Big DataMartin Waxman, my esteemed Inside PR co-host and long-time friend, recently went back to school.

Yes, the man who has run two agencies, who teaches digital strategy at University of Toronto, and who is an author has gone back to school.

I love this about Martin.

He certainly has the street cred and the experience to know everything he needs to know about communications.

And yet…he’s working hard to evolve and learn more.

He entered school last year to get a master’s degree in communications management from McMaster-Syracuse University.

And we have the benefit of learning alongside him.

Last week, in a pre-recorded episode of Inside PR, he invited Alex Sevigny, one of his professors, to join us.

Big Data Information for Communicators

Alex is the director of the master’s program at the school and an expert on Big Data.

You can imagine the fun Martin, Joe Thornley, and I had quizzing him on the topic.

We covered everything from measurement and how communicators can use it to the future and artificial intelligence.

The episode hasn’t aired yet, but will in the next week or so.

If you’d prefer to listen to it (and you should because I haven’t covered everything here), you can subscribe on iTunes or your preferred podcast app.

In the meantime, there were three sections about Big Data I thought pertinent for all of you.

The Four Vs of Big Data

The first thing Alex discussed were the four Vs of Big Data.

They include:

  1. Volume: the scale of data;
  2. Variety: different forms of data;
  3. Velocity: the analysis of streaming data; and
  4. Veracity: the uncertainty of data


The volume—or scale of data—is significant.

Thomson Reuters estimated we are at 800 exabytes of data—and growing.

That number is so large, it’s hard to put it in perspective.

The point is that every, single one of us has access to a gigantic amount of Big Data that can be used to measure our efforts.

But not only that, it can be used to understand what is working and, more, what is not.

While none of us ever want to be wrong—and we certainly don’t want to have to admit it to our clients or bosses—wouldn’t you rather have Big Data tell you what you need to know so you can fail quickly?

I know I would.

Use the sheer amount of Big Data to help inform your decisions.


With variety, you have both structured and unstructured data.

Think of structured data as the information on your bank statement.

It’s easy for a computer to define things that fit in a database, such as date, amount, and time.

Unstructured data, on the other hand, includes things such as blog posts, tweets, and audio files.

These things don’t easily relate to a database so it’s difficult for a computer to, well, structure it.

You want both kinds of information in your Big Data pull.

The technology will help you make sense of unstructured data.

For instance, it could be website traffic that has come from a specific story, even though it didn’t include a link.

Or it could be an analysis of your key messages in an article, as compared to the other experts cited.

We’re very, very close to having that information at our fingertips.


Velocity is the frequency of incoming data.

If you have an ice cream shop with a loyal customer card program, you want to know how often those people come in and how much they spend.

Likewise, you’d want to know how they found you to begin with.

Did they walk by? See an ad? Read a store update in the paper? Learn about you from a friend?

All of this data is available to us, and it’s coming in via Facebook status updates, Instagram photos, text messages, or credit card swipes.

Being able to manage the velocity of our Big Data will help us make informed decisions that support our instincts.


The veracity simply means is the data trustworthy?

And that, as it turns out, is the role of Big Data.

Because it’s all machine learning, there isn’t human error in it.

But you still have to use your gut and your brain to determine if the data pulled is the correct set or if you need to analyze it differently.

As we continue to move at record speeds toward artificial intelligence, machines will do that for you.

How Communicators Should Use Big Data

After we got that incredibly useful lesson from Alex, I asked how communicators should use Big Data.

He said, no matter the size of your organization, there are four questions we should constantly ask ourselves:

  • Are we collecting data?
  • Where are we putting the data?
  • How are we storing our data?
  • Once we have the data, what do we want to know?

Perhaps, right now, all you want to know is if your communications program is driving sales qualified leads.

As you grow the program, you can eventually ask if it’s converting to sales and driving profitable revenue.

But, in many cases, the role of the communicator is not to drive revenue.

Rather, it’s to gain leads.

In the ice cream shop example, the role of the communicator would be to get a ton of people there.

But what if the shop is closed? Or the manager is late opening? Or they ran out of ice cream?

The communicator cannot be responsible for lack of sales, in that case.

Big Data will give you that kind of information versus making it sound like you’re being defensive.

(I know many of you have been in that situation.)

Figure out what you want to know and then start collecting the data to support (or help you tweak) your goals.

Use Big Data to Inform Your Decisions

When I began my career, the only thing we had to “measure” our efforts were media impressions and advertising equivalencies.

They’re totally bunk numbers, but that’s all we had.

Today, we have a gigantic opportunity to use Big Data to inform our decisions.

We now can tell a client or an executive exactly how we affected leads or sales (or both).

The information is there. We have to ask ourselves those four questions and get to work.

I, for one, love my career right now because we can measure our efforts to real business results.

It’s about freaking time!

Gini Dietrich

Gini Dietrich is the founder, CEO, and author of Spin Sucks, host of the Spin Sucks podcast, and author of Spin Sucks (the book). She is the creator of the PESO Model and has crafted a certification for it in partnership with Syracuse University. She has run and grown an agency for the past 15 years. She is co-author of Marketing in the Round, co-host of Inside PR, and co-host of The Agency Leadership podcast.

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