities. Some are internal, such as winning over key stakeholders, building internal consensus and acquiring the necessary budget; while others are externally facing. For example, market research, engaging with colleagues in similar firms to share experiences, and of course contacting salespeople for product demos and pricing negotiation.

I do not claim to have coined the term ‘buyer’s journey.’ For more information on it, you can check out a great article by Christine Crandell that appeared on Forbes.com earlier this month. Among other things, Crandell does a great job explaining how social media can be leveraged to better connect with and understand the buyer’s journey, particularly during times when prospects are not engaged with your sales team. What’s especially interesting about the concept of the buyer’s journey is that prospects are actually unengaged with your firm during the vast majority of this process. Engagement only begins when prospects start their market research and contact a salesperson—usually not before.

Now how does this relate to database marketing? Well, it does in two huge ways. On a strategic basis, any marketer worth his or her own salt knows that effective marketing depends getting your message in front of qualified prospects as inexpensively as possible. In order to do this effectively, identifying how prospects are researching the marketplace is key. Why? Because this is where your prospects are spending much of their time, this is where you need to have your brand appearing front and center. So, from a marketing spend point of view, without a doubt this is where you’re going to get the most bang for your buck.

Now, of course, this is far easier said than done. It’s going to take a ton of market research, including customer interviews, focus groups, industry insight and general analysis to identify how your customers researched the marketplace prior to making a purchase. Did they attend key industry trade shows or events? Do they belong to specific peer or networking groups? What publications do they subscribe to? Whatever the answers to these questions are … well this is where you need to be.

Another key to deciphering the buyer’s journey is understanding how the prospect is engaging with your firm across all Key Performance Indicators (KPIs). This understanding can only be arrived at through a deep analysis of every touchpoint between you are your customers. The best way to achieve this is to identify and extract customer and prospect data wherever it may reside. There are no shortcuts here. For large organizations, it can be located in an email broadcast tool, CRM, ERP, Marketing Automation Solution or purpose-built Master Data Management (MDM) Hub, among other places.

Now, of course, this means extracting and sifting through tons and tons of data—everything ranging from garden variety campaign analytics to purchasing history, from personal attributes to company insight, from demographic data to psychographic profile. Tracking, archiving and sorting out all this information is big business. In fact, many in the industry are now referring to this reality as ‘Big Data,’ as companies track and store vast troves of information that they need to make sense out of. In addition to the physical IT infrastructure required to capture and store the information, making sense out of it often requires technical expertise. Without wanting to veer off topic, if this sounds interesting then I suggest turning to NPR, where an interesting and in-depth story on Big Data aired on November 29, 2011.

As I was saying, once the data is extracted, you need to make sense out of it. Paramount to this task is the process of creating robust user profiles replete with detailed demographic, psychographic and, of course, (for B2B) firmographic information—in effect, multi-dimensional user profiles—and mapping it back to KPIs that help identify engagement patterns and behavior central to the buyer’s journey.

Once user profiles have been established, this is where the fun parts comes in, as marketers leverage this information to create compelling offers that speak to the various customer segments. The good news is that recent technological innovations have made this job much easier and more effective. Using marketing automation tools, it’s now possible to broadcast varying sophisticated drip marketing campaigns to various segments of your database—segments that can now easily be created using complex rules based on both list attributes and user engagement. What’s more, the marketing message itself—email creative, direct mail piece, landing page, and so on—can now be highly personalized based on profile data, resulting in higher response rates, reduced media costs and, of course, improved customer satisfaction.

I hope this all makes sense. Any comments or feedback are welcome.

Updating Your Marketing Database

It’s amazing how quickly things go obsolete these days. For those of us in the business of customer data, times and technologies have changed along with the times. Some has to do with the advent of new technologies; some of it has to do with changing expectations. Let’s take a look at how the landscape has changed and what it means for marketers.

It’s amazing how quickly things go obsolete these days. For those of us in the business of customer data, times and technologies have changed along with the times. Some has to do with the advent of new technologies; some of it has to do with changing expectations. Let’s take a look at how the landscape has changed and what it means for marketers.

For marketing departments, maintaining updating customer data has always been a major headache. One way to update data is by relying on sales team members to make the updates themselves as they go about their jobs. For lack of a better term, let’s call this method internal crowd-sourcing, and there are two reasons why it has its limitations.

The first reason is technology. Typically, customer data is stored in a data hub or data warehouse, which is usually a home-grown and oftentimes proprietary database built using one of many popular database architectures. Customer databases tend to be proprietary because each organization sells different products and services, to different types of firms, and consequently collects different data points. Additionally, customer databases are usually grown organically over many years, and as a result tend to contain disparate information, often collected from different sources during different timeframes, of varying degrees of accuracy.

It’s one thing having data stored in a data warehouse somewhere. It’s quite another altogether to give salespeople access to a portal where the edits can be made—that’s been the real challenge. The database essentially needs to be integrated with or housed in some kind of tool, such as an enterprise resource planning (ERP) software or customer relationship management (CRM) software that gives sales teams some capability to update customer records on the fly with front-end read/write/edit capabilities.

Cloud-based CRM technology (such as SalesForce.com) has grown by leaps and bounds in recent years to fill this gap. Unlike purpose-built customer databases, however, out-of-the-box cloud-based CRM tools are developed for a mass market, and without customizations contain only a limited set of standard data fields plus a finite set of “custom fields.” Without heavy customizations, in other words, data stored in a cloud-based CRM solution only contains a subset of a company’s customer data file, and is typically only used by salespeople and customer service reps. Moreover, data in the CRM is usually not connected to that of other business units like marketing or finance divisions who require a more complete data set to do their job.

The second challenge to internal crowd-sourcing has more to do with the very nature of salespeople themselves. Anyone who has worked in marketing knows firsthand that it’s a monumental challenge to get salespeople to update contact records on a regular basis—or do anything else, for that matter, that doesn’t involve generating revenue or commissions.

Not surprisingly, this gives marketers fits. Good luck sending our effective (and hopefully highly personalized) CRM campaigns if customer records are either out of date or flat out wrong. Anyone who has used Salesforce.com has seen that “Stay in Touch” function, which gives salespeople an easy and relatively painless method for scrubbing contact data by sending out an email to contacts in the database inviting them to “update” their contact details. The main problem with this tool is that it necessitates a correct email address in the first place.

Assuming your salespeople are diligently updating data in the CRM, another issue with this approach is it essentially limits your data updates to whatever the sales team happens to know or glean from each customer. It assumes, in other words, that your people are asking the right questions in the first place. If your salesperson does not ask a customer how many employees they have globally or at a particular location, it won’t get entered into the CRM. Nor, for that matter, will data on recent mergers and acquisitions or financial statements—unless your sales team is extremely inquisitive and is speaking with the right people in your customers’ organizations.

The other way to update customer data is to rely on a third-party data provider to do it for you—to cleanse, correct, append and replace the data on a regular basis. This process usually involves taking the entire database, uploading it to an FTP site somewhere. The database is then grabbed by the third party, who then works their magic on the file—comparing it against a central database that is presumably updated quite regularly—and then returning the file so it can be resubmitted and merged back into the database on the data hub or residing in the CRM.

Because this process involves technology, has a lot of moving parts and involves several steps, it’s generally set up as an automated process and allowed to run on a schedule. Moreover, because the process involves overwriting an entire database (even though it is automated) it requires having IT staff around to supervise the process in a best-case scenario, or jump in if something goes wrong and it blows up completely. Not surprisingly, because we’re dealing with large files, multiple stakeholders and room for technology meltdowns, most marketers tend to shy away from running a batch update more than once per month. Some even run them quarterly. Needless to say, given the current pace of change many feel that’s not frequent enough.

It’s interesting to note that not very long ago, sending database updates quarterly via FTP file dump was seen as state-of-the-art. Not any longer, you see, FTP is soooo 2005. What’s replaced FTP is what we call a “transactional” database update system. Unlike an FTP set-up, which requires physically transferring a file from one server and onto another, transactional data updates rely on an Application Programming Interface, or API, to get the data from one system to another.

For those of you unfamiliar with the term, an API is a pre-established set of rules that different software programs can use to communicate with each other. An apt analogy might be the way a User Interface (UI) facilitates interaction between humans and computers. Using an API, data can be updated in real time, either on a record-by-record basis or in bulk. If a Company A wants to update a record in their CRM with fresh data from Company B, for instance, all they need to do is transmit a unique identifier for the record in question over to Company B, who will then return the updated information to Company A using the API.

Perhaps the best part of the transactional update architecture is that it can be set up to connect with the data pretty much anywhere it resides—in a cloud-based CRM solution or on a purpose built data warehouse sitting in your data center. For those using a cloud-based solution, a huge advantage of this architecture is that once a data provider builds hooks into popular CRM solutions, there are usually no additional costs for integration and transactional updates can be initiated in bulk by the CRM administrator, or on a transaction-by-transaction basis by salespeople themselves. It’s quite literally plug and play.

For those with an on-site data hub, integrating with the transactional data provider is usually pretty straightforward as well, because most APIs not only rely on standard Web technology, but also come equipped with easy-to-follow API keys and instructions. Setting the integration, in other words, can usually be implemented by a small team in a short timeframe and for a surprisingly small budget. And once it’s set up, it will pretty much run on its own. Problem solved.

Get Your PCRM On!

Never heard of PCRM? Well, that’s because it doesn’t exist—not yet, anyway. But it should. For those who are unfamiliar with Customer Relationship Management, or CRM, it describes a strategy for managing a company’s interactions with customers and prospects. The key to any CRM program is that interactions are with your customers and prospects—and that means you know something, usually a lot, about them.

Never heard of PCRM? Well, that’s because it doesn’t exist—not yet, anyway. But it should. For those who are unfamiliar with Customer Relationship Management, or CRM, it describes a strategy for managing a company’s interactions with customers and prospects. The key to any CRM program is that interactions are with your customers and prospects—and that means you know something, usually a lot, about them.

And as any experienced database marketer knows, knowledge means power—power to tailor the marketing message based on what you know or learn. Essentially, it’s a marriage of marketing and data. Unfortunately, however, many CRM programs miss the boat when it comes to taking advantage of this fact, and fail to communicate with customers and prospects on a 1:1 basis. Hence the need for Personalized CRM, or PCRM, instead.

Personalization is important because, let’s face it, we live in an age of information overload. According to an article in the New York Times published in 2007, at the time Americans were exposed to 5,000 ads a day—and it’s safe to say that number has continued to climb since. And unless you’ve been living under a rock for the past 10 years, this fact has been painfully obvious. For marketers, it’s meant a steady and inexorable decline in response rates across the board, in an increasingly futile attempt to get the attention of a distracted populace. How pronounced has the decline been? While a 3 percent response rate might have been the gold standard for a prospecting direct mail campaign 10 years ago, for example, today it hovers at around 1 percent, according to the DMA.

One effective strategy to cut through the clutter is personalization, or 1:1 marketing-a strategy you should be implementing across the board on all your CRM initiatives. Think about it: These are your customers and prospects, and you’ve captured tons a data about them. You know when they became customers, and how. You know what campaigns they’ve responded to, banners they’ve clicked, emails they’ve opened, and so on. You know their gender. You may even know their birthdays. So use this data to drive personalization!

When it comes to implementing 1:1 communications, the good news for marketers is two-fold. First, in our multi-channel world there are increased opportunities to add a personalized touch to your communication strategy; email, direct mail, landing pages and mobile can all be personalized based on your CRM data. Second and perhaps more importantly, the past few years have witnessed a proliferation of new and exciting technologies that make it ridiculously easy for rank-and-file marketers to communicate on a 1:1 basis, much of it not requiring any IT support.

Direct mail, for example, can now be personalized using Variable Data Printing (VDP) software, a technology used by virtually all digital printers in business today. Never tried it? Well, maybe it’s time you did, as the days of ‘spray and pray’ are long gone. And although VDP may be more expensive than traditional offset, the improved response rates can mean improved ROI. On the Interactive side, email marketing and demand generation software have grown up to the point where it’s a snap to personalize both images and text in an email message based on profile data, not to mention trigger multi-touch drip-marketing campaigns based on lead scoring.

When driving customers of prospects to the Web, keep in mind that a personalized landing page can convert traffic up to five times better than a generic Web page ever will. The fact is, keeping customers and prospects focused on the marketing message interlaced with personalized content is a winning combination.