There's a funny scene in the television series Mad Men. Advertising executive Don Draper is having a tough time with the president of Belle Jolie lipstick, a prospective client. The makeup mogul rejects Draper's proposed advertising campaign.

Draper persists, however, and the executive finally comes around to Draper's way of thinking. "Nice work," Mr. Lipstick says. "I think you may be right about this."

"We'll never know, will we?" Draper coolly replies. "It's not a science."

There, in a nutshell, is the problem that has plagued advertising since before Coke was in cans. Everybody knows that ads can be effective. Getting down to the specifics is where things start to get fuzzy.

Advertisers need to understand how their campaigns drive sales—especially whether the ads are stimulating purchases that would not otherwise have occurred.

They need to know what brought customers through the door. Was it the slick television commercials? The radio spots? The circular in the Sunday paper? The direct-mail pieces? The online ads?

Further complicating things is that a retailer might have customers who fall into a dozen or more distinct categories: For example, one category might comprise extremely loyal customers; another, those who visit the store only during the holidays; a third, shoppers who respond solely to promotions; and so on.

It's a sure bet that each group responds differently to different kinds of advertising.

Another complication is the media's combinatorial effects. That is, Customer A may respond more to direct marketing after seeing a TV spot. Customer B, however, may be more likely to click on a banner ad after having received direct mail or having seen an item in a newspaper circular.

Gauging the return on marketing dollars spent is not new. Most big companies perform basic analytics to understand their ads' effectiveness. But they are almost always looking at the media independent of the customer dimension—they analyze television ads versus direct mail, for example.

That's fine, but it's much more valuable to understand how effective the television ads are doing, say, with extremely loyal customers in St. Louis. Or, how the direct mail is working with promotions-hungry shoppers in Atlanta. With so many customer groups and many media types, it becomes a very complex web to untangle.

Modern analytics can tell a retailer how well a product is selling with a certain category of customer in a specific market, and how badly with another group in another market. It can tease out crucial facts—for example, that the online ads are effective against one competitor but not another. It can recommend a robust defensive strategy aimed at maximizing revenue, such as running a print campaign targeting a specific set of customers in a specific market.

Analytics are especially useful in the burgeoning field of interactive ads delivered to shoppers' smartphones and other portable devices. The immediacy of those ads—their ability to spark impulse purchases—can be very powerful.

But to be successful, they must be personalized—the right ad aimed at the right customer at the right moment. A sophisticated analytics system can do just that by considering—in real time—each customer's preferences, past purchases, and habits, along with a wealth of other factors.

Such analytics techniques are increasingly prevalent in all aspects of business and life. Analytics help physicians diagnose diseases, and they enable transportation authorities to predict—and avoid—traffic jams. Manufacturing-plant operators rely on analytics to identify machines that are on the verge of breaking—so that they can be repaired before they fail completely and shut down the production line.

Now, forward-thinking advertisers are embracing those new technologies and so have a distinct advantage in the marketplace: They will have greater ability to pull in more revenue from current customers and attract new customers as well.

Advertising will never be a science. It is a creative endeavor and, in its fullest expression, an art form. But science can help marketers make more effective decisions about where to spend their advertising dollars. Furthermore, it can inform the creative team about which customers are most likely to be receptive to their messages and what makes those customers tick.

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The Key to Effective Advertising? Use Analytics to Make It Personal

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Dr. Michael Haydock is a partner, IBM Global Business Services (, and Worldwide Practice Leader, Customer Analytics—Business Analytics and Optimization ( Reach him via