Giving Channel Agnostics Something to Believe In


There’s a good deal of ink—pixels, rather—being spilled about marketing to consumers in a “post-channel world.” That, of course, means different things to different people. For some, post-channel represents the convergence of marketing efforts previously divided among multiple channels into the ubiquitous, ever-present, smartphone. (A recent Deloitte study revealed that the average American checks his or her phone 46 times a day. 74 times if you’re a Millennial.) For others, post-channel might mean the immersion of the consumer into the ubiquitous plasma of signals delivered not just through smartphones, but cars, smart televisions with addressable advertising, virtual reality, even your refrigerator (a scenario Nicholas Negroponte predicted nearly a quarter century ago). Like amniotic fluid surrounding and infiltrating the American consumer, marketing becomes all pervasive in this view and all channels are one big channel. Or no channel.

Yet another version of post-channel involves the integration of digital engagement with brick and mortar experiences. The customer engages seamlessly on their own terms across both digital and physical environments. They don’t think about using or being in a channel. Which makes it hard to tell who really has the power here: the consumer or the marketer. Given these realities, it no longer makes sense for most brands to be anything but channel-agnostic.


Just as post-modernism reacted to the assumed certainties of scientific explanations, so post-channelism is a reaction to the assurances of certainty promulgated by martech vendors who often end up all claiming credit for the same results. The multiple attribution claims for a $50 purchase can add up to $500 if you listen to all the solution providers in the stack.

The problem is we really don’t know how the customer will respond…until they respond. And they may react differently tomorrow than they did today. This fluidity and fickleness of response is probably why things like last-touch, intent signals, and in-market micro-moments loom so large and seem so compelling. They promise to be the one inflection point where marketers still feel like they have a shot at impacting purchase outcomes. But is there a way to impact results beginning in the earliest stages of the funnel? Yes, if you follow the money.

Dollars Don’t Lie

It is only when the consumer makes a purchase that you know for sure what their priorities are. After all the searches, retargeting, micro-moments, reviews, and recommendations, it is the actual spending that becomes the most valuable data in predictive models. To wit, the guy whose searching, surfing, and clicking would suggest he’s in the market for a $40,000 speed boat with a 350 hp inboard motor. Problem is, his online and in-store purchases over the last three years suggest instead that the most he’s willing to spend is $10,000 on a bass boat and a trolling motor. That’s because dollars don’t lie. They express quite precisely the real propensity and affinity that people have for any product or offer.

This is not to say that down-funnel intent signals aren’t important. They are. It’s just that parting with cash has a way of clarifying things. And that clarification fuels accurate predictive analytics. Enter AI—machine learning that leverages massive, detailed transaction data to find patterns that fuel predictive analytics.

Pre-Intent Marketing Influence

Purchase data drives intelligent top of the funnel strategy, and it enables pre-intent marketing. It enables marketers to create brand preference among consumers most likely to ultimately respond to a brand or offer further down the funnel.

So do channel agnostics have something to believe in?

You bet.

And it all comes down to two things: data and analytics. If you have data that continues to prove itself to be truly predictive of customer behavior—namely first-party consumer purchase data—and if you have the sophisticated analytics to make that data actionable, you really have something you can believe in. It’s possible to predict the future. Not perfectly, but well enough to steer marketing efforts intelligently regardless of channel and find the incremental gains that separate profitability from mere survival.

And when that first-party data comes from thousands of organizations from diverse industries, it points to correlations—some expected, some surprising—that predict future spending behavior in ways that relying on one’s own CRM data alone can’t deliver. This is the power and the promise of the data cooperatives like Wiland. It’s an honest approach that is both refreshingly transparent and highly credible in a confusing martech landscape that frequently strains credibility.

So regardless of strategy, choice of DSPs, or channel preferences, it’s the quality of the data and predictive analytics that engender confidence—something to really believe in…even if you’re a channel agnostic.

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