For all of its creativity and attempts at deep analysis, traditional marketing has always been somewhat of a guessing game. Sure, you could create new campaigns based on analyses of those that had come before, and you could even do mid-campaign evaluations, but traditional marketing measurements were imprecise at best, painting a broad picture of the consumer and lagging behind changing desires and market demand.
Big data has the potential to turn this model inside out. Why? Because, in tracking consumer email addresses, Facebook likes, product views, purchase history and overall online behavior, big data continuously measures the pulse of the market. In this way, big data can turn marketing from a cumbersome, mysterious beast into a nimble analytical tool that can anticipate the outcome of campaigns as well as customer needs, and change on a dime to suit demand.
That said, for all of its strengths, big data can be particularly overwhelming, leaving marketers unable to act. That’s why it’s so important to make big data small by narrowing the focus of analysis, and to employ the kinds of tools that turn raw information into insight, knowledge, and ultimately action. Doing that requires an intimate knowledge both of what big data is and how it differs from more traditional methods like persona building, which can and should still be used in conjunction with these newer tools. Let’s take a look at all of these methods, both old and new, and just where big data fits in your marketing strategy.
How Big Data Marketing Differs From Traditional Persona Building
The difference between big data marketing and persona building is this: big data tells you with great precision what your customers are doing online and how they’re doing it; personas help you understand why.
Not to be too blunt here, but big data in its rawest form is just a huge mass of numbers. Even when you’ve whittled that down into helpful insights, big data can still be difficult to wrap your mind around in any kind of actionable way.
Take the example presented in this video. Big data might tell you that two women aged 22 have similar shopping habits, buying at similar times of the year and visiting the same discount chains. But that doesn’t mean they’re the same person with the same wants and needs, nor that they can be targeted effectively with the same message.
Person A might be a young professional fresh out of college who needs to look good for the job but can’t afford big splurges while Person B might be a young, single mom who needs a lot of value for her purchases. Ultimately, they may make the same purchasing decisions, but their motivations likely differ wildly, as do the kinds of messages that will get them swiping that credit card.
This is where personas come in. While big data analytics will help you find these two characters, personas help you write their story. Once you’ve got that, it’s much easier to create a vivid and highly relevant content marketing campaign to motivate your target customers into action. That’s not to dismiss big data at all. In fact, big data helps you make those personas all the more precise, rather than being completely imaginary. It also will help you evaluate your personas both as you go and at the conclusion of your project, which in turn can help you flesh them out or redirect them entirely. It’s the hard numbers you need to justify the persona’s existence.
So, knowing all of this, how can you further use big data to your advantage?
# 1. Create Hyper-Targeted Content and Ad Campaigns
While big data certainly is big—gigantic, really—it’s especially adept at making the user experience small. This often comes in the form of fine-tuned customer segmentation, whether via banner ads, email marketing, or social media campaigns.
Take Facebook ads as an example. When they first rolled out, Facebook ads were still segmented into pretty broad categories. Now, the company has pulled from its mass of user data to create 500 categories, as specific as, “people who ride bicycles,” which can then be paired with more traditional categories like location. Using this kind of data, you’ll be able to create an ad that uses hyper specific imagery and copy, and that might differ broadly from an ad targeting “people who ride motorcycles.” With increased relevancy comes increased interest and much better results.
To understand how big data can achieve similar results for content marketing, just take that category of “people who ride bicycles” and brainstorm concrete blogposts, videos and infographics that would interest that category. If you’ve got a segmented email list or even a segmented Twitter list, you’ll be able to easily direct this content where its most relevant.
# 2. Create Personalized Promotions
Promotions can be an excellent way to drive customers into stores, whether online or in person, but they’re far more effective if you’ve got razor sharp information about just who would be interested in what you’re promoting. Big data software programs makes doing so pretty simple, and in some cases, even automates the process. Amazon is perhaps most famous for this, as the company platform instantly suggests other relevant items and can quickly create deals based on your buying history.
Another company that’s also quite adept at big data personalization is Target, a company that’s so good at crawling customer purchase histories and analyzing wider purchasing patterns across a wide customer base that it can determine not only that a woman is pregnant but also where she is in her pregnancy so they can start sending women hyper-relevant coupons. In some cases, Target might know that a woman is pregnant before she does, all through her purchases of scent-free lotion and vitamins.
This knowledge, however, does need to be handled with care, as Target famously found out when it sent pregnancy-related coupons to a teenaged girl whose father didn’t know she was pregnant. The company has also found that customers are pretty creeped out if they appear to know more than the customer has told them, so if you’re running similar campaigns, it’s wise not to be too overt with your knowledge, perhaps alternating the equivalent of your pregnancy coupons with unrelated promotions.
# 3. Identify Customers Who Might be Leaving You
If big data can help you predict a customer’s purchasing behavior, it can also help you determine when a customer is about to jump ship and when it’s time to step it up with a personalized approach.
As an example, take T-Mobile USA, a company that not too long ago was a slow moving goliath, struggling to act across a very disparate data architecture. That changed when the company went through a process of data integration so that it could better understand user behavior across 33 million customers. The result? T-Mobile now can pull from this mass of billing data, social media information and web logs to predict just who is on the verge of canceling, enabling them to cut defections in half in the first quarter alone.
With a deep understanding of just what it is and what it can do for you, big data has the potential to completely remake marketing, to the benefit of company bottom lines far and wide. However, big data on its own isn’t a cure all. Making the most of the information big data provides means keeping people on staff who can turn information into knowledge and actionable insight that can be used hand in hand with more traditional yet still effective methods.
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