The term ‘big data’ gets thrown around a lot. In fact, I’m sure we all have our own definitions of what it really means.

So which of us is correct? What does big data really mean?

In its most generalized form, big data refers to the cumulative information that a business has acquired over time. This information reveals trends that can be leveraged in a manner that helps the business make smarter decisions and improve their brand.

In today’s digital marketing space, the most critical insights we can gain are in regards to the customer journey. Why? Because people share EVERYTHING online. Facebook alone stores, accesses, and analyzes around 30+ Petabytes of user generated data. Thanks to this wealth of information, there exists spot-on targeting for acquiring qualified customers, and most importantly, for keeping them.

With so much customer data at your disposal in 2017, it’s easy to get lost in the fog and miss out on some valuable opportunities. We’re going to discuss how you can leverage the RIGHT data to help you better understand your customers, create personalized marketing campaigns that will resonate with them, and use predictive analytics to inform the next steps you should create along their customer journey.

Determining What Data To Gather

Have you ever been on information overload in your personal life? Like when you’re studying for an exam in school and you don’t know where to begin? Unfortunately, the same can be said of data analysis—and with data production set to be 44 times greater in 2020 than it was in 2009, this problem isn’t going away.

The solution isn’t to try and examine everything, it’s to examine only the most important selections of data from our best analytical resources.

To accomplish this, let’s establish our goals…

  • Goal Setting

Data becomes immensely easier to comprehend when we know what specific areas we’re trying to improve upon. Is it our email campaign click-through rates? How about the customer engagement with our brand on certain social channels? Recognizing these deficiencies, then setting a benchmark for how much we would like to improve upon them are the first steps towards success.

Let’s use a basic scenario. This comes from the area of lead generation…

Say we’re an apparel brand who’s looking to increase the amount of traffic to a squeeze page. Thus far we’ve been utilizing Google AdWords, Bing Ads, and organic social media posting to drive traffic, but our conversion rates are still low. What do we do?

Well, in this scenario we could find that it’s an audience issue—we simply aren’t targeting the right audience who’ll want to opt-in to our squeeze page.

But where in the past we’d simply run more ad sets and target people based on “likely accurate” demographic information, we can now utilize retargeting pixels to operate campaigns with pinpoint accuracy.

We could then take the data that our pixel has gathered and create a Google custom audience. If we run more highly targeted ads and see opt-ins increase, we could then import our email list into Facebook to create a lookalike audience.

The possibilities are endless when you have clearly defined goals, and you’ve set the necessary mechanisms in place to collect your data.

Taking The Correct Actions

Optimization starts at a granular level. Let’s say you’re running a pet supply affiliate blog and attempting to get leads through Facebook ads. If you’re smart, you know not to run just a single ad set and pray that it works. Success with Facebook ads (and pretty much anything in digital marketing) requires frequent tweaks and optimizations.

So let’s say that 5 days have passed and you haven’t gotten many email leads. It’s okay! You can make the following changes based off of the data Facebook has accumulated and use it to optimize your campaign:

  • Assuming you integrated your Facebook pixel, you can turn your link clicks into a custom audience. Then you can make that custom audience into a lookalike audience, giving you a wider yet more optimized audience to target.
  • You can cut off the ad sets that are costing you the most money and keep the ones that are giving you the cheapest clicks.
  • Assuming you split tested your individual ads (ad copy, images/videos, call to actions, EVERYTHING!), you can delete the ones that aren’t working.
  • View your insights to see WHO is viewing and clicking on your ad. Then you can develop more ads that are better targeted.

The reason we’re using Facebook in this example? Because Facebook holds 2 billion users’ personal information. Not to scare you, but it’s true! This makes them a mammoth figure in the world of big data, and if you know how to optimize your Facebook campaigns, you’ll be able to tap into more sales, engagement, brand following, and just about anything else to help grow your business.

It starts with a simple perusal through Facebook’s Audience Insights area.

Audience Insights.png

Here alone you can find enough actionable information to get your campaigns started off on the right foot.

In the same way Facebook allows customized audiences for paid campaigns, so does AdWords. Google’s Similar Audiences gives you the ability to create AdWords ads targeting your remarketing list.

So let’s say you’ve been running an AdWords campaign for a few days and have less than 100 hits on your remarketing pixel. Some marketers will panic and try to create a similar audience right away, based on very little data. The problem is that with little data to work from, AdWords will not be able to get you a highly targeted similar audience. A better decision would be to wait a few more days until you’ve gotten a few hundred clicks, and then try creating your similar audience.

The beauty of remarketing is that it can be used to better address the needs of your customers throughout their lifetime relationship with your brand.

Let’s say you’re noticing a pattern where customers stop purchasing from you after six months’ time. Utilize the power of remarketing to get them back in the funnel! Launch an email campaign reminding them that it’s been awhile, offer them discounts to come back, and re-engage them once again with your brand.

A re-engagement campaign is a MUST if you’re struggling to maintain customers. Take a look at Pinkberry’s attempt to win you back. Gotta admit, it’s working…


Going back to our section title “Taking The Correct Action,” yes it sounds idealistic. After all, isn’t that everyone’s goal? But the point we’re trying to make is that you must consistently optimize your campaigns, and in doing so, the “correct actions” will emerge on their own.

Just remember that the more big data you accumulate, the more informed your decisions will be.

Winning With Predictive Analytics

If only we could accurately predict the future of our businesses. But, we can’t. So the next best thing is to look at big data in order to give it our very best educated guess.

Simply put, predictive analytics is the portion of advanced analytics that describes making predictions about future events. In today’s marketing climate, this encompasses everything from lead scoring to using advanced top-down marketing modeling.

Without diving too deep into the minutia of these advanced concepts, let’s look at a visual representation depicting how we arrive at our predictive conclusions…

Predictive Analysis.jpg

Source: Predictive Analytics Today

As you can see, this goes back to the idea of constant optimization and retargeting our campaigns. From the start of data flowing in, we should be asking ourselves what is happening and how can we optimize those campaigns to improve the results.

Improve Your Results With A/B Testing

Split testing each step along your customer journey is key to winning BIG off of big data. Run multiple ad sets and multiple email campaigns and test different headlines, images, and calls to action.

The more time and money you spend testing today, the greater your financial return will be tomorrow.