It’s Time To Get Serious About Plotting A New Audience Targeting Strategy

We’ve been talking about the tectonic shifts occurring in digital media, and in a recent post, I emphasized that brands that have built their marketing strategies on third-party or non-consented audience data are facing an evolve-or-die moment. It’s encouraging to see more discussion across the industry about what steps marketers need to prioritize today to be ready for tomorrow. Much of the conversation has focused on the need to:

Each of these steps is important and will require significant investments and company-wide alignment to effectively execute, which is likely why so much of the conversation about the future of audience targeting in digital media has focused on these topics. We’re going to take a different approach, however, and spotlight aspects of audience targeting that we’re worried brands aren't thinking about but need to be.

Let’s dive deeper into the mechanics of what audience targeting will look like in practice, how audience data sources will benefit various types of businesses differently, and why you need the right measurement framework to make sense of the complexity.

Understanding the Targeting Tools Available and How to Use Them

Let’s start with a simple framework for the most common audience data sources marketers are using and how those data sources reflect a brand’s relationship to that audience: 

On the surface, it may seem logical to prioritize spend first to known audiences, then expand to semi-known audience data sources, and use contextual targeting once all other options are exhausted. Rise’s approach to holistic media management has always been to maximize top performing audiences, tactics, ad placements, etc. before investing in the next—and that still holds true. 

In a world with more reliance on 1P data and walled garden signals, however, the impacts of different audience targeting options will vary by brand based on the business model, goals, etc.,  which makes the equation more complicated.

Aligning Audience Targeting to Business Strategy

As an example, let’s compare a business whose growth requires a steady influx of new customers, like sellers of a high consideration/low frequency purchase—think a household appliance, a loan or an insurance policy versus a business with lower consideration products that rely on repeat purchases from existing customers to fuel growth. In the case of the latter, 1P data of past purchase behavior is more beneficial. Meanwhile, for a customer acquisition-driven company looking to reach new individuals who look like their customers, leveraging behavior data from walled gardens may be more valuable. But the only way to know for sure which of the many data sources are the most valuable is to test them, which we’ll cover in the final section.

The recent explosion of players in the retail media space is a natural byproduct of the increased demand for new audience targeting options in a privacy-first world, where third-party cookies are no longer supported. Retailers are capitalizing on the value of their accumulation of consented customer data. This started with Amazon and quickly expanded to other retailers like Walmart, Target and Kroger. Recently, Ulta Beauty—Rise’s longest standing client—launched UB Media to help brands better reach end customers by leveraging Ulta’s best-in-class loyalty program data. Marriott even launched a media network. The fragmentation is only going to continue, and the volume of options marketers will be presented with will increase. 

Building a Measurement Strategy to Determine the Right Audience Mix for Your Business

This fragmentation and complexity leaves marketers with the hefty task of evaluating which audience targeting inventory best drives business outcomes—a task that is untenable without the help of technology.

At Rise, we help clients make sense of their results across data sources with Connex, our cross-channel media optimization platform that normalizes, aggregates and analyzes data from all of the major advertising platforms in real time. We compare results of different audience segments side-by-side across platforms, showing clients which mix of audience targeting best aligns to their goals. For example, we can test the same subset of a brand’s CRM data of high value customers across Meta, Google Search, YouTube and other social channels to see where spend is driving the highest ROI. Connex Alerts are configured to notify our team in real time when there are audiences (or messages, geographies and many other attributes) significantly over- or under-performing goals that require our attention. 

This type of audience testing technology and framework will be essential to marketers’ future success. Evidenced by the explosion of media networks in the “semi-known” category of audience targeting, having a complete picture of what’s working in real time is getting more challenging, but it’s non-negotiable. Whether in-house or through agency partnerships, marketers need to be demanding a plan to see their cross-platform data in a side-by-side format to make better decisions about which tactics and audience data sources are doing the best job of connecting with their customers.

Whether you’re excited about this new future or apprehensive—let’s talk.