Introduction

Big data is big news—and for good reason. The numbers are stunning. Global data generated by enterprises is projected to increase by 40 percent annually. And in 15 of the 17 major industries in the United States, more data is stored per company than in the entire Library of Congress.

And no wonder. Companies are amassing new and different types of information—from sensor data to social media content—at ever-increasing rates. At the same time, global IT spending is projected to grow at just 5 percent annually, leaving IT teams unsure how to accommodate this exponential growth in information emerging from every facet of the enterprise.

Marketing leaders may be thinking, “That’s all well and good, but what does it have to do with marketing?” The answer is simple: just about everything. In fact, the rise of big data may be more relevant to marketers than to anyone else in the enterprise—including IT.

This paper takes a look at the hard truths and common misconceptions surrounding big data. In particular, it focuses on five common myths about large-scale analytics, then offers a glimpse at the next steps necessary to make big data work for you.

Defining 'Big Data'

The phrase “big data” refers to datasets so large and complex that traditional analysis programs are unable to process them. With help from recent technology advances in big data analytics solutions, marketing leaders are able to better manage these datasets, thus informing their marketing efforts for more targeted, personalized interactions with customers.

Big Data Myths

By this point, you’ve surely heard a number of conflicting claims about big data. Who is it for? What can it do? And why all the fuss anyway? Here are five of the most common big data myths—and an attempt to separate fact from fiction.

Myth No. 1: Big data is only for IT

You might assume that chief information officers (CIOs) have been at the forefront of the big data phenomenon, but that’s not necessarily true. In fact, Forrester Research estimates that more than 45 percent of big data deployments are for marketing.

The reason is fairly simple: Your customers’ unique preferences have already been captured in your data. By harnessing that data, rapidly analyzing it for new insights, and using it to create personally tailored marketing campaigns, you can offer customers the best possible experience in every single engagement. This is called data-driven marketing, and it’s one of the most effective ways for organizations to take full advantage of the extensive customer data already in their possession.

Myth No. 2: Big data is just hype

Marketing leaders are understandably worried that big data represents yet another hype cycle. But the fact is that marketers in every industry are already using big data analytics to increase revenue, reduce the cost of going to market, and improve the accountability of all their activities.

By segmenting and targeting prospects based on specific behaviors, marketers can increase open rates by more than 50 percent and increase conversion rates by more than 350 percent. Meanwhile, operating costs go down considerably—as much as 43 percent. Customers themselves prefer a more targeted approach, reporting that they are 40 percent more likely to purchase from retailers who personalize across channels.

In short, the cost of not embracing big data is too great for you to risk—and the risk will only grow.

Myth No. 3: Big data is unstructured

Many people think that big data simply means that data is “unstructured” and further assume it’s too difficult to analyze. But more accurately, big data is “multi-structured,” meaning there is a variety of data types—with some fitting nicely into rows, as in a Microsoft Excel spreadsheet, and other data falling into less easily analyzed formats. Because of this, big data requires some extra work to unify—and technology has advanced to the point where most of that work is automated.

The truly multi-structured data is what many marketers have been struggling with for years: weblogs, email content, and social media data, among others. This lack of a common structure becomes more problematic with the rise of multi-channel marketing: Customers engage with a brand across multiple channels, expecting a consistent message no matter with which channel they choose to interact. A data-driven marketing solution provides the comprehensive framework necessary to take insights from widely divergent datasets and apply them across those channels, giving marketers the ability to present personalized messaging to every customer, every time.

Myth No. 4: Big data is the answer to all your problems

Harnessing the power of big data analytics is crucial for moving your business forward—but it’s the execution on those insights that will drive revenue. Properly used, big data analytics of digital channels should be leveraged in conjunction with offline data to generate the deepest possible insights. That means coordinating with an integrated marketing management solution to bring insights to market in a sustainable and scalable way.

With a centralized analytic environment to optimize content across both inbound and outbound channels, marketers can take all available online and offline data into account for in-depth discovery and analysis. The results are worth it. According to technology research firm Gartner, companies that develop an integrated marketing strategy will deliver a 50 percent higher return on marketing investment (ROMI) by 2014.

Myth No. 5: The big data conversation starts with somebody else

A scalable and sustainable data-driven marketing solution requires you and your team to collect and connect large amounts of data, gain real-time insights, and bring those insights to market by way of a tailored campaign. IT can offer the tools and expertise to make that happen—but none of it will be truly effective unless it’s informed by a strategic vision. And the vision starts with marketing leadership.

Senior marketing leadership is essential in implementing a data-driven marketing strategy. Marketing leaders will still need to involve the CIO at the business level from start to finish, collaborate on designing a clear roadmap for big data analytics, and address whatever technology gaps may be keeping the company from pursuing its goals. Only then will they gain the tools, technologies, and insights they need to engage more deeply and richly with any customer at any time.

Conclusion

The rise of big data isn’t strictly an IT challenge. In fact, big data may be more relevant to marketers than to anyone else in the enterprise. With a data-driven marketing solution in place, your organization can increase revenue, reduce the cost of going to market, and improve the accountability of all your activities. But making that strategy into a reality will require proactive leadership—and leadership begins with you.