How to choose your targets carefully

Marketing is all about targeting. That is nothing new, and even people who don't call themselves marketers understand the concept reasonably well. But what constitutes a viable target is constantly in flux. What was once a clearly defined target is now far too broad for most uses. The advances in behavior tracking and data mining have turned targeting from a demographic exercise into a science in its own right.

Marketing professionals who've been around for a while often speak in wistful tones about the "good old days" when one television spot running on Thursday nights could capture 90 percent of consumers. The extreme fragmentation of media, and the addition of media elements not even thought of 20 years ago, has changed things, to say the least. Even so, it's not uncommon to hear agency creative teams talk about the television spot as though it was still the anchor point of the campaign.

It hasn't been all that long -- less than 10 years in fact -- since a useful media target description went something like this: women, 18-49, working outside the home, with kids living at home. That sounded pretty good in 2005, and many hundreds of millions of media dollars were spent going after that target. But as media has become more fragmented, targeting has gotten more specific.

In his book "The Power of Habit: Why We Do What We Do in Life and Business," author Charles Duhigg recounts a story about mass merchant Target and its capabilities that hit a little too close to home for one family. The company was able to successfully identify a customer as being pregnant based on her purchase behavior and sent her marketing materials promoting baby-related products. Unfortunately, the girl's father wasn't aware of the coming grandchild and was initially upset, and ultimately embarrassed.

But Duhigg's book isn't really about media targeting; it's about habits and how much we humans are slaves to our habits. Major life-changing events, such as having a child, are opportune moments for habit change, and Target was just trying to make the most of the opportunity. The bigger message for marketers is that given enough data and the right analytical tools, some incredibly accurate insights can be developed and acted upon. This is light-years beyond the old demographic-based target definitions. It also sets a new high-water mark for targeting in the new millennium. Keep in mind that this all happened without the use of a loyalty card.

Most retailers, when faced with the question of targeting, either think media targeting or loyalty cards. But targeting is really about one thing: data, and lots of it. Making the most of that data requires robust analytical toolsets and people who know how to use them, not to mention people who can derive actionable insights from the data. It's one thing to be able to find the needle in a haystack; it's something else to know what to do with that needle once it's been found.

It's at this point that the real magic -- and hard work -- of targeting takes place. Regardless of how the data is collected, collated, and cross-referenced, there has to be a strategy for how the findings will be used, and someone with a clear vision of how the data will help to pave the way to that vision. The ideal target will have specific traits that match the overall market strategy and needs that said strategy can fill.

Generally this means that there needs to be a clearly defined goal to begin the analysis -- who are we after, what we want to know, what problem we are trying to solve. Without a goal in mind, sifting through all the massive data stores amounts to burying bottles on the beach and digging them up again; it keeps people busy but doesn't accomplish much. And it's far deeper than demographics; lifestyle traits, lifestage information, purchase history, and economic factors are just some of the deeper questions that need to be considered before digging into the data for answers.

There has been a lot of hype and chatter about "big data" -- that is, massive datasets that are too large to be mined with conventional toolsets. And most of the chatter has been about collecting all that data and the wonderful things that can be done with it. But those wonderful things won't happen in a vacuum. They require vision and clarity from the outset, and someone with an intimate understanding of what data can and can't supply. Next is the ability to take the insights and actually act on them (i.e., use the info to capture interest and engage the target).

There is definitely gold in those spinning discs of bits and bytes, but it all starts with strategy and a clear view about who the ideal target is. Data will help you find the target once you've identified it and can do so with uncanny accuracy. Data will also help to entice and engage the target. What data won't do is build that target up front; that part remains a marketing function that a computer can't replicate.

Jeff Weidauer is the vice president of marketing at Vestcom International.

On Twitter? Follow Weidauer at @Vestcom and iMedia Connection at @iMediaTweet.

 

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