Big Data Is Not Like Teenage Sex

In my previous columns, I’ve touched a bit on big data and shared with you my thoughts around it. In this column, I’ll explain more on the relations between big data and marketing automation.

It looks as big data is one of the buzzwords of the year. I’ll start with a quote that describes the phenomenon:

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”

Amusing, but to some extent true. So, is your big data strategy teenage sex, or not?

Let’s start by exploring what big data is used for. Research shows that marketing automation yields an astounding 417 percent increase in revenue, as well as a 451 percent increase in nurtured leads, which then makes 40 percent larger purchases than non-nurtured leads (Source: Gartner and Marketing Sherpa 2012). The fact is, it would be crazy for marketers not to embrace this concept and this is where big data comes in.

In our increasingly connected world, data is all around us. According to IBM, we create 2.5 quintillion bytes of data every day. Customers are increasingly on their smartphones, tablets, and personal computers making all sorts of electronic communications and transactions creating a staggering amount and complex matrix of data; “big” might be an understatement already, it is actually pretty ginormous!

In fact, big data is a goldmine for marketers. But how do you store and manipulate this data. And how do you analyze it and make use of it?

Some MSP (marketing service providers) have developed technologies that aggregates these customer motivations and behaviors, meaning not only big players but also small businesses can use big data to create tailored marketing campaigns.

Most businesses already have a great amount of customer data but they’re not sure how to unlock it and convert it into useful insights. MSPs use big data to analyze, segment, test, and refine difficult-to-process raw data and extract customer intelligence, which can help you to devise more strategic, targeted, and multichannel marketing campaigns. Amazon is a great example of how a business can use big data to produce targeted marketing automation campaigns.

One-message-fits-all just doesn’t work any more! Seventy-six percent of companies ranked targeting recipients with highly relevant content as their number one challenge (Source: Marketing Sherpa – 2011 Email Marketing Benchmark Report).

While big data can help you to segment customers and prospects it may not be practical for every business, cost- and time-wise, to deliver one-to-one marketing. The more effective and faster-to-implement way is an upgrade from “one-to-many” to “one-to-few,” a model that would allow marketers to spend more on high-potential or high-value clients than is possible through broadcast marketing.

At the end of the day, it is still about ROI. There are dozens of possibilities on how to pursue the big data model depending on an organization’s goals and business situation. I expect more MSPs to embrace big data in the long run because it is a cost-effective model for customizing content according to unique customer profiles and for achieving overall higher message relevance.

To sum it up, your big data solution should be “fed” with data from different touch points you have with your customers and recipients. This would allow you to have visualized information by making sense of data collected, and give you the ability to act on the information discovered and use it for marketing purposes.

Until next time, stay tuned.

Image on homepage via Shutterstock.

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