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Podcast: What is the "data" in Data-Driven Marketing?

NetWise May 27, 2021 7:58:40 PM
NetWise-Data-Driven-Marketer

Show Notes:

Welcome to the second episode of our podcast. If we had to give these first few a "series" name we would probably call them, the basics. The first episode was about the idea of data-driven marketing, and why its an exciting time to be a digital marketer. In this one we're starting with some definitions, namely, "what is data?"

We break it down into what we see as the three buckets of marketing data. The data you start with, the data you get back from your campaign, and the "augmented" data sets you can build by bringing in vendor data tools to really pour fuel on your marketing efforts. (Like the NetWise Audience Platform 😉.)

And, because everyone liked last weeks' graphic so much, here's one for this week:

 

Venns Marketing Data

 

Links:

https://en.wikipedia.org/wiki/Data

https://en.wikipedia.org/wiki/Quantified_self

https://en.wikipedia.org/wiki/If_a_tree_falls_in_a_forest

https://en.wikipedia.org/wiki/Scientific_method

Transcript:

Adam Kerpelman:

We have talked about this before. I know what color of post-it I prefer. I don't know if that means something about me, but why won't they let me just buy orange post-its? They come with pink ones and blue ones. The blue, you can't even read your pen on.

Brian Jones:

It seems unbelievable that you can't just buy a single color post-it.

Adam Kerpelman:

I can, but not in the accordion configuration that I want for my little dispenser.

Brian Jones:

I see. That's some fancy post-it note technology.

Adam Kerpelman:

The real answer. The real answer in the digital marketing podcast is probably, "What are you using post-it notes for?" Hey, this is The Data-Driven Marketer. I'm Adam.

Brian Jones:

I'm Brian.

Adam Kerpelman:

Welcome back for another hang in the data lab. What's up, man? How you doing?

Brian Jones:

I am getting by. Been a busy week so far.

Adam Kerpelman:

I hear you. We switched to a slightly later recording slot and now I'm worried that I sound like a frog.

Brian Jones:

I think the concern is that we also added a few other meetings right before this one.

Adam Kerpelman:

Right.

Brian Jones:

So we've already been talking for three hours.

Adam Kerpelman:

Right. You need to do some jumping jacks? Get hyped. Yeah. Well, thanks everybody for joining us for another episode. This week we are trying to flesh out some stuff that I think I wanted to cover for few episodes, before we jump into doing guests and all that stuff.

Adam Kerpelman:

And this one we thought we would hit. What is data, essentially? What do we mean in the context of, quote, data-driven marketing? What do we mean when we say data? Right? There's certainly a lot of different definitions if you just google data.

Brian Jones:

Totally. There's a lot to cover there and you're totally right. Everybody means something different when they say data, depending on the conversation, depending on their job, depending on the project they're working on. There's a lot of data.

Adam Kerpelman:

We even mean different things at different phases in a marketing campaign.

Brian Jones:

Mm-hmm (affirmative).

Adam Kerpelman:

And, so I think important to get that straight in terms of setting the ... I was going to say level setting, and then I was immediately aware that that's one of those canned startup terms. Or canned meeting terms that just ... but, it's fair. Right? What do we mean when we say data? Right?

Brian Jones:

Yep. What do we mean?

Adam Kerpelman:

What's your top level?

Brian Jones:

It's a great question. We didn't frame it that way as we were thinking about the episode. Data is information. I think data is your everyday reality. We just don't think of it as data. And, so I think it starts to become a little more apparent in a business context, which is what our business is. Aids with B2B marketing and advertising. Because all of a sudden, once you're at work, you're all about tasks, and getting stuff done, and doing things, and hitting goals, and level setting, like you said.

Brian Jones:

So all of a sudden you start to think about your day as data. Let me get the info about this thing I need to do so that I can meet the expected goals that somebody set for me. Or let me close as many deals, or talk to this many partners. And, so at home it's not like I need to wash seven plates today to meet my quota.

Adam Kerpelman:

Right.

Brian Jones:

You don't think about things as a data set. But, as soon as you're in a business context, everything is data. Right?

Adam Kerpelman:

Right. I would say it's quantified information in our context, again. Right? Because I would say that I am getting data. I would freely, in a different conversation, say that I'm getting data about the world as I read a Wikipedia article, but what I mean is I'm getting information. In our context, what we mean is it's the cast off, quantifiable information that it comes off of interaction with a campaign. Or even just moving through your day.

Adam Kerpelman:

Right? When you talk to quantified self people, I started to be aware ... Just, you wear an Apple Watch and it's checking your heart rate every minute. As somebody who has had intermittent heart issues, every once in a while I go look at my heart stuff and I go, man, this watch is like every minute checking my heart rate. And I can go read the trail of my heart rate every minute for the last few months.

Brian Jones:

Mm-hmm (affirmative).

Adam Kerpelman:

And that's actually really useful when I have an episode, and I can figure out where that came from. My heart was still beating and still having a heart rate before I started wearing a watch.

Brian Jones:

Was it, though? Was it really?

Adam Kerpelman:

So that data was still there. This is where it gets to the weird philosophical, if a tree falls in the forest territory. But the reality is that that activity is still happening. We just increasingly, with IOT devices, or smartwatches, whatever we're talking about ... and ultimately in our world, digital platforms, we have systems where we can quantify the information cast off by that behavior and put it into usable formats.

Adam Kerpelman:

You were talking about work, but everybody has KPI they're supposed to hit for work. They have an idea of how much time they spend in meetings. If you work in a profession with billable hours, you are very attuned to the idea of how minutes in a day do I spend doing X? Because I have to record it because that's how our company makes money.

Brian Jones:

I like that you just said data is quantifiable information, and information is more broadly stuff you're learning that is squishier. I purposely gave a broad answer in our situation, because I think it's important to talk about the fact that even for a modern data-driven company, who has data-driven marketers working inside of it, a lot of what you're trying to analyze and make decisions from is still really that non-quantifiable information.

Brian Jones:

And, so I think it's really critical for a data-driven marketer to be very conscious of when they're trying to quantify information, and when they actually have quantified data to make decisions on. They're both important, they're both valuable, they're both necessary. You're never going to have just quantified data. Even scientists running the most meticulous of physics experiments don't always just have quantified data. So it's critical that you understand how you go from information to a dataset that you can, essentially, do math to. Right?

Brian Jones:

Because that's the point. You want something logical to be giving you answers to your questions and helping you make decisions, helping guide your decisions. And, so you can't make clean, presentable, shareable arguments just around your experience. Right? That's not a fair thing to do, especially in a business. That's great to do when you're hanging out at a barbecue and you're just like, "Hey, man. How was your day? What did you do last weekend? How did it feel now that you've got two kids?" Right?

Brian Jones:

But, for business it's, well how does that affect my ROI? Right? You've got to make data-driven decisions. And, so you spend a lot of time trying to quantify information. Which is, I think, what is a lot of the art of modern marketing, too. Especially for data people who are trying to be more data-driven.

Adam Kerpelman:

Well, and that's the cool thing we got to in the last episode, which is because of these digital platforms and stuff like that, and digital media, and all that stuff, we're more able than ever to quantify the right things, and pay attention to the right things, to make our marketing more effective, ultimately. Instead of just guessing, or just letting creatives run with it, or tracking metrics that are too far down the funnel to really ...

Adam Kerpelman:

I mean, imagine the world before even the tiniest bit of digital stuff. And, it was just ... we did an ad campaign and then sales went up. And the problem with anyone working in a company of any size, they know that that's just going to result in a fight to take credit for that increase in revenue that nobody can necessarily attribute.

Brian Jones:

Right.

Adam Kerpelman:

And, so then you're making sloppy decisions and maybe make the wrong one.

Brian Jones:

Yeah. I mean, the level of effort, and cost, and complexity to run real physical world studies to understand the impact of a marketing campaign you do in a local geographic newspaper is astonishingly hard. Right? Why data-driven marketing is so available to people now, because there were only a few companies that could do that before. Right? You had to be so large, and so specific, and so sophisticated.

Adam Kerpelman:

And let's be real. Those companies were even probably trash at it because you had to go survey people. And it was like, "Did you see this ad?" And like, "I don't remember, man."

Brian Jones:

Top 2 box scores, and relying on witnesses.

Adam Kerpelman:

Yeah. Right.

Brian Jones:

Totally.

Adam Kerpelman:

I mean, right. It's just as bad as witness testimony in court, which is better than nothing, but lawyers know is meh at best.

Brian Jones:

Meh.

Adam Kerpelman:

People aren't very good. Anyway. So, yeah. So let's get to the marketing context. What do we mean when we say data in the data-driven marketer aspect? Which, I think, gets to the thing where you have to talk through three different phases of data. Or maybe three different types of data, which is essentially the data that you start with as you're initiating a campaign. It's the data that you get from the campaign coming back to you. And then, ultimately, there's this intermediate space where we live, which I think is one of the very fascinating layers that I think it ... it's one of the things that maybe we can start to educate our audience about, because they don't know that they know that it exists necessarily. It's the curator layer.

Adam Kerpelman:

You can do a lot to be more effective with the data that you're getting at that in between step. But let's go in order. What are we talking about when we say the data that you are starting a campaign with?

Brian Jones:

Well, it's anything you know about your market, your industry, potential customers in that space, who buys your products, your product price points, your product categories. Right? It's all this stuff that lets you organize. What do I sell? How do I sell it? Who buys it? When do they buy it? What do they buy it for? What reasons do they buy it? It's what helps drive branding, and messaging, and product verticals.

Adam Kerpelman:

And I think this is the part where the exercise that the data-driven marketer is trying to undertake with this piece of the data is ... another department will most likely come to you say, "Okay. All right. Our ideal customer, our ICP, ideal customer profile is ... " Let's say it's me. Right? It's going to be white male in their late thirties that just bought a house. Right?

Adam Kerpelman:

They know that that's somebody that you want to reach. And that's what we would call segmentation. Right? But the data you're dealing with at this point is essentially segmentation data. Who makes up your audience, and then where are they potentially reachable? I'm not on Facebook so much anymore, but I am on Twitter. And the channels I just mentioned are novel, but this part of the machine is not really anything new.

Adam Kerpelman:

Since there's been marketing, we've been doing this data-driven part of it. Marketing segmentation, not a new term at all.

Brian Jones:

Yeah. Exactly.

Adam Kerpelman:

The, who is your audience, to start piece? Not really anything new. The next two pieces are the pieces where it starts to get interesting because one of them, the curation, touches data science. And it's just so complicated, we couldn't do it before. We'll get to that one in a minute because that's our bread and butter.

Adam Kerpelman:

The next piece is the data you get back from the campaign, and that's what we talked about before. That's data about how people are interacting with the campaign. Which, like we said, the best we used to have was a survey about whether or not you saw this ad before you made a purchasing decision. Now we know if you clicked on the ad. Right?

Brian Jones:

Yeah. I think it's fair to say, before the advent of the internet, almost every company was advertising blind. Right? That's why you had such limited information. Right? You had the little cards that people would send back in, but how infrequently would that happen? Right? That's why the idea of warranties ... got to send this card in to get warranty, it was to gather marketing information. It wasn't for any other purpose.

Brian Jones:

Your warranty, most of the time, I don't even think you can limit warranties, legally. If you offer them, they have to be available no matter what, but the card was to incentivize people to give you their demographic information so that your company could sell your products more effectively. So now we just have so many more places where that information can be gathered, or asked for, or prepared, or quantified. Right? Loose information that can be turned into quantified data.

Adam Kerpelman:

And, ultimately, the data that you're getting from the campaign kicks off the feedback loop that, I think, is the exciting thing about the idea of letting your marketing be data-driven, which is what we talked about before. But I think what we really want to talk about, ongoing, which is why we're putting this in the order where we are as an episode, is the thing to understand is it's not just about that feedback loop.

Adam Kerpelman:

It starts with the data that you started with. Which, in digital platforms, can be the segments ... segmentation almost doesn't even feel like the right way to say it, because it can be more granular in a digital sense, which means you can run tests differently. We get more and different information back from actually running the campaigns. And those two things add together to give us a capacity to make data-driven decisions.

Adam Kerpelman:

And then in between we have this, what we would call a curation layer, which is the idea that you can do other things with those data sets once they're in there. Right? And this is totally that place where people go get degrees in data science. There are things you can do with the information that you're getting to run tests without even having to go back into the campaigns. Because if you're just looking at the data you started with and the data you get from your campaigns, you can try to make decisions, and you can change the starting parameters, and call that a test, and run the whole thing again.

Adam Kerpelman:

But we're getting so much data now in the digital space that you can use platforms like ours on NetWise, to be self-serving, to go and run whole tests that are just, "Oh, well what if we make the segment this?" Well, here's what that audience would look like. Okay. That probably won't work. Let's try this one, instead. You can do all this testing and curation, and then it gets recombinatory in an interesting way, because you can do things like append data that's available in public databases.

Adam Kerpelman:

Which is the cool thing about being in the B2B space, because there's a lot of public information. It doesn't even get into the space that is getting politicized about this, which I don't think we want to talk about at all. But in the business space, that's part of the cost of doing business. Right? If I want to create a corporation, I have to file a list of all of my officers with the state that I register in, so that other companies can look me up if they, for example, want to sue the CEO for negligence or something like that.

Adam Kerpelman:

That's part of the deal. If you want the special treatment, or special tax bracket, and all that stuff that comes with being a corporation, you have to put this public information out there. But that also means that I, as a data-driven marketer, can go look up ... I can fatten my dataset of people that fit into the segments that I'm working with outside of what I started with and what I got, datasets. I can go do that data science on the side and flush out this stuff.

Adam Kerpelman:

And, so that's where it really starts to turn into this crazy multiplier of, well, what do we mean by data? We mean also all the other data that you can add on to that pile if you know where to look. And that just turns into this bag of tricks that I think really gets to the stuff we're going to talk about, ongoing, on the podcast. Which is, what is that know-where-to-look bag of tricks?

Brian Jones:

Yeah. It's really interesting seeing, in the business space, how many different ways you can analyze your market, you can present your product line, how many different places you can go to market, how many different ways you can get your messages to people, how many different value propositions there are. Right?

Brian Jones:

We're a relatively small company and we have a relatively limited product set. And yet there's still so many concepts that apply to our customers, and how they use our products, and how we sell our products, that our entire team can't keep up with it. Right?

Brian Jones:

And I think that, obviously, is a product of our company being in a complex space. But as a technology company, which more and more companies are becoming, what matters about the products just becomes more complicated. So there's so much information about what a company is, and what it does, and what your customers look like, and buying cycles, and decision teams.

Adam Kerpelman:

When you can reach those customers to be the most helpful with the product that you're offering ... An example that's simple, but easy to understand, is there's a reason I see more ads for tax software around March, because they know in a month I'm going to be filing taxes. Right? I mean, and that's an easy one because it's just based on government deadlines. But there's all kinds of stuff like that in the business world where you can better target an ad spend if you understand that it's useless to run those ads on a seasonal basis. The demand for our product is going to be seasonal. We can behave accordingly with our ad spend.

Adam Kerpelman:

And you maybe don't know that. You might have a seasonal product and you don't realize it until you start looking at the data and realize like, oh, nobody ever buys our thing in August because everybody's on vacation. So we can just stop dumping 30 grand in ads every August. Glad we learned that. Yeah. Ultimately, I think the thing we're chasing here is what do we mean when we say data? It's those three things and they all merge together into this data-driven marketer stack of how to conceive of data. Right?

Adam Kerpelman:

There's initial, there's audience data, which you'll constantly be augmenting and changing. And then there's campaign data, which is how the campaign is doing against that audience. And then there's the intermediate stuff where you're trying to learn more, and trying to understand more, and trying to run tests against that to see if you can find anything weird in the middle there.

Adam Kerpelman:

And I think this is the interesting space that is emergent here that's really, I think, hard to get your head around because it's kind of a paradigm shift. Which is, in the digital space, we have put a data point to so much more information now that you have emergent properties ... I mean, I already used the term emergent, but that's what it is. This is an emergent phenomenon of the digital space that allows marketers to run tests to look for other emergent phenomenon that they might not have been able to find just by logicing their way through the problem or just by, whatever. Right? You have to just run the tests on the data and then occasionally you go, "Huh. That was an interesting phenomenon."

Brian Jones:

Part of the complexity here for a modern data-driven marketer is that none of this stuff is linear anymore. It's not just a matter of come up with an audience to target, run an ad, have them buy your product. Right? Especially in a more complex technology space like we play. Not only is that not how you're going to sell expensive business to business products.

Brian Jones:

That kind of represents a lot of consumer purchases. Right? They're small, they're simple, they're just made impromptu. But business purchases, not only is it lots of people that are often involved, but it's lots of touches, is the term. A lot of communication back and forth, a lot of asynchronous communication, a lot of different exposures to your brand, talking to other customers of yours, reading testimonials, and as ...

Adam Kerpelman:

Listening to podcasts.

Brian Jones:

Listening to podcasts is the number one way everyone sells anything. The modern data-driven marketer, and I think this is going to be a common theme, is consuming the sales funnel from the top down. Right? And as that's happening, there's just more and more information, and your campaigns start to overlap, and your communications start to overlap. And then, like you were saying, there's a lot of emergent information in there.

Brian Jones:

And there are ways that you can tie information back on itself. Right? There's ways that you can take multiple campaigns and compare them to see what comes out. And then maybe you come out with a refined, single campaign that took the best aspects of those other things. And then there's other information that you bring in, other information about businesses and the people that work there, that you can then layer in. You can expand, you can contract. There's so much complexity to explore. And there's so many opportunities to optimize things and the pace. Right?

Brian Jones:

The pace is what allows that now. You get information quickly. Real-time is not really ever fair with anything. Even a sophisticated, modern marketing stack. You're not changing everything day-by-day, usually. It's still weeks and months to make really big picture strategic decisions, but there's just a lot to work with and it's really interesting. And it makes this a really ... there's still a ton of creativity in the data side of this, as a profession. Right?

Brian Jones:

I think it used to be heavy. Everyone thinks of the creative side being the images, and the taglines, and stuff. Right? What people think of as the fun part, but this is the fun part too. Right? Is analyzing the data, uncovering these trends, and optimizing things. It scratches a slightly different itch, but it's still creative.

Adam Kerpelman:

Right.

Brian Jones:

I think an important piece to keep in mind here is that it's very ... just despite all of this information, despite all of these capabilities, and all of these platforms, and all of this data, it's still very, very challenging to organize, plan, and execute marketing campaigns, marketing strategies, where you're making good decisions. Right?

Brian Jones:

So if you're listening to this and you're like, "Man, I do a lot of stuff every day and I still don't see signal in the noise." Know that that's okay. Know that if you're thinking, "Oh, man. We were trying to make a decision on all this data. And we came to all these conclusions, but then everyone had different opinions on what the conclusions were." That's okay, too, that it happens a lot. There's a lot of complexity to this. Right?

Brian Jones:

And it really is academically emerging of the scientific method with marketing. Right? It's taking these approaches where what you're trying to do is, really, you're isolating variables, you're doing control studies, you're doing blind control studies sometimes. Right? And you got to come at it with a creative head, but you also have to come at it with an analytic head. It's a real fun combination.

Adam Kerpelman:

And that's, like I said, why we hit this early in our series of episodes where Brian and I just talk to one another instead of talking to guests and stuff, because I think this is important stuff to lay out. What we mean by this and what it means to be in that space. Just because you don't get an answer off of the tests that you're running, doesn't make you not data-driven. You have to keep doing the tests. Right? Any scientist will tell you that they are constantly like, "Well, nothing happened. I hope I can keep my grant to try again."

Brian Jones:

Right? Got to keep your marketing budget.

Adam Kerpelman:

That's just part of the process. Right. But, yeah. Otherwise, tune in for more of this stuff and we'll keep digging in. I think everything you just alluded to, Brian, is some of the stuff we'll get into soon, which is really how the scientific method really applies to this. I think those will be some of the episodes that are a little more in the weeds of how to do data-driven marketing. Those will come with blog posts and all kinds of fun stuff. So, like, subscribe, give us a review if you enjoy the conversations so far. It will actually help us reach more data-driven marketers. Otherwise, this has been The Data-Driven Marketer. I'm Adam.

Brian Jones:

I'm Brian. Have a great afternoon, evening, morning, night, day.

Adam Kerpelman:

Asynchronous media, baby.