Do You Know What All Those Data-Driven Buzzwords Really Mean?

One person’s clean room isn’t the same as another’s

In data and ad tech, the winding path that words take and the evolution of their meanings can create confusion as different definitions are applied. After all, just a few years ago a cookie was really just a delicious treat.

Often, the same terms are imbued with different meanings to different people across the industry. Take “clean room,” for example. Data clean rooms seem to be popping up everywhere, with the term being used liberally for a host of different services. Confession: my past definition of a clean room would not fit the way the term is often being used today.

And that’s okay, because it’s the value of explicitly describing a capability, how it works and what it achieves that’s important.

In that spirit, let me plainly offer a few pieces of advice to advertisers and brands on what they should be focusing on from a data perspective—trying my best not to use any amorphous buzzwords.

How to best leverage data

Let’s break down some of the terms related to the big opportunities for data-driven advertisers to leverage data in today’s market:

Identity or identity graph: Advertisers need to have access to a set of unique identifiers to curate and size a set of people to whom they wish to communicate. These identifiers can join disparate sets of data together for a host of use cases, including ones I will describe shortly. Bottom line: An identity graph is foundational to data-driven advertising and can be created with an advertiser’s own data or be licensed from a third party.

Matching: Next comes data matching, where brands can join their customer data across multiple sources with publisher or third-party data to identify high-performing audience segments. Simply put, this helps guide an advertiser to the data that will best facilitate messaging to the audiences they want.

Activation: Once advertisers know which audiences they want to reach, they need to be able to activate that seamlessly across all the different media channels that make sense for that audience. Without the ability to activate data, brands wouldn’t be able to get their message to the right customer, at the right time.

Measurement: Once a campaign launches, an advertiser should be tracking performance of that campaign and using that information to manage reach and frequency overall. Think of it this way: Where did my media run, who did it reach and how many times? And where were the unique and duplicated audiences?

Attribution: Also called “outcomes,” attribution capabilities help marketers understand what actions their audience takes after seeing the ad, such as if they went to a store or if they researched the brand further. This connects their marketing efforts to the real-world business outcomes they are trying try drive.

Insights: And finally, what insights are you getting? It’s important to uncover deep learnings on your current and prospective customers to drive future investment decisions. Individual insights ladder up to a holistic view that can drive a business and may be unique to that business. For example, high duplication across media may drive conversion for one customer segment and may be waste for another.

How to evaluate potential solutions

Data is just one element of a successful advertising program. As a brand or advertiser, ask the following questions as you evaluate potential data or publisher partners:

What is the goal or business objective? Are you looking to reconcile your own first-party datasets, or are you looking to create a privacy-safe environment to collaborate with others?

Does the platform or data repository integrate well with the other systems or solutions you are currently using?

What capabilities are you looking to harness? Identity solutions? Activation? Measurement and insights? These are all important capabilities, but you may need different partners to achieve each.

Is the data you are using for identity and data matching deterministic? Will you be able to match that confidently and consistently with other sets of data?

To summarize, while there are numerous data-driven opportunities to take advantage of, don’t get frightened by all the new buzzwords that may be thrown your way. It doesn’t matter if it is a clean room or a cookie. Focus on your core objectives, what your goals are, and how you want to incorporate them into your overall advertising strategy.

Dan Rosenfeld is SVP, analytics and insights, for DIRECTV Advertising, responsible for leading data strategy, analytics and insights across the company’s advertising portfolio.