We Have the Data, But We Need Better Ways to Activate It
As marketers, we are constantly prompted to consider the question, “How do people intuitively engage with media?”
We are, after all, consumers, just like the people we’re trying to reach every day. But we often lose sight of the behavioral nuances and how someone really engages with, and is inspired by, an experience, media or otherwise. That is because so many of the systems will live in today do not create a clear picture for reality.
What many marketers still see are disparate, fragmented views of audiences. They are fixated on recurring, or past, behaviors that seem to indicate intent to engage and buy. But that intrinsically leads to equally disconnected channel and media experiences that could, in any scenario, deliver the wrong message or miss the right person all together.
Unilever CMO Keith Weed classified it as tunnel vision. Rather than viewing individual customers in a connected journey across their online and offline lives, it’s seeing and treating them as several different individuals in the various channels and devices they use.
This has long created tremendous levels of inefficiency across the media landscape. And it’s resulted in a dramatic shifting of power in the retail world from legacy names to nimbler breakout brands and behemoths like Amazon.
Yet even with richer data about customers, we face challenges in measuring and activating it, particularly when brands don’t actually own much of that data. Standards for audience and digital measurement metrics have been up for debate over for the larger part of 2017, most notably by P&G’s Marc Pritchard.
There are also significant underlying issues in how we identify people across digital and, in turn, how we communicate with them. More specifically, there is often a gap in how marketers correlate media impressions with actual brand impact and, eventually, revenue potential. And it’s propelling marketing dollars out into the abyss.
Do we target a person with hundreds of similar messages, based on what we presume to know about him or her, to influence a desired behavior or action? Unfortunately, our knowledge of that person as a device-agnostic, app-first individual is usually fairly limited in a scenario where cookies are used as the source of truth.
Or do we dig deeper to analyze the impact of a message at an individual level? This helps us to determine just how much exposure and the right sequence of messages and creative that will spark interest. It’s this kind of efficiency that the industry needs. The beauty of digital is the many interesting mediums and mechanisms that give us the ability to influence someone’s behavior.
But it’s not just about more nuanced and personalized engagement, though that is increasingly important. It’s about knowing with greater accuracy the “when” and “how much” it takes to truly impact a consumer’s decision. It’s about being able to identify the window, or the moments in time, when you can change a customer’s path.
We have the data at our fingertips. We just need to activate it in a better way.
Companies such as LiveRamp and Neustar have taken critical steps on building advanced graphs to help marketers first pinpoint all of the cookies and IDs associated with individuals. Once individuals can be identified, the right data management platform infrastructures are needed to capture data from audiences as they’re being served media and interacting with brands through conversion. Data scientists and analysts can then build predictive models around pre-engagement, engagement and post-engagement data to guide media strategy.
The goal, and where the most value can be achieved, is when these predictive audience models can suggest how to sequence and “frequence” messaging, what media to use based on cost and impact and identify the most critical moments to engage customers and influence their decisions.
While much of what’s mentioned here can be brought to life through turnkey solutions that leverage AI and automation, these technologies are not always viable options for all marketers from a cost perspective.
But innovation doesn’t just come from the tools. It’s also the human insight that allows us to understand customers in their constantly changing worlds. This shift to more efficiency and quality will take an evolution of business models, a hard look at partnerships and, most importantly, a change in the way we build teams around the new and emerging channels used by customers.
The answer to the question we’ve asked is: People intuitively engage with media like individuals. And today, smart marketers are realizing the new opportunities at hand. We can build connected frameworks for behavior that not only land the right combination of contextually relevant, right frequency, right time and right message to know what resonates with individuals, but we can anticipate their decisions before they happen. It is much more than achieving data transparency, but seeing consumers as they are across their devices, apps and platforms in their digital lives.
If we can keep this in mind, we can continue to use marketing to drive and achieve business growth. And that is where the real value will be found.