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Six Predictions About Big Data and Marketing in 2015

by David Steinberg  |  
February 19, 2015

The primacy of Big Data in marketing and advertising has occurred so quickly that it's hard to remember that just a few years ago, Big Data was initially met with resistance. Marketers wondered, "What is it? How will it work? Will the unknown benefits outweigh the known risks?"

Results have a way of speaking for themselves. Early adopters that trailblazed in the past now stand poised to dominate in 2015.

A new order has emerged: the marketing and ad tech sectors have embraced Big Data—thoroughly and completely. In a short time, harnessing the power of Big Data (gathering, synthesizing, and acting on data on a large scale) has moved from an innovation to a critical success factor.

There are many questions about how the evolution will play out in 2015.

Which new advances will have an impact in 2015? Will profits from Big Data marketing be significantly higher? Is there a ceiling regarding how far Big Data can go or is the potential limitless, as global data creation and information collection grows exponentially and the cost of storing data continues to plummet?

Predictions about Big Data can be notoriously problematic, but thinking about the future of Big Data is a productive exercise. With the caveat that these predictions a standard deviation or two of the mean, here are a few predictions.

1. Big Data goes mainstream

2015 will see Big Data management become more mainstream. In many ways, we are still in the infancy of Big Data, but the consistent growth is becoming unstoppable. Essentially, Big Data management is simple: collecting, storing, analyzing, and acting upon large and sometimes complex data using various methods and techniques.

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David A. Steinberg is CEO and founder of Zeta Interactive, a New York-based customer lifecycle marketing platform company.

LinkedIn: David A. Steinberg  

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  • by CyberH Mon Feb 23, 2015 via web

    David, very interesting article. Many uses of big data have a measurable positive impact on outcomes and productivity. Areas such as record linkage, graph analytics deep learning and machine learning have demonstrated being critical to help fight crime, reduce fraud, waste and abuse in the tax and healthcare systems, combat identity theft and fraud, and many other aspects that help society as a whole.

  • by Sonam Wed Mar 25, 2015 via web

    Thanks! This is really an interesting blog! One thing I would like to add is that The Internet of Things (IoT) is also going to impact Big data this year. Before anything can really grow up into a “real” technology that has real application for real companies, issues need to be ironed out, and that can’t happen until those issues arise in the first place. This includes issues with connectivity, applicability and most of all, security. 2015 will likely be the year that, diving headlong into the IoT excitement, companies start to experience these challenges in a first-hand manner. So why is this a good thing for IoT? Because it will force the industry a whole to get serious about using IoT technology in a truly applicable manner, with bona fide safeguards in place to ensure proper security and connectivity.

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