One-to-one marketing should have been solved years ago

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Brands are still struggling to deliver on the promise of one-to-one marketing, writes the CEO of Flite

The confluence of two aspects of marketing makes absolutely zero sense to me. First, soon after the advent of the first digital ad, the marketing world espoused that soon we’d be able to accurately target consumers and properly track marketing spend, and by extension, we’d no longer have to hear the famous John Wanamaker quote ever again. Second, over the course of the last decade or two, email marketing and CRM disciplines have been able to, more or less, make that a reality. Yet, somehow it’s never quite become a reality in the one part of marketing where it could most easily be achieved—digital advertising.

Throughout the last six or so years, every so often the term "One-to-One Marketing" crops up and everyone gets excited. Google it, you’ll see. Then, unfortunately, it sort of fizzles. However, quite frankly, with the availability of tools, technology, mountains of data and armies of software engineers, this problem probably could have been solved many years ago. Those of us in technology use the word problem a lot, but for the marketer, the better description would be opportunity. The brands that harness the power of data to truly achieve personalized marketing stand to win big.

Sure, Facebook has been recently cited as being able to predict whether you lean conservative, independent or liberal, from an analysis of your newsfeed, likes and other platform activities. Of course, that’s quaint and somewhat interesting, especially in an election year. But let’s face it, that’s not really one-to-one marketing—it’s only the beginning.

Let me illustrate just how absurd it is that digital marketing is still struggling to make this happen. Offline retailers, i.e. brick-and-mortar stores (remember those?), have been doing something close to personalized marketing for years. Remember that viral story about how Target figured out a teen girl was pregnant just from her purchases? Granted, that was a tad creepy, but hidden in that story was a prime example of using consumer data to achieve precise targeting. From their massive shopper data, Target also knows that men who buy diapers are probably new dads, and new dads tend to drink at home instead of going out. So they show male diaper buyers coupons for beer. It’s not exactly one-to-one marketing, but in many cases it’s better than what we’re seeing in the digital advertising space.

What’s important to note is that Target is making a connection, between diapers and beer, that’s not necessarily intuitive. Male Target shoppers may not even realize that these ads are aimed at them—they just know the coupon is useful. It’s vital that digital advertisers start using the technology, tools and algorithms available, to make these less-than-obvious connections between a person’s trackable behavior and their less trackable wants and needs. Finding those connections are the basis for achieving personalized marketing in digital advertising and gives marketers a huge leg-up over their competition.

Digital advertising that incorporates more than just raw browser history, and takes into account a user’s interests, tastes, and preferences and tailors a message that’s just for them, should not be that difficult. Granted, the fragmentation of data across accounts and devices makes it difficult to assemble a comprehensive profile on any one user across the vast digital landscape. In fact, heavyweights like Facebook, Google, and Microsoft have been working on unique identifiers for users that will allow them to track behavior across multiple devices, particularly mobile where old-school browser cookies essentially don’t work.

While sophisticated user profiles and unique identifiers will advance the industry by leaps and bounds, we don’t necessarily need those profiles to get started on the journey toward true one-to-one marketing. Automated tools already exist that can deduce the political leaning of a tweet, or decide whether a comment about a brand is positive or negative.

For example, data can tell a marketer that you’ve made negative Facebook posts about one of its brands and thus keep ads for that brand from surfacing in any of your digital travels. And it can also tell a meal delivery service like GrubHub or UberEats that you’ve been staying in nights and watching a lot of Netflix.

Leveraging data insights will help brands, agencies and marketers get closer to creating ads that are truly personalized and useful. True one-to-one marketing is no longer just a concept that is pondered every year or so as a pipe dream. It’s already here.


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