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Targeted Marketing: It’s Tough Getting Out of the Gate

January 8, 2015


Emily Steel (@emilysteel) reports that in the past few years hundreds — if not thousands — of companies have emerged that are selling marketing technologies. These technologies include real-time advertising using artificial intelligence, cross-screen targeting capabilities, and ad personalization.[1] These technologies, she writes, were meant to streamline “the process for creating, buying and selling ads across a proliferation of digital devices — and then instantly measure the effectiveness of marketing campaigns.” Instead of sharpening the focus of marketing campaigns, Steel asserts that the proliferation of marketing technologies has resulted in a lot of confusion. She writes, “Marketers report being more perplexed than ever before amid the proliferation of media and new technologies, along with growing uncertainty about whether or not digital marketing delivers business results.”


Marketers might be uncertain about whether digital marketing can deliver the goods, but apparently most of them have a gut feeling that it will. Steel cites a survey conducted by Adobe that revealed “two-thirds of marketers said that companies would not succeed unless they had a digital marketing strategy.” The challenge is finding a way to cut through the confusion and implement a digital strategy that makes sense. “The broader uncertainty becomes more vexing as marketers devote a larger share of their advertising budgets to digital media,” writes Steel. “Global digital ad spending is expected to surge 15 per cent this year to $138bn, representing about a quarter of total ad spending, according to research firm eMarketer. By 2018, digital is expected to capture about one-third of advertising budgets worldwide.” Adding to challenge of getting out the gate with a digital strategy is the urgency that companies are feeling. Rushed decisions are often bad decisions and bad decisions are costly.


Why the urgency? The simple answer is that consumer behavior is changing rapidly and most of those changes involve the digital path to purchase. More specifically, a growing number of consumers are using mobile technologies (especially smartphones) when making their buying decisions. Businesses that don’t adapt to changing consumer behavior are likely to go out of business. Entrepreneur Alan E. Hall (@AskAlanEHall) recalls meeting Jeff Bezos back in 1997 at an Ernst & Young banquet honoring young entrepreneurs.[2] Hall asked Bezos about his business and Bezos replied, “I have started a new business called Amazon. We sell books over the Internet.” Hall explains what happened next:

“I turned to my wife and prophesied that he would be out of business within two years. ‘Who would ever want to buy books over the web? We all visit our favorite bookstores when we want to buy books. We’ve done it for decades. Why does he think we will change our buying behavior?’ Now when my wife sees press about Amazon and Mr. Bezos she laughs. ‘Boy, Alan, were you wrong.’ Wrong indeed. Jeff not only sells millions of books, but everything else a shopper wants to buy.”

The business landscape looks nothing like it did back in 1997. Once thriving malls now lie vacant. Companies that had survived for decades are no longer in business. That’s why companies are feeling the urgency to change. In this new digital-path-to-purchase world marketers hoped that the arrival of big data analytics would create order out of chaos. As noted above, however, the introduction of so many different kinds of technologies added to the confusion. If that weren’t bad enough, getting to know and understand consumers has turned out to be a lot harder than people imagined it would be once the data started to be analyzed. John Lucker (@johnlucker), principal and global advanced analytics and modeling market offering leader, Deloitte Consulting LLP, notes, “Behavioral economists have found that consumers often act irrationally, in conflict with past behaviors and trends.”[3] Since targeted marketing is based on past behaviors and trends, this revelation is a bit unsettling. Lucker asserts that unexpected consumer behavior is nothing new. He explains:

“Time and again, consumers make emotionally-based buying decisions. Factors such as friends, family, online social networks, life experiences, group consensus, habits, lack of self-control, and ‘decision fatigue’ sway their behavior, often without them even knowing it. These factors lead consumers to move in directions that defy businesses’ expectations. Consequently, companies that subscribe to the notion of the always rational consumer risk misunderstanding the factors that motivate individual customers’ buying decisions. This lack of understanding may lead to missed marketing opportunities, customer churn, loss of market share, and declining revenue.”

Lucker insists that such behavior does not lessen the importance of big data analytics rather it makes them even more important. He explains why:

“Some companies are well aware that mercurial tastes and a variety of external influences sway consumers’ shopping decisions. But until recently, they’ve lacked tools that can help them make sense of — and profit from — irrational buying behavior. Regardless of whether they’re purchasing cars, insurance, clothes, or groceries, consumers regularly buy certain products — some planned, some spontaneous. Throughout their virtual and physical shopping journeys, and even in the course of their everyday lives, they emit ‘signals’ that offer companies a window into their needs, behavior, life stages, and buying patterns. … Within the constraints of privacy regulations, policies, and evolving perceptions of what consumer research deems ‘acceptable’ data usage, companies can combine traditional enterprise data with big data to discover and interpret these signals, and use business analytics to help understand the triggers that lead to specific buying propensities or outcomes.”

Lucker reminds us that “the goal of analyzing behavioral and transactional data is, of course, to better anticipate consumers’ needs and whims, and to create more effective products, services, and promotions that increase customer loyalty and enhance the bottom line.” Targeted marketing has a better chance of converting a looker into a buyer because the offers consumers receive through targeted campaigns are more relevant than traditional marketing approaches. “An added benefit of analyzing this data,” Lucker writes, “[is that] the results can help decision-makers overcome biases and assumptions that may be undermining performance.” He continues:

“Ultimately, deep analysis of customer biographic, demographic, and psychographic data can give companies a more accurate view of what makes customers tick and lead to better business outcomes. Although the factors that motivate customer behavior may not always make obvious sense, businesses can use analytics to derive statistical outcomes that can make more sense of the seemingly nonsensical.”

Michael Goldstein (@goldsteinmlg), a member of the global industry strategy and marketing group at Adobe, agrees that getting out of the gate with a digital strategy can be difficult. “So much hype surrounds big data that many media and entertainment marketers have become understandably overwhelmed,” he writes. “Some are not sure what its benefits are. Others think any endeavors involving big data analytics might be too complex or expensive to undertake.”[4] Goldstein recommends taking three steps that will help marketers get out of the gate. They are:


  • Acknowledge that the benefits associated with big data are substantial. Whenever consumers opt to provide personal information, they expect highly personalized, targeted exchanges with their favorite media brands.
  • Take a data inventory and determine what is already available. For media and entertainment companies, it is no longer enough just to consider age, gender, income, and location. Instead, it’s essential to go deeper within audience segments and consider such factors as social network activity, content engagement, ad exposure, and other online activities.
  • Set up a systematic, step-by-step process that lets research and marketing teams identify the data that matters and deliver it to people who can act on it.


That last step is the most important. You have to decide what you really want to accomplish and then determine what kind of data will help you gain insights that will help you reach your goal. Once you’ve done that, you should have an easier time selecting the technology that is best-suited to helping you achieve your objectives. In today’s fast-moving business environment, being left at the digitalization gate is not an option.


[1] Emily Steel, “Marketers are all over the shop,” Financial Times, 27 May 2014.
[2] Alan E. Hall, “Businesses must adapt to changing customer habits,” Standard Examiner, 9 January 2013.
[3] John Lucker, “Making Sense of Irrational Customer Behavior,” The Wall Street Journal, 11 November 2014.
[4] Michael Goldstein, “Why Big Data Is a Big Deal,” Digital Marketing Blog, 25 September 2014.

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