In our digital worlds, it is safe to say that advertising is becoming more dynamic and complicated than ever. In advertising, Mad Men are becoming Math Men.

Some would say that mobile devices, technology and advanced consumer behavior have made it a complex art and science of anticipating how, when and where someone will respond to a brand’s message. At Ad:Tech San Francisco, the debates surrounding advertising and our multi-screen, cross-platform communication channels yielded three key trends:

2013 Trend: The Focus Is On “Programmatic”

Mad Men are becoming Math Men with programmatic, transparent, scientific processes according to Michael Baker of DataXu, a programmatic marketing platform. Programmatic Marketing is the key phrase and practice for marketers in 2013. Programmatic marketing is a brand’s use of their consumer data to measure and tailor messages to incite action – most notably in their digital display advertisements.

“Brands, companies and marketers now have tons of data, but few processes to really understand and leverage it. So we see the rise of programmatic marketing,” says Michael Baker. “A programmatic approach is allowing the human entities that work within an organization to focus on leveraging technology for creativity instead of non essential tasks.”

Programmatic marketing enables brands to optimize their media spends and eliminate spend waste by automating ad targeting through leveraging that data and predictive analytics. The practice of programmatic marketing is directly related to the contextual relevance of the ad content to the target audience’s behaviors, needs, geographic locations and possibly other AIO variables.

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Technology has made it easier than ever to compile, store and evaluate data gathered online. With the cost of storing large amounts of data dropping, more and more companies are doing so. But why?

Simply put, sifting through data can reveal amazing insights for businesses and marketers looking to develop a robust profile of their prospects and ideally, their customers.

So what is big data?

Big data is an umbrella term used to describe the exponential growth, availability and use of information.

Big data is basically any information that can’t be processed through a conventional database. Either the sheer volume of data is so massive it can’t be stored on site, or it comes in too quickly to analyze. Some data simply doesn’t fit into the existing analytics structure within a company. In these instances the information must be captured and processed using other methods.

What makes up big data?

Volume: This refers to the amount of information that’s able to be captured, tracked and stored. With data storage costs dropping, the amount of information companies are capturing will only continue to rise.

The key to dealing with volume starts with sifting through the data to determine what information is relevant, and assigning value to the relevant info.

Example:  FICO, or Falcon Credit Card Fraud Detection System, protects 2.5 billion active credit card accounts world-wide.

Variety: Data comes in many forms and only a small portion of it is numeric. That means there’s relevant data pouring in from multiple sources and much of it is difficult to quantify. Despite the challenge of identifying and measuring these sources, it still must be accounted for and considered in a company’s analysis and decision making process.

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