Using Big Data to Measure Your Marketing Efforts

In case you haven’t heard the news, big data is kind of a big deal. Measuring the media that people consume is becoming increasingly important for marketers and businesses. From determining costs per lead to understanding what marketing methods are reaching and converting consumers, big data helps you make smarter decisions.

Smarter decisions = Better decisions.

This sounds great, until you realize that you are anything but a number-crunching math whiz or a technology expert. If the thought of working with numbers gives you a headache, you’re not alone (I promise!). There’s also the general question of relevancy: how much do you really need to know about big data? Is it even part of your job?

Short answer: Yes. You’re far better off accepting data and learning how to use it to your advantage than ignoring it or hoping that someone else will do the math. It’s not as scary as it sounds.

A good way to get a quick grip on big data is to check out resources that detail the “Five V’s of Big Data: volume, variety, velocity, veracity, and value.” Here’s a snapshot of each “v”:

Volume: There’s an incredible amount of data that exists. we must handle the volume of data that is necessary to provide meaningful insights.
Variety: Multiple industries are now coming together to provide comparable metrics, and everything is changing very fast. Flexibility is key when you need to quickly adapt to these changes.
Velocity: Real-time data and decision making is becoming increasingly important.
Veracity: The quality of your data is key; one small error could kill the entire data set.
Value: What you get from the insights derived from the data.

While it’s important to understand and take into consideration all of the Five V’s, I want to focus on the one that can really impact a business: value. There are many ways to show value using big data, but my focus is how it can impact marketing efforts.

The data that is incorporated into the “value” piece of the big data puzzle comes with a few layers. First, you have the directional data, which describes the who, what, where, and which. Similar to demographic data, directional data provides excellent insights on a surface level. It’s where you can start during strategic planning, monitor the effectiveness of your plan mid-campaign, or analyze the results of your fully-executed plan. As marketers and strategists, we are always looking for data that will help us better understand the target customer and their behavior. But even with these insights, you still may find yourself stuck when it comes to proving ROI. Chances are, someone within your company will still ask, “So what?”

Here’s where the “value” piece of big data really lives up to its name. When you start to think about the “how” and “what” of big data, you are then able to transform the data into “currency.” In short, you are monetizing the insights to understand what efforts yielded a certain amount of ROI. Does this sound familiar? It’s nothing more than a transaction. You may also recall a method from your grade-school math classes called “educated guessing.” While you always want to get as close to the mark as possible when monetizing your data, there is nothing wrong with making educated guesses along the way. Think about the value of what you are trying to sell or what goal you are trying to achieve , and then ask yourself the following questions: “What is it worth?” and “What is the value per customer?” You could even use this method to provide a best/worst case scenario when predicting your ROI for certain efforts or when setting goals.

Here’s a quick, fictional scenario:

Your company’s marketing website was built in 2005, and you desperately want a new one. As a B2B marketer, you inherently see the value in an updated website and understand the costs associated with designing and developing a new site. To you, it’s an investment. To your CEO and CFO, it’s just another way marketing exemplifies itself as a “cost center.” Senior leadership wants to know why a new marketing site is worth the investment, and telling them that “cool” websites attract new clients won’t cut it. If your company charges a client $30,000 annually for its products/services, and the marketing website costs approximately $50,000, then your qualified lead conversion goal should be at least two (annually). This is a very basic example, but the point is clear: do the math, and present the information in such a way that everyone understands the monetary value of what you are trying do.

The value in finding value

I’m not trying to advise you to stop listening to your gut instincts, but I’ve found that it is much easier to justify decisions when I place a value next to them. Not everyone understands tactics such as marketing campaigns or mobile marketing, but everyone understands money. Placing a value in the form of a currency on your tactics will get everyone speaking the same, jargon-free language. Use this method to prove that your idea will yield a strong ROI or use it for your own personal checks and balances when considering a strategy or tactic.

It’s important to remember that big data is not a silver bullet that will solve all of your problems. Rather, it is a method to receive accurate insights that will help you make more informed decisions and show which tactics will yield an acceptable ROI. There still exists an element of unpredictability in marketing, but it’s far less frightening when you have real insights and educated guesses attached to your goals. So the next time you worry about asking your boss for budget to execute a marketing campaign, look at the data and do the math.

Mo’ Data, Less Problems: Finding Value in Big Data

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