How Big Data is Advancing Programmatic Advertising

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5 min read

Advertising has come a long way since the days of Don Draper.

While data has always played a part in ad campaigns—like whether a potential customer was more likely to see an ad on a billboards, TV, or radio—big data has enabled a new era of advertising. Brands once relied on certain content being a proxy for a certain type of person. Gillette might have bought a full-page ad in Esquire magazine hoping to reach 18- to 35-year-old men interested in buying razors. Cover Girl might have run a 30-second TV spot during Vampire Diaries hoping to reach teenage girls.

Today, brands no longer need to rely on hope as a strategy.

The Emergence of Data-Driven Advertising

With the advent of big data, brands can finally turn to tangible, actual numbers and metrics to make decisions—and use technology to help automate those decisions. Specifically, the programmatic advertising industry has deployed big data technologies so that companies and brands can be more precise about who exactly they’re targeting. They no longer have to rely on sample data; they can ingest broad swaths of exact data generated from GPS on mobile devices, social networks, actual purchasing behavior, and direct customer contacts, and analyze it to pinpoint their target audience.

As a premium programmatic platform, Altitude Digital uses this demand-side data alongside our own data to automatically match the right advertiser demand with the right publisher supply. We use our big data platform and tools to understand and collect different attributes about particular users who visit pages of content across the web.

By analyzing this diverse data stream along with 1st-party advertiser data, we can play the right advertisement at the right time for the right person. Our platform allows publishers the ability to more accurately value their website inventory and their unique visitors, and lets advertisers reach not just the people—but the exact person—they want to message.

Real-Time Analytics

We built our platform not just to drive the decisions on which advertisement we play in real-time, but also to provide valuable big data insights back to our clients. Our data platform and processes enable us to store all events and display them back in the dashboard within 15 minutes. Clients can see months of performance data returned in seconds, or drill down into hour-by-hour reports.

Our publisher clients that might not otherwise be able to afford big data infrastructure can find big data analysis tools right in the dashboard, letting them drill into data points like video player size, non-human traffic numbers, and geographic information, and find corresponding business and revenue insights.

On the buyer side, brands and agencies can use our big data-backed platform to understand exactly the audiences they’re reaching with their marketing budgets: where their target customer saw an ad and how long they engaged with it.

The Future of Programmatic Advertising

The amount of data that we are able to collect, store, and analyze is only increasing as consumers adopt more and more “smart” technologies—from refrigerators that know when you’re out of milk, to cars that know your preferred coffee stops on the way to work, to washing machines that literally know all about your dirty laundry.

Even traditional mediums like TV and radio are beginning to become wired into the always-connected world, and with it, ad spots that used to be bought directly are starting to become purchased through programmatic and technology-enabled methods. This “internet of things” era will only make programmatic advertising more pervasive and more precise, allowing marketers to make increasingly complex decisions about when and where their message is seen.

This type of deep insight would have been impossible just ten years ago, but now it’s becoming the norm. It’s no longer a question of whether or not you want to utilize big data—it’s a question of how you utilize it. Businesses that don’t have the right partners in place to help them understand, analyze, and utilize massive and diverse data streams will be left behind by those that do.

This blog post was published July 10, 2015.

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