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Amazon Customers who bought also bought socks
Searching for Analogs in a Digital World - example of marketing to individuals

For decades we have concentrated on marketing to a demographic; in the future we will be marketing to individuals. That entails a basic revision to the way we think of customers.

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Marketing to Individuals

It’s been over a year ago since I first blogged on the subject of Big Data, and I‘ve had time to further consider the fundamental changes an unbounded supply of consumer information will have on marketing. For decades we have concentrated on marketing to a demographic; in the future we will be marketing to individuals. That entails a basic revision to the way we think of customers.

First, let’s look at what Big Data won’t do (at least any time soon). We’re not going to be able to push a button and have a computer spit out the name and address of everyone ready to buy a pair of argyle socks, with a blue-black-teal pattern and in a polyester/silk/spandex blend. It will, however, identify those who are most likely to buy such an item based on whatever they’ve done, said, or has been said about them online. That is where the future of marketing lies. And it flips everything we’ve done in the past on its head.

Marketing by the Numbers: Finding  the Best Place to Fish

Demographic marketing adopts a macroscopic point of view. Through research, market data, or both, we develop profiles based on characteristics likely to be shared by prospective customers for our product or service, and create clusters with a higher-than-average potential for success. Like a fisherman who has his favorite fishing spots, we want to drop our hook in a place we know is more likely than others to result in a catch. We know that there are more fish swimming elsewhere in the lake, but since we can’t see them we’ll be content to fish where we believe the numbers are in our favor.

Marketing by Behavior: Stocking the Pond

Big Data promises to give us the equivalent of a sonar fish finder. Not only can we see exactly where the fish are, we can identify and go after the biggest ones in the lake. Being privy to an individual’s preferences and buying habits puts our marketing efforts on an entirely different basis. The process of narrowing the pool of potential targets based on shared demographic characteristics is inefficient. Now we can build our own pool of prospects from the ground up, based not on projected tendencies but actual behaviors. In essence, we get to stock the pond… and make it a relatively small pond at that.

Affinity vs. Analog

Demographics provide the ability to market to people based on their affinity with a particular group or groups. We might, for example, decide that the argyle socks I mentioned before will most likely to be sold to men, and market them that way. With Big Data, however, we can identify the individuals – male or female – with analogous past behaviors that indicate their likelihood of finding those argyle socks appealing.

The phrase “Customers Who Bought This Item Also Bought” will be familiar to anyone who has ever searched for an item on amazon.com. Look for anything online these days and you’re likely to be hounded by pop-up ads for similar products wherever you go on the Internet. And this is all based on a single behavior; imagine the potential of all of your behaviors being integrated into a single marketing profile.

The Emerging Face of Advertising

For my own profession, advertising, this represents a sea change. Traditional mass media and demographic marketing are inalterably entwined; two sides of the proverbial same coin. Profiling behavior, on the other hand, focuses on direct, one-to-one appeals through digital and social media. It allows us to make assumptions regarding related behaviors, test those assumptions, and refine them in real time.

Here’s a real world example. My agency is currently running an advertising and marketing campaign aimed at recruiting fire and EMS volunteers. Along with other media options, we are using Facebook ads geo-targeted at behavioral clusters with which we believe a civic-responsibility message will resonate. After studying behaviors widely shared by the existing volunteer population, we deployed ads based of relevant keywords. These included such terms as “church”, “bowling”, “NASCAR”, “kayaking”, and even “yoga”. Under-performing keywords were evaluated daily, and dropped in favor of those that were more successful. Results from this social media effort surpassed those achieved with more traditional, mass media.

This example is still functioning on the basis of only a single characteristic, but marketing to behavioral analogs is just in its infancy. Big Data will soon provide us with the ability to target multi-dimensional profiles. The more dimensions, the tighter the targeting — and the nature of advertising and marketing will be changed forever.

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