6 Thorny Data Problems That Vex B-to-B Marketers, and How to Solve Them

B-to-B marketers are plagued by data problems. Business data is complex and fast-changing. Customers interact with us through a variety of channels, and often provide us with conflicting information. Our legacy databases are not as robust as we need. New tools and technologies emerge and must be evaluated. It’s a never-ending battle. To shed some light on B-to-B data problems, Bernice Grossman and I compiled a working list of problems and solutions. Here are some of the thorniest.

B-to-B marketers are plagued by data problems. Business data is complex and fast-changing. Customers interact with us through a variety of channels, and often provide us with conflicting information. Our legacy databases are not as robust as we need. New tools and technologies emerge and must be evaluated. It’s a never-ending battle. To shed some light on B-to-B data problems, Bernice Grossman and I compiled a working list of problems and solutions. Here are some of the thorniest.

  1. Data entered by our sales people ends up as mush. They don’t follow the rules; or there are no rules. That may be okay for the rep, but it’s not okay for the company.
    Here’s the best practice: Create a centralized data input group. Train and motivate them well. Give them objective rules to follow. Develop a simple method for testing the accuracy from this group as an ongoing practice. If this group cannot follow the rules, then the rules should be re-evaluated.

    Then, develop a very simple process by which reps pass their data to this group. Dedicate particular group members to certain reps, so the input person builds experience about rep’s behavior and communication style. The bonus: these two parties will team, build a valuable relationship, work together well, and improve data quality.

    Consider enabling the data input group with a real-time interface with a database services provider to prompt the standard company name and address. This can be an expensive, but very helpful, tool.


  2. How do I match and de-duplicate customer records effectively?
    Some approaches to consider:
    • Establish—and enforce—data governing rules to improve data entry, which will keep your matching problems under some semblance of control.
    • Find a solid software vendor with a tool specifically designed to parse, cleanse and otherwise do the matching for you. Test a few vendors to find the one that works best with your data.
    • Create a custom matching algorithm. As a place to start, ask several match/merge companies to show you examples of the results of their algorithm against your data.
  3. When data elements conflict in my house file, how do I decide which is the “truth”?
    The short answer is: by date. The most recent data is the one you should default to.

    But also keep in mind when importing data to enhance your records that appended data will always have its limitations, and is best viewed as directional, versus real “truth.” Be careful not to build targeting or segmentation processes that are primarily dependent on appended data.

    You could consider conducting an audit to validate the quality of your various append sources. (This is usually done by telephone, and it’s not cheap.) Then you can add a score to each appended element, based on its source, to manage the risk of relying on any particular element.

  4. Which corporate address should I put in my database? There’s the legal address and the financial (banking) address, which may be different. Or there may be a street address and a P.O. box address. Equifax and D&B often supply the financial address. The address to receive proxies is different from the address to receive advertising mail. How should I sort all this out?
    As a marketer, your concern is delivery. You care about a bill to and a ship to. Focus on the address where mail and packages are delivered.
  5. Measuring the impact of each touch in our omnichannel world is driving us nuts. Any ideas?
    The attribution problem has heated up recently, fueled by the rise of digital marketing. But it’s really nothing new. The traditional attribution methods of assigning the credit have long been either the first touch (the inquiry source medium) or the last touch (the channel through which the lead was either qualified or converted to a sale). Marketers are in general agreement today as to the deficiencies of either of these traditional methods.

    Digital marketers are experimenting with various approaches to the attribution problem, like weighting touches based on stage or role in the buying process, or by the type of touch—attending a two-hour seminar being weighted more heavily than a content download.

  6. How should I handle unstructured data, like social media content. All this “big data” stuff is getting bigger, and meaner, every day.
    User-generated social media content may offer valuable insights into customer needs and issues. But marketers first must think through how they will use the information to drive business results. First you must develop a use case. Then, you must develop a way to attribute the information to a record. For example, one method to allow the match is collecting multiple cookies to find an email address or other identifier. There may be situations where you want to track sentiment without attributing it to a particular customer but to a group, like large companies versus small. In either case, we suggest that you test the value of the data before you put a lot of time and money into capturing it in your marketing database.

You can find more thorny data issues and solutions in our new whitepaper, available for free download. Please submit your issues in the comments section here, and we’ll be happy to suggest some solutions.

A version of this post appeared in Biznology, the digital marketing blog.

Chicago With a Purpose: Wrapping up the DMA2013 Session Picks

With apology, I want to say that this blog is a little about me—what topics I’m interested in, and sharing a little bit of this knowledge (or lack of knowledge) with blog readers. In the process, I’m hopeful you’re doing the same bit of pre-conference research—because it is this forethought and planning, beyond the engagements and booth visits on the Exhibit Hall floor, which make for a truly informative DMA13 conference

With apology, I want to say that this blog is a little about me—what topics I’m interested in, and sharing a little bit of this knowledge (or lack of knowledge) with blog readers. In the process, I’m hopeful you’re doing the same bit of pre-conference research—because it is this forethought and planning, beyond the engagements and booth visits on the Exhibit Hall floor, which make for a truly informative DMA13 conference

With the Direct Marketing Association Annual Conference starting literally at the end of this week, I’m still at it here lining up MyDMA2013 schedule with sessions I’d like to attend—admittedly doing some double-booking because of the great, comprehensive content on offer.

Yes clients and professional colleagues are on hand, and I’ll be sitting in on some of their sessions—but my guideposts for session picks are simply the subjects to which I welcome new learning, new updates and state-of-the-art in data-driven marketing such as it is. That’s why “The DMA” is always a conference attendance “must.”

A few weeks back, I cataloged some of first-impression session and events picks here: http://targetmarketing.adweek.com/blog/creeping-up-fast-dma13-making-plans-chicago

I’m hopeful our paths will cross in Chicago as I add 10+1 to the session wish list here…

  1. Who drives client relationships and customer engagement today? Advertising. “Mad Men + Data Specialists: When Two Worlds Collide,” Tuesday, Oct. 15, 9 a.m. to 9:45 a.m.
  2. Follow the money (and media) trail… “Outlook 2014: Data Driven Marketing in an Omnichannel World,” with The Winterberry Group’s Bruce Biegel, darnnit, also Tuesday, Oct. 15, 9 a.m. to 9:45 a.m.
  3. And trending too, “B2B Trends in 2014” with SAP’s Jerry Nichols, B-to-B magazine’s Chris Hosford and leading biz marketing consultant Pam Ansley Evans: Monday, Oct. 14, 11:15 a.m. to 12:15 p.m.
  4. “The Big Data Ecosystem: Informing Effective Marketing Campaigns,” with Time Warner Cable—curses, also yet again, Tuesday, Oct.15, 9 a.m. to 9:45 a.m. This is really a parochial pick, since my apartment building is now allowing RCN to enter my building—and I’m curious to see (finally) if TWC will give me a better deal on pricing its services.
  5. Multichannel (yet digital) ROI—too bad we don’t have offline here, too, but it has some client-side folks, “No BS, Strictly ROI: Definitive Case Study Panel on Successful Multichannel Digital Marketing” with Intercontinental Hotels Group, Travel Impressions, Equifax and FedEx, Wednesday, Oct. 16, 9 a.m. to 9:45 a.m.
  6. Pinterest + Email = Customer Engagement, with Sony and (disclosure, former client) The Agency Inside Harte-Hanks—now here’s a social media case study that taps Pinterest users, first I’ve seen in a venue that I’ve attended, Tuesday, Oct. 15, 11:30 a.m. to 12:15 p.m.
  7. “Creative Masterclass” with “THE” Herschell Gordon Lewis, and it won’t be a horror film classic (one of Herschell’s other talents), but I know it will be entertaining, focusing as it will on word choices and testing with minimal waste. Afterall, we all should test and choose our words carefully, on Monday, Oct. 14, 11:15 a.m. to 12:15 p.m.
  8. “USPS Goes Mobile: Direct Mail Integration with Mobile Technology”—hey this is a postal-focused blog, and USPS is offering postage discounts here, so there is money to be made/saved: Monday, Oct. 14, 3 p.m. to 4 p.m.
  9. Evaluating marketing service providers—”Why You Must Look at Least Three: Solutions Showdown.” Yes Bernice Grossman—database marketing extraordinaire—has lined up Neolane, SDL and IBM to help us evaluate and compare leading trigger-marketing vendors, on Tuesday, Oct. 15, 2 p.m. to3 p.m
  10. The elusive attribution question gets answered, at least by Petco: “Power-Up: How Petco Uses IBM Marketing to Drive Attribution.” OK, this is an IBM-sponsored track on real-time and automated marketing, but I know many brands struggle with attribution assignment in multichannel and omnichannel environments, so I’d like to hear this case study, Monday, Oct. 14, oh well also 3 p.m. to 4 p.m.
  11. AND a BONUS: Speaking of real-time marketing, my editor Thorin McGee at Target Marketing, is moderating his own panel on “Real-Time Marketing: Tools and Techniques to Own the Moment,” on Wednesday, 10 am – 10:45 am. Do I get extra credit for mentioning this one? Afterall, this blog post was a bit behind his deadline—though I’m hopeful it will be posted on time!

See you in Chicago!

Facebook Embraces Direct Response

Facebook dominates the Web, but it’s never really cracked the direct response puzzle. That looks like it will change in 2013 with an avalanche of new measurement and targeting tools. As a marketing platform, Facebook has traditionally thrived at top-of-the-funnel advertising. Unlike search, which hits people just as they express an interest in buying a certain product or service, social media marketing at its best builds relationships, and there’s compelling evidence for its value.

Facebook dominates the Web, but it’s never really cracked the direct response puzzle. That looks like it will change in 2013 with an avalanche of new measurement and targeting tools.

As a marketing platform, Facebook has traditionally thrived at top-of-the-funnel advertising. Unlike search, which hits people just as they express an interest in buying a certain product or service, social media marketing at its best builds relationships, and there’s compelling evidence for its value.

The heavy lifting for this type of advertising, however, happens on the advertisers’ own media—their brand pages. Although Facebook doesn’t charge for brand pages, it can still make money from them by selling ad units that encourage users to become fans, or that amplify the reach of content shared on the page. In a lot of ways, these are straight direct response ads, but with a call-to-action for a “like” or “share” and not a sale.

Showing marketers how many likes or conversations an ad produces is one thing, but proving ultimate sales is another, much more difficult job. Because Facebook advertising traditionally operated high in the funnel, the platform has long suffered from a “last-touch” bias. Click rates and conversions probably underestimate the actual impact of advertising on the Facebook platform, especially for the small display ads that appear to the right of the newsfeed. If people see an ad while they’re checking in on their friends, they may not click. Or they may click on it and do nothing. Later, however, they may decide to go to the website or a store and make a purchase. It’s often this last channel that gets outsized credit for this sale.

Overcoming this last-touch bias has become an imperative for Facebook. First of all, Facebook has developed “sponsored stories,” a native ad format that appears in the newsfeed and refers to how a friend interacted with a brand—becoming a friend, commenting on an article, redeeming an offer, etc. They still pivot off the relationships within Facebook’s social graph but have much higher CTRs and engagement. With these ads, Facebook has a more powerful format, where CTR becomes their ally as opposed to an obstacle.

Facebook is also trying to move down the purchase funnel by giving advertisers the ability to reach people who have already shown interest in a brand. Last year, Facebook introduced two new advertising products that do this. Custom Audience targeting lets advertisers upload their proprietary lists and match them with Facebook users to deliver sponsored stories or standard display ads to their existing customers. Early results show that these custom lists produce higher CTR and lower cost-per-lead. In February, Facebook reached an agreement with big data aggregators Epsilon, Axciom, BlueKai and Datalogix to import even richer audience segments.

Ulitmately, an even more important innovation might be Facebook Exchange, which allows marketers to retarget ads on Facebook. Through cookies and other tracking tools, Facebook can identify which websites users have visited—and even specific products they’ve browsed—and then deliver ads based on this information. Although the exchange is still in its early stages, it too has shown promising results.

Through Custom Audiences and its Exchange, Facebook is digging deeper into the buying process, but its big challenge remains attribution. It needs ways to span the gulf between advertising on the Facebook platform and the ultimate actions it produces. Custom Audiences and the Exchange have shrunk the width of this gulf but haven’t eliminated it—and its advertising team knows it.

That explains why Facebook bought Atlas Solutions from Microsoft right at the end of February. The ad server enhances Facebook’s ability to track online purchases. In announcing the service, Facebook’s Head of Monetization Product Marketing Brian Boland said, “Why we’re doing this is not to launch an ad network, and why we did do this is to improve measurement. We heard loud and clear from advertisers that they want to understand multi-touch attribution instead of just looking at the last click.” With the ad server, Facebook can deliver more types of ads to more publishers and, most importantly, it can effectively follow what users do online. It’s an incredibly powerful tool for online attribution.

It is made even more powerful when paired with Facebook Connect, a plug-in for online publishers that lets visitors log in to a website with their Facebook email and password. The service gives websites a simpler login process and gives them access to a rich layer of biographical information and connections that Facebook has amassed. Facebook, in turn, can see what people are doing all across the Web, not just in their walled community and, importantly, it can track activity across multiple devices, as long as a user has logged into Facebook from that device. If you see an ad on your desktop but convert via your phone or tablet, Facebook can track the activity.

Combining Atlas and Facebook Connect produces a powerful suite of online measurement tools. With a partnership with Datalogix, it can even track activity offline via loyalty cards and email addresses collected at checkout. With these tools, Facebook seems positioned to fully “close the loop” and overcome the last-touch bias. In classic direct marketing fashion, they also let Facebook better optimize who receives advertising. If you know who’s bought your products, you’ve found a great audience for future purchases.

Better measurement tools and advertising formats with higher click-rates transform Facebook into a legitimate direct marketing player. With Facebook experimenting with a slew of new DR formats and tools, including trigger-based Gifts, the social search tool Graph Search, redeemable Offers, and its gift card called—what else—Facebook Card, Facebook seems finally to have embraced it inner direct marketer.

Attribution and the ‘Mail Moment’ in the Multichannel Mix

At its Sept. 13 meeting, the Direct Marketing Club of New York hosted an engaging panel discussion regarding the use of direct mail in a multichannel world, and the panelists included representatives from Citigroup, Gerber Life and The Agency Inside Harte-Hanks. … Hearing from two financial service brands, and an agency that services brands in several markets, packed the house. I’m not sure if it was the topic or the brands who spoke, or both, that was the draw—but the information imparted prompted lots of audience interest and questions.

At its Sept. 13 meeting, the Direct Marketing Club of New York (DMCNY) hosted an engaging panel discussion regarding the use of direct mail in a multichannel world, and the panelists included representatives from Citigroup, Gerber Life and The Agency Inside Harte-Hanks.

The representatives included Linda Gharib, senior vice president, digital marketing, for Citi’s Global Consumer Marketing & Internet division; David Rosenbluth, vice president, marketing, Gerber Life Insurance Company; and, from the agency side, panel moderator Pam Haas, who is both vice president, sales, for agency services at Harte-Hanks (and first vice president for DMCNY), and Michele Fitzpatrick, senior vice president, strategy and insight, The Agency Inside Harte-Hanks.

Hearing from two financial service brands, and an agency that services brands in several markets (tech, consumer package goods, automotive, insurance, pharma and more), packed the house. I’m not sure if it was the topic or the brands who spoke, or both, that was the draw—but the information imparted prompted lots of audience interest and questions.

First, customer acquisition—at least in the financial services area—still appears to be very dependent on mail. At Gerber, Rosenbluth said, as many as a third of new business policies are still generated by direct mail, even as the brand is “omni-channel”—digital (including web site, search, display ads, email), direct-response television, as well as direct mail. For Citi, the brand is positioned No. 2 in the nation by Target Marketing in its “Top 50 Mailers” ranking for 2012 (which is ranked by overall revenue, not mail volume), Gharib said, solidifying its importance in both acquisition and retention.

Fitzpatrick agreed, noting that in financial services, where marketing is modeled most precisely for risk and performance, direct mail remains an acquisition workhorse, particularly on new product launches. For automotive and pharma verticals, however, where as much as 80 percent of transactions are researched anonymously beforehand online, digital media is used for hand-raising, and direct mail may be then used to deliver a brochure of other information in a highly segmented way to close the deal. “Consumer preferences [for media] are situational,” Fitzpatrick said.

Who gets credit for attribution, when a multichannel communications mix produces a desired response? At Citi, Gharib said, such discussions are a “work in progress,” where the final interaction point currently gets the credit, whether that is chat, direct mail, email or some triggered communication. Adding to the multichannel attribution discussion is the mix of advertising purposes—some are pure branding messages, while others are intended to elicit a response, but both may compel or influence customer behavior in some discernible (or indiscernible) manner. Hence, there is complexity in the attribution discussion.

Yes, indeed, says Rosenbluth, where “allowances” are given for each channel in regard to the brand’s most importance metric to manage: total costs to convert a policy. Currently, “last touch” gets the attribution on response, but the policy conversion metric is the bigger-picture measurement, where everyone gets to take some credit.

Fitzpatrick pointed to recent Forrester research where “fractional attribution”—first touch, mid-touch and last-touch on the path to purchase share credit—and “engagement” is modeled, rather than response (alone). Every brand should undertake a channel impact study to determine, as best it can, the impact of incremental sales as a result of a multichannel customer experience, while also researching receiver reaction research. Clearly, direct mail, email, chat and other channels can be both or either “conversation starters” and “conversation extenders,” but analytics is the only way to know the role of the channel for any given customer.

“There’s credibility in paper,” Gharib remarked, “that helps with both the brand and its consideration.” Where email is cluttered, direct mail largely is not.

At Gerber, Rosenbluth, there really is no brand spend, all market spending is intended to produce engagement.

Fitzpatrick sees almost all “below the line” spending getting a branding blend—branding and direct marketing have come together. All the panelists agreed: it’s really about the consumer experience across channels, and having a database that enables customer recognition and a full customer view. Having tons of data is not enough—it’s having technology and processes in place for customer data integration and analytics to create smart engagement rules.

The verdict? Direct mail is and will remain a vital part of the media mix—because it’s an anchor in the consumer’s experience and brand consideration mix. As digital gets more clutter, boy that mailbox is looking pretty.

4 Attribution Models in the Age of Big Data

For marketers, attribution is the Holy Grail. For those unfamiliar with the term, attribution means determining what marketing channel or budget was responsible for generating a particular action. Without proper attribution, it’s pretty darn difficult to perform any kind of meaningful ROI calculations on your marketing spend. In fact, I wrote another post about attribution earlier this year or so ago titled “The ‘A’ Word—Learn It, Love It, Live It!,” which pointed out that in today’s marketing world, attribution isn’t always what it’s cracked up to be.

For marketers, attribution is the Holy Grail. For those unfamiliar with the term, attribution means determining what marketing channel or budget was responsible for generating a particular action. Without proper attribution, it’s pretty darn difficult to perform any kind of meaningful ROI calculations on your marketing spend. In fact, I wrote another post about attribution earlier this year or so ago titled “The ‘A’ Word—Learn It, Love It, Live It!,” which pointed out that in today’s marketing world, attribution isn’t always what it’s cracked up to be.

Now it’s no secret that attribution analysis is rather difficult to perform in an age of proliferating media, multichannel customers and, drum roll … Big Data. Think about it, how do you gauge which marketing channel was responsible for generating a sale when a customer was sent and read an email, received a direct mail piece and visited a microsite, Googled the company name and found the homepage, but clicked on a sponsored link leading to a landing page, went to and Liked a Facebook page, became a follower on Twitter, tweeted about it to his friends … and ultimately made a purchase using an App on an iPhone. Which channel gets credit? Email, direct mail, organic SEO, mobile, social? All of them? None of them? Some of them? It’s enough to make your head spin.

Now enter Big Data. In this column, I’ve written extensively about the challenge to marketers posed by Big Data. I know, it’s the meme du jour … seems like you read about it everywhere you go these days. Basically, Big Data is the massive accumulation of information that’s taking place across organizations as they market and engage with their customers and prospects across an ever-expanding proliferation of channels.

As customers and prospects interact with firms across different channels, the data continue to pile up. It’s this deluge of information and how to make sense out of it that is being referred to as Big Data. But, as I’ve written before, Big Data is really the problem—not the solution, per se. The fact that organizations are collecting all of this information is great. It’s what they are doing (or not doing, as you’re about to see) with it that’s most important.

I recently read a study done by the Columbia Business School and the American Marketing Association titled “Marketing ROI in the Era of Big Data.” The study was a survey of 253 corporate marketing decision-makers, director-level and above, at large companies. The results were striking.

They found that 91 percent of senior corporate marketers believe that successful brands use customer data to drive marketing decisions. OK, fair enough … couldn’t agree more. But, among those who are collecting data, a measly 39 percent admit they’re actually unable to turn this information into actionable insight. Pretty surprising, huh?

That’s not all. A whopping 65 percent of marketers admitted that comparing the effectiveness of marketing across different digital media is “a major challenge” for their business. An astounding 57 percent of marketers are not basing their marketing budgets on any ROI analysis whatsoever. And to add insult to injury, 22 percent are using brand awareness as their sole measure to evaluate their marketing spend. That’s right, as their sole measure. A direct marketer by trade, I almost spit out my coffee when I read that last stat.

But the shocking thing is based on my experience, I do not find this to be out of the ordinary. In fact, I met with one client recently and was shocked to learn that the client had basically thrown in the towel when it come to defining attribution, and had created hyper-simplistic ROI analysis by using a control customer group to whom the client didn’t market at all, and compared how much this group bought against the rest. Sounds pretty wonky, right? The crazy part is that even the simplistic model is astronomically better than the 57 percent who don’t even bother with ROI in the first place.

So, what are some solutions to the attribution conundrum? Well, there are several popular models that marketers are experimenting with, and each one of course has its plusses and minuses.

1. First-click attribution—credits the channel where a customer first engaged with the firm. On the plus side, this model actually attempts to discern where the customer journey actually began. The downside is that in today’s environment where marketing is often run in silos, it can be challenging to track customer engagement in a multichannel manner.

2. Last-click attribution—credits the channel where the last action took place (i.e., where the conversion occurred). On the plus side, this model is super easy to track. The downside is that it only measures the channel that’s best at generating the sale itself, and completely disregards how the prospect was initially brought into the fold.

3. Equal-weighting attribution—tracks all of the touchpoints where the customer engaged with the firm, and gives them all equal weight in terms of generating the conversion. The advantage of this model is that it takes a holistic view of the customer-vendor relationship. At the same time, this model overlooks the disproportionate role one channel may play over another.

4. Custom-credit attribution—a hybrid model created by the marketer based on its marketing strategy, customer base, and so on. If done right, a custom model can be highly effective, as it’s designed based on facts on the ground. The only downside is, well, you’ve got to create and test it—which is often easier said than done!

Okay, guess I’m out of room for this post, so I’ll end it here. In any event, I’d love to hear about what if any attribution model you’re been using, how it has worked out, and so on. Let me know in your comments.

— Rio

The ‘A’ Word—Learn It, Love It, Live It!

I attended a seminar earlier in January held by the Direct Marketing Club of New York titled “Annual Outlook: What to Expect in Direct & Digital Marketing in 2012.” The main speaker at the event was Bruce Biegel, managing director at the Winterberry Group, a strategic consulting firm that focuses on advertising and marketing.

I attended a seminar earlier in January held by the Direct Marketing Club of New York titled “Annual Outlook: What to Expect in Direct & Digital Marketing in 2012.” The main speaker at the event was Bruce Biegel, managing director at the Winterberry Group, a strategic consulting firm that focuses on advertising and marketing.

For those of you who have never before attended an event where Biegel presents, I highly recommend attending one if you get a chance. He’s a highly engaging speaker with many interesting insights gleaned from years of experience in the field, and backed by the research and analytics of the Winterberry Group.

The focus of the presentation was a review of the marketing and advertising world of 2011, along with some predictions for 2012. According to Biegel, 2011 was the year in which many firms intensified their focus on reporting and analytics tools. For 2012, he predicted many marketers will finally begin to pursue true multichannel integration across their firms, driven by data, analytics and the quest for cross-channel attribution. He touched on the term attribution repeatedly, referring to it as the “Holy Grail” of multichannel marketing.

In a marketing sense, I define attribution—or the “A-word” for the purposes of this blog post—as the act of determining what marketing channel or budget was responsible for generating a particular action: be it a click, lead, order, etc. As a direct marketer, I just love this word. And you should, too. Attribution is where the rubber meets the road. Attribution is what separates the men from the boys, the measurable from the immeasurable, direct response from … well, branding. Not to disparage brand marketing, but I think I can speak for most—if not all—colleagues in the industry when I say that demonstrable attribution is really what has always separated direct response marketing from branding—analytics that essentially give us the ability to calculate the actual ROI of every precious marketing dollar we spend. Enough said.

But, let’s face it, there’s a dirty little secret in the direct response community that those outside of it might not necessarily be aware of. The fact is that attribution has not been all it’s cracked up to be over the past 10 years—and a far cry from an exact science, to say the least. We have the Internet to thank for that. To elaborate, let’s take a moment and turn back the clock around 15 to 20 years, and think back to a time in which the Web did not play such a prominent role in our lives. Back then, most direct response marketing was done via direct mail, catalogs and inserts, as well as DRTV. In this relatively simplistic world, customers could only really place orders using the return mailer or by calling a toll-free number. That was it. Since each piece was stamped with a keycode, attribution was as easy as: “Could you please tell me the five-digit code on the bottom right-hand corner of the order form” … and we knew with certainty why the sale originated.

Then along came the Web—and, with it, an entirely new channel for consumers to interact with their brands. And this is when things got confusing. Let’s say, for example, a consumer received a postcard or catalog from a company. In place of calling the toll-free number, he could instead go to Google and search for the website, find it, locate the products he’s interested in and place an order. Now who gets the credit for the sale? The direct mail team? The search engine marketing team? The catalog team? The email team? All of them? None of them? The fact is, there was really no scientific way to tell for sure. The gears of attribution broke down, creating a vast gray area of uncertainty where the worlds of traditional and new media converged. This was the direct marketer’s dirty little secret in the age of Web 1.0.

To deal with this mess, new techniques and technologies invariably emerged to bring some order to the chaos. Before long, many marketers turned to the concept of campaign-specific landing pages to send their cross-media (or cross-channel) customers to. At least this bypassed the regular website and kept and sales or leads it made in one bucket, separate from the home page and other Web traffic. This was a huge improvement.

Then other technologies like personalized URLs, or PURLS, entered the mix. Gimmicks aside, PURLs work because they are a tool for attribution—not because they give someone a link made out of their name. Sure, giving someone a personalized link is nice … but that’s only window dressing and obfuscates the real value of this cross-media technology. PURLs help marketers attribute activity to the direct mail channel. That’s it in a nutshell. Now of course, there are additional benefits, such as improved Web traffic rates resulting from personalized content, and higher website conversion rates due to a simplified workflow on a landing page that’s been optimized for this purpose alone. But the real value of this technology is attribution—and don’t ever let anyone else tell you otherwise.

Similarly, across other channels useful cross-media technologies emerged like QR Codes, which really solve in mobile the same issue marketers face on desktop Web browsers—namely, the inability to properly track and attribute cross-media actions resulting from their offline campaigns. When push comes to shove, sending individuals to purpose-built, mobile-optimized landing pages, personalized or not, enables precise tracking and measurement, not to mention a better overall user experience and, presumably, a higher conversion rate, too.

Looking forward, the next stage in attribution will most certainly need to deal with the advent of Web 2.0 and the world of social media. Seeing as firms are now making investments in social media strategy, CMOs are going to want to attach some kind of ROI calculation to the mix. Now, of course, you could pretty easily argue that it’s absurd to try to assign any type of ROI to social media in the first place. In that vein, Scott Stratten has a great blog post called “Things We Should Ask The ROI Question About Before Social Media” on UnMarketing that does just that pretty convincingly. But that’s an argument for another time and place. Regardless of whether you feel it’s a smart policy, I think it’s safe to say that where the marketing dollars go, pressure will ultimately follow to show value (ROI).

At the same time, regardless of what dollars are being spent and how these expenditures make CFOs hyperventilate, social media can and do generate sales for organizations. This is an indisputable fact and should not be up for debate anymore. What is in question is the ability of firms to track what happens in social media and attribute the activity to this emerging channel. As we speak, we’re starting to see the introduction of the first generation of effective tools (SocialCRM) that track social media interactions among pools of prospects or leads, and make them available to marketing teams for actionable analysis and follow up. Very cool stuff. But, of course, social media data are only one piece of a much larger puzzle, named “Big Data.” I briefly touched on Big Data in a previous post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey.”

Actually, on that note, I think this is a good place for me to call it a day. Not only am I running out of space for this post, but that last thought will make a great segue to my next post, which will address the amazing transformation that is taking place within many firms as they deal with the endless volumes of unstructured data (Big Data) they are tracking and storing every day. 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 data are stored, such as CRM/SocialCRM platforms, social media websites, marketing automation tools, email software, Web servers and more. Stay tuned next time for more on this topic.

Until then, I welcome any questions, comments or feedback.

The Database Marketer Superhero: Expanded Role, Big Impact

Riddle me this, Batman: What sort of marketing strategies today require deeper, strategic database insight? Not so puzzling, is it? Pretty much everything a marketing team does today is driven by data — e.g., digital outreach, content, media, attribution, return on investment analysis, lead nurturing, PR and social community participation. In fact, the list would be shorter if we tallied up those marketing functions that don’t benefit from data-driven decisions.

Riddle me this, Batman: What sort of marketing strategies today require deeper, strategic database insight?

Not so puzzling, is it? Pretty much everything a marketing team does today is driven by data — e.g., digital outreach, content, media, attribution, return on investment analysis, lead nurturing, PR and social community participation. In fact, the list would be shorter if we tallied up those marketing functions that don’t benefit from data-driven decisions.

Database marketers were traditionally the geeks of the marketing department. They kept to themselves, ran queries to answer questions posed by other strategists, and worked hard to keep data clean and updated. Today’s database marketers are part of an emerging and essential marketing operations team that’s driving a lot of brands’ strategies. One marketer said to me recently, “Whomever knows the customers best gets to make the call.” Who knows your customers better than the people working with the data every day? All of a sudden, database marketers are superheroes — or at least have the opportunity to wear capes if they choose to accept the challenge.

There are two factors driving this trend, one being consumer habit. Given the ability and choice to interact with brands in many ways and across many channels, consumers are taking full advantage. It’s a me-centered consumption world where customer preference and whim create habits. At the same time, marketing automation technology is advancing and data integration is possible. Marketers can track and, more importantly, react to customer behavior in order to meet needs across channels.

Consider these five initiatives that have become imperatives for many chief marketing officers today:

1. Obtain a 360-degree view of the customer. One B-to-C marketer told me that there are more than 25 ways customers can interact with her brand, from a kiosk to a store counter to email to mobile commerce to branded website to call center to social communities. Most consumers participate in three or more of those channels. Communications can only be optimized if those habits and experiences are captured — and actionable — in your database.

2. Respond to customer behavior in the channel where the interaction occurred. This also has to be aligned with self-selected preferences.

3. Select the optimal channel for your next offer. A hotel owner uses past booking behavior to send last-minute alerts via SMS to those who have opted in and accessed the brand’s mobile commerce site. All others get the information via email. Response has boosted overall 8 percent.

4. Outline personas representing key customer segments. Do this in order to profile audience types and improve communication messaging and cadence.

5. Test and optimize your mix of channels for lead nurturing campaigns. For a live seminar event, one B-to-B marketer emailed reminders and offers based on interaction with previous email campaigns. Those who didn’t respond got simple reminders on date, location and keynote speakers. Those who did respond got more robust offers. Revenue from the offers increased 50 percent over the previous year and spam complaints dropped 25 percent. This is surely because those who demonstrated a willingness to engage prior to the event were nurtured with offers that made sense to their actions, and the others were left alone.

I’m sure there are infinite variations of these opportunities. Perhaps you’re testing some of them now. It will also be great to see how database marketers react to this new level of attention and interest from the C-suite. Will you embrace it and join the strategists, or will you run back to the corner and take orders?

How are you and your team embracing the need for a data-driven marketing approach? Please tell us by posting a comment below.

Attribution is the Word of the Day

I’ve just returned from a few days in sunny Florida, attending the Direct Marketing Association’s Retail Marking Confernce 2010, and the main takeaway I received from it was that multichannel retailers today are struggling with attribution.

I’ve just returned from a few days in sunny Florida, attending the Direct Marketing Association’s Retail Marking Conference 2010 (RMC), and the main takeaway I have from the event is that today’s multichannel retailers are struggling with attribution.

Attribution is determining which of your marketing vehicles is reponsible for generating consumers’ purchases. And it doesn’t have to be all or nothing. For example, a catalog and search can share credit for a sale.

While attribution in the retail world is often viewed strictly as a way to figure out which online marketing programs — e.g., search, affiliate or display, social media — are responsible for the most sales, it also refers to figuring out which sales channel (online or off) are bringing in the most dough.

It’s a tricky thing: Old-line catalogers at the event claimed catalogs drive more online sales than websites or search efforts. E-commerce guys, on the other hand, said websites are where sales occur, so attribution should be credited to them. Email marketers were in the mix, too. They believe email messages received by opt-in consumers are the main driver of in-store and online sales.

Attribution is even more important these days, as corner offices are closely watching marketing teams, who are operating with tighter budgets, to see if spending is being accurately assigned.

The issue of attribution was discussed in several sessions at the RMC. A preconference intensive session led by Al Bessin, a partner at multichannel direct marketing firm LENSER, for example, discussed how customer and transactional information from multiple sources, such as website reports, email service providers and order management systems, can help marketers figure out which channels are working to ensure they’re spending their marketing budgets in the best ways possible.

Attribution was also discussed by Chad White, research director at Smith-Harmon, a Responsys company, in his his closing keynote.

White correctly identified attribution as the missing link, citing an Epsilon study that found 33 percent of permission-based email recipients said they usually visit a brand’s website directly after receiving an email about that brand, instead of clicking on an email link. So, he said, “online conversions attributed to email may be undercounted by as much as 50 percent.”

White also discussed an attribution experiment performed by REI, the outdoor gear merchant. In an effort to test email attribution, REI withheld emails from a certain group of customers while continuing to send them to another, and began monitoring sales. When the test was completed, REI discovered it was overstating the impact of email on online sales since a good portion of customers still bought even without receiving an email.

However, White said, “after determining email’s impact on store sales, which email previously got no credit for, REI discovered that email contribution to total sales was actually twice the level of cookied sales.”

So what’s the answer? Which channel drives the most sales? It’s really hard to tell, and it’s not an exact science. Whether you’re at a large company that has the resources to institute an attribution modeling system or a smaller company that performs witholding tests, it’s still a crapshoot, in my opinion. How can you really know why a customer decides to buy something?

How do you handle attribution? I’d love to hear from you.