Three Myths About Big Data and Marketing

File - In this Nov. 18, 2010 file photo, a magnifying glass is used to illustrate an excerpt from the Top Internet Service Go
File - In this Nov. 18, 2010 file photo, a magnifying glass is used to illustrate an excerpt from the Top Internet Service Goggle Maps, recorded in Bremen, Germany. The U.S. Justice Department approved Google's acquisition Friday, Dec. 2, 2011, of online advertising service AdMeld after concluding the deal wouldn't diminish competition in one of the Internet's most lucrative marketing niches. (AP Photo/dapd, Joerg Sarbach, File)

Tech story of the year -- Big Data. Everyone is talking about how Big Data will save the oceans, predict the weather and track the functions of human bodies. When it comes to the world of business, Big Data will transform marketing forever. Experts say Big Data will deliver the right messages to the right consumers at the right time, turning advertising into a true one-to-one medium.

Will it? Haven't these claims been made for everything from mainframe computing to social networks? Why is it true now?

Fact: technology revolutions have their greatest impacts in unexpected places. And there's no single solution to the problem of marketing to such complex and often perversely motivated creatures as humans.

The real question: How to maximize Big Data's value to my company's marketing now?

Let me present the three biggest myths about Big Data in marketing, and suggest how to deal with them.

Myth 1: Big Data Is Moving the Needle on ROI

Marketers want to believe they're getting big returns on their investments in Big Data tools, including real-time ad bidding (RTB) and data management platforms (DMPs), data-driven campaign management, and predictive analytics to measure huge sets of campaign, customer, sales, and other datasets.

But what most marketers don't appreciate is that these tools are minimally impacting ROI. Why? Because for now Big Data marketing is more promise than reality. Most marketers don't know what data to gather, which analysis tools to use, and how to use that processed data to have real impact on sales.

That may change. The prudent strategy is to prepare and wait -- prepare a strategic Big Data plan. Find out what exactly big data can do for your programs, then execute on that plan across search, social, display, mobile, and video. Investigate the Big Data tools and partners out there. There are hundreds of ad tech vendors claiming to use 'Big Data' technology, but few that actually do.

After you understand what vendors are offering, and the financial dynamics of Big Data in your industry, then you pull the trigger... or not.

Tip #1: Make sure the Big Data you are measuring correlates with the things that impact your bottom line.

Myth 2: Big Data Will Give You Access to All the Right Data

Most marketers feel they are drowning in data -- from campaign and click, to customer, purchase, mobile, social, RTB, and third-party publisher data. They can't imagine how the data sets they're using could actually fall short. Yet they convince themselves that capturing more of the same will somehow make their decisions wiser.

In fact, access to more data doesn't mean it's the right data to analyze. Improperly targeted, Big Data becomes just more Bad Data. Most advertisers have no idea how many different kinds of data are out there, nor how to capture them. So they mostly analyze first-party data from their websites and campaigns, but neglect to include third-party data from DMPs, publishers, mobile apps, and ad networks.

Measuring only first-party data provides just a small glimpse into how your campaigns are working, and doesn't provide clear insights into performance across the web, mobile, and social. The solution is to work with providers and agencies that can deliver access to comprehensive data. Do monitor partners' data sources to make sure they are as far-reaching as promised. Finally, accept that the data you're analyzing is just the tip of the iceberg, and strive to continually uncover new data sources.

Note that I did not suggest you implement a Big Data solution. In fact, that will only exacerbate your problem. Wait until you know what you are looking for... then consider Big Data.

Tip #2: Build a road map before you buy or implement any Big Data services. Use your map to determine what data is still unobtainable -- and plot alternative routes for getting it.

Myth 3: Your Analysis Is Working to Deliver Insights

At this point you may be saying: Okay, we'll be more careful. But Big Data delivers big insights, right? Doesn't that make it worth the risk?

Not necessarily. Many advertisers look to analytics tools and marketing partners to deliver reports on campaign ROI and optimization suggestions. These can be very useful, showing which campaigns and channels are working to acquire customers and which are falling flat. But many reports gloss over the surface, providing standard insights that only incrementally improve marketing ROI. If you don't know what you don't know about the data you're analyzing, the findings from analysis are limited. That mistake will burn a lot of money on Big Data initiatives that deliver nothing new.

One solution is to make sure your Big Data marketing solution, whether it's an in-house platform or an agency partner managing campaigns for you, can deliver the exact reports you need. The metrics you slice and dice will depend on your industry, business goals and marketing plan. A one-size-fits-all reporting scheme will not help.

Once you have created the right individualized reports, you can work those findings. It is this type of deep insight married to instant, automated optimization that will begin to move the ROI needle.

I am an optimist. I believe that Big Data-driven marketing will rule the 21st century. But that century has only just begun. This is one time when you may not want to be ahead of the pack. Let others make the mistakes, and use their experiences to help you build your road map. When it comes to applying Big Data to marketing, a bit of patience will go a long way to improving your competitiveness.

Tip #3: Don't depend solely on your own resourcefulness to find answers. Look into expert systems and consultants who can help you connect the dots with Big Data. Those same professionals also can provide you with best practices to make sure you start out in the right direction -- and reduce your learning curve -- as you enter the world of Big Data.