Download Exclusive Campaign Performance Analysis: Impact of Unstructured Data vs. Pre-Packaged Audience Segments


Over 30,000 active advertisers are currently leveraging’s programmatic platform to drive higher performance on their digital campaigns. Why? Because’s unstructured data network allows advertisers to extract more value from audience and campaign data than traditional audience segment-based platforms. In fact, we performed a study to prove just how successful our approach to data can be for our clients and their programmatic campaigns, which can be downloaded below.

Before we dive into the report findings, it’s important to note the power of data when it comes to programmatic advertising. It’s what the entire programmatic paradigm is built on. And there’s more of it than ever before. By 2025, the global datasphere will contain more than 175 zettabytes of data.

You’ve probably heard before that when it comes to programmatic advertising, the ultimate goal is to utilize this massive amount of data and serve the right ad to the right person at the right time. What you may not know is that in order to achieve this goal, advertisers need the following: access to high-quality data, transparency, precise targeting, the ability to optimize, recency, and personalization across creative types. Something that is only possible when utilizing unstructured data as opposed to pre-packaged audience segments.

Unstructured Data Improves All Aspects of a Campaign

At, we use unstructured data to enable marketers to target, bid, optimize, and report at the data element level. Unstructured data gives marketers the freedom of transparency to deliver effective, relevant advertising.

Let’s take a look at why unstructured data is far more superior to audience segments when it comes to driving performance. We’ll set the stage for you and then show you how it plays out on the ground in our latest Campaign Performance Analysis report.

Why the Effectiveness of Segments is Limited

Audience segments are made up of what is called “structured data”. Structured data is information that has been scrubbed, organized, and lumped into prepackaged categories. It has been placed into a nontransparent audience segment – a digital black box of sorts – and sold to marketers and Demand Side Platforms (DSPs) as indicative of potential consumer behavior. Examples of pre-packaged audience segments would be “auto intenders,” “high-income retail enthusiasts,” etc. Prepackaged audience segments have significant limitations when it comes to programmatic marketing.

Simply put, prepackaged audience segments lack transparency. This is because, with audience segments, advertisers have no way of knowing what the specific data elements within the segment actually are. Some of them may be relevant and useful to your campaign, some not—there’s no way to know. This means you’ll never know which specific data elements are working well and which are not. And if the campaign doesn’t perform well, you won’t know why.

Speaking of relevant, that leads us to another issue with segments: advertisers do not know what data points justified putting a user into a given audience segment. Purchasing segments from third-party sources means the data sources are unknown. There’s no way of seeing what the data points are before they’re put into the segment because by the time you get your hands on it, all the data has been obscured. In fact, these audience segments are created using arbitraged models so that they more thinly sliced and narrowly targeted the data is, the more expensive it becomes. In essence, the cost increases but the value of the data doesn’t. This is also important to note when talking about timing. Timing is everything when it comes to marketing, and with the lack of transparency when it comes to third-party prepackaged audience segments, there are limited insights into recency of intent or action.

Finally, there’s the question of optimization. While campaigns that use prepackaged audience segments can certainly be optimized, this can only be done at the segment-level. Meaning, if optimizations do not perform as expected, the advertiser is out of luck.

There’s a Better Way

Fortunately, has provided advertisers with a better way of unlocking the potential of programmatic: unstructured data. The benefits that come from this approach directly address the weaknesses inherent in audience segments, and ultimately drive higher performance in digital campaigns.

When utilizing unstructured data, advertisers don’t select from a pre-packaged menu of audience segments. Rather, they use individual data elements, including both online data points – such as contextual content, keywords searched, browsing behavior, domains visits, apps used, site search history and more – as well as offline data points, such as GPS location, to create a custom audience for their campaign, optimizing along the way with the same element-level control.

With, advertisers can tap into unstructured data in real-time, resulting in dynamic audiences. As advertisers learn more about what is working and what isn’t, the audience evolves with the campaign. Advertisers can target dynamic audiences with pinpoint precision, right down to the exact mix of desired individual data points. This is next to impossible when using audience segments because you have no idea what data points justified putting certain users into the segment in the first place.

What’s more, unstructured data lets advertisers optimize in real-time throughout the course of a campaign based on what is working and what is not working to minimize wasted impressions and drive higher performance. There is no need to have to buy new audience segments to test. Marketers can easily bid individual data points up and down, giving them the ability to get higher performance faster and more efficiently. Whereas with segments, unless you have visibility into pre-impression data, you only know half the story.

Additionally, when using unstructured data, advertisers can retain the data and timestamp associated with every piece of data they target, bid, optimize, and report on, allowing them to utilize variable recency from instant recency up to 30 days. Range of recency is important because not everyone needs to target someone who just took an action. Some marketers need to target people while they are researching a purchase, and others want to catch them at the point of purchase. Being able to leverage recency in programmatic marketing truly makes it possible to place the right ad in front of the right person at the right time. Couple that with’s completely transparent and highly granular analytics system, and marketers have access to detailed reporting and insightful analytics where they can report all the way down to the individual data element level.

Seeing is Believing

You don’t have to take our word for it. In our latest Campaign Performance Analysis report, we analyzed our data and analytics from thousands of advertisers on our platform to see the overall performance of programmatic campaigns when using unstructured data as compared to those that use pre-packaged audience segments. You’ll get to see exactly how these advertisers have successfully met their Key Performance Indicators (KPIs) with the use of’s unstructured data, including metrics such as: Cost Per Action (CPA), Click Thru Rate (CTR), Cost per Mille (CPM), Cost Per Click (CPC), and more.

Access the full report below to get an in-depth look at how advertisers have succeeded using unstructured data. For more information, reach out to us at