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Micro-Moment Marketing: The Audience

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What is real-world behavioral targeting? And why does it matter? To answer these questions, let's first turn to behavioral targeting.

Behavioral targeting is the tactic of using customer browsing data to serve up relevant ads, offers, and content. If you've been in performance marketing for any amount of time, you're most likely familiar with it.

The style of targeting is based on intent-rich signals provided by specific datasets. It uses historical data and detailed user profiles to deliver personalized ad experiences and improved messaging to consumers. It's one of the tenets on which digital advertising was built.

Here are just a few benefits of traditional behavioral targeting:

  • It helps advertisers better understand and engage their consumers.
  • It helps marketers match creative and messaging around consumer needs.
  • It helps drive conversions by matching ads based on intent.

However, despite these advantages, behavioral targeting is going through a bit of an existential crisis these days. And it's becoming harder and harder to be target online.

Offering the option to opt-out.

Data privacy has grown to become a major concern in recent years. While it's not a stretch to say that consumers have always been at least tangentially concerned about online privacy, recent headlines have led to more awareness. In fact, nearly half percent of U.S. internet users were more concerned about online privacy in 2019 than they were the year prior. And as consumer cognizance continues to increase, business models will be forced to adapt.

We've already seen major changes crop up. In late 2020, Apple launched App Store privacy labels to provide more transparency into data usage. These iOS 14 updates require all apps to ask users if they'd like to be tracked prior to usage. Providing the opportunity for consumers to opt-out could undercut behavioral targeting. It’s not a long shot to say this could impact how companies receive and process conversion data. It could even force businesses that optimize around web conversion events to change how they advertise online.

As you may have noticed, Facebook is at the center of these data privacy conversations. Following Apple's announcement, the social media giant took out full-page newspaper ads to criticize the iOS updates, claiming they're a blow to small businesses that rely on the platform to generate revenue. While Facebook doesn't disclose the size of its iPhone base specifically, it's a safe assumption that the changes will affect a chunk of its user base.

These iOS updates aren’t all that surprising. The crackdown on data privacy has been discussed for as long as these platforms have been around. While regulation—either on a federal or state level—may not be in the cards quite yet, an evolution in data privacy policy was inevitable. However, Facebook may not be too far off the mark as well.

Real-world behavioral targeting to the rescue.

The future may look different for digital marketers. However, it's possible to view these developments as a call-to-action. At what point is it time to get back to the basics of being a good marketer and understanding what your users are doing in real life? That's where real-world behavioral targeting steps into play.

We consider the "real world" the logical next step in targeted advertising. Real-world behavioral targeting throws all the benefits of traditional behavioral targeting into the mix, but with one crucial element that digital marketing accounts for: real-world behavior. This is represented by the actual buying behaviors, intent, and measurable engagement in offline metrics, including:

  • Store visits
  • Frequency
  • Types of venues

Real-world behavioral targeting provides marketers the ability to understand their audiences at the right moment—those intent-rich, action-driven micro-moments we've discussed before. It takes the existing data you have and layers it with real-world data.

It all starts with understanding the type of business that is advertising.

It's important to analyze your existing customers. Understanding where they are in the real-world gives us our first strategy pillar. To better illustrate real-world behavioral targeting, it's important to ask yourself the right questions.

  • Is there a brick and mortar retail location where customers buy stuff?
  • Can your customers buy online as well?
  • Where do they come from?
  • Where do they live, work, and play?

If you don't have a brick and mortar location—or are in the service industry—the process becomes similar to building a custom audience on Facebook or Instagram. Uploading a database to a real-world behavioral platform helps illustrate patterns that create opportunities for you to reach your target audience with a high-degree of certainty. Just like you would online. If you don’t have a database, it's time to build a Perfect Prospect Avatar (PPA) and really paint the picture of your ideal customer. That's where the following questions come in handy:

  • Where do your customers work?
  • Where do they go on the weekends?
  • What do they care about?

Creating a PPA helps create a vivid picture of where to best engage with your audiences in the real-world. From there, it's as easy as picturing a budget and timeframe to run your campaign—and you're off to the races.

So, what does this mean for your organization?

To help explain, let's provide a little data modeling 101. Ever heard of probabilistic and deterministic data modeling? In computer science, math, and physics, deterministic systems have no randomness and produce the same output from a given starting point. In the context of data collection, the term "deterministic" refers to any analysis that's verifiably true. Deterministic data recognize specific users through actions like log-ins, registration data, and offline customer data—and marketers can use this data to identify users with certainty.

Probabilistic data modeling, on the other hand, deals with so many variables that further analysis is needed to draw any conclusions. Because it relies on hundreds of signals across multiple channels, it's difficult to attribute who exactly these data points point to. Behavioral data is analyzed and aggregated to predict the probability your users belong to certain demographic categories. However, probabilistic modeling does not deal with absolutes. Instead, it provides your business with a level of certainty based on what can already be validated.

Obviously, these two concepts are far more complex. But you don't have to be a data analyst or technical expert to benefit from real-world behavioral targeting—just a good marketer who understands their audience and what matters to them. As marketers are forced to figure out how to adapt to changes in targeting abilities on platforms like Facebook, deterministic data can help them reach consumers with targeted, relevant messaging based on real-world signals.

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