TRANSCRIPTION OF EPISODE
Chris Battis: On this episode of Intent Topics, we’re going to take a deep dive into what intent data actually is.
What’s up, Logan? How’s it going, man?
Logan Kelly: What’s cracking, dude?
Chris Battis: Not at a lot, not a lot. You ready to rip today?
Logan Kelly: I am. Let’s crush it.
Chris Battis: Great, great, great. So today let’s do a deep dive into intent data.
Logan Kelly: Sure.
Chris Battis: I want to do that because we’re finding the key differentiator in our lead generation business, right? It’s what makes us a lot different from other lead generation companies.
Our key differentiator is really this intent data plus our ability to apply human hustle to do this kind of one-to-one outreach. Whether it’s email or calling or chat, right? And so I just want to establish a better understanding of how we use data and more about what the data is and to make our clients successful. You want to jam on that?
Logan Kelly: Yeah, dude. I think it’s important. Absolutely.
Chris Battis: Cool. Cool. So let’s start with what is intent data? Let’s start with a high-level overview. Let’s kind of umbrella this thing and then we’ll dive deeper. What do you think?
Logan Kelly: Cool. Cool. Yeah.
Chris Battis: Talk to that.
Logan Kelly: Every time we do this fit analysis with all of our clients, or all of our prospects that get to that stage, where we take a few hours with our teams, our data and our content teams, to basically say “on a scale of one to a hundred, is this a good fit customer?” Right?
Chris Battis: Yeah, yup.
Logan Kelly: And what we’re looking for, and I think this is an important piece of intent data is, are there signals that show us what’s going on inside of a company that we can then speak to or build a sales outreach strategy that’s outbound, but it’s still assimilating into a process that’s currently happening inside of a company.
For instance, a company is researching, say human capital management. What are some of the signals or what are some of the pieces of content or what are some of the keywords that we will be looking for that show us that that company is currently researching a specific topic. That is intent data.
Chris Battis: Sweet, sweet, sweet. So generally there’s kind of three types of intent data, right? So there’s first party data. This is the information a business will observe and collect in their interactions with customers, prospects, web visitors. And these are all interactions with their website. Maybe email sending and social channels.
So savvy marketers, they’ll use this to segment communications, do lead scoring and create effective workflows. That’s kind of standard marketing practices. That’s what pretty much everyone’s doing at this point. The next would be second party data. Right?
Logan Kelly: Sure.
Chris Battis: And this is like first party intent data, but it’s collected by another company. It’s like Google AdWords or Facebook or whatever. And the premise here is to observe the actions taken everywhere on the internet, not just on a single site or a network of sites.
But then there’s third party intent data. And that’s what we’re talking about today. So why don’t you dive into the kind of what third party intent data is, because it is kind of evolving daily. I almost call it the Wild West.
Logan Kelly: Sure.
Chris Battis: Every day there’s new sources of data coming out and there’s kind of three types of intent data. Why don’t you talk to those?
Logan Kelly: Yeah, so let’s back up to second party intent data and first party intent data. So what we are looking for in third party intent data is all the things that you get by understanding the content that somebody is looking at on your own website or a collection of landing pages or whatever. Then all the good stuff you get to see what keywords are effective, these kinds of things in second party intent data.
Third party gets scale and then you get to start to see AI machine learning and algorithms aggregating this data. And not just spitting it back out, and this is what I love about 2019 where we are now. That data is not just coming back to you in this raw output of here’s all this stuff people are looking at in the market.
What we’re starting to see from data providers is really insightful readouts of this data. So this particular person location account, we’ll talk about that in a second, is researching these particular topics or these particular pieces of content. And because of that, based on our algorithms, we believe that they are researching X topic.
That’s where I think having a good grasp on first party data and depending on the sophistication of the company, having a good grasp on your second party intent data, it really becomes powerful.
Now let’s sort of set B2B intent data because that’s where we’re talking about here, aside.
Chris Battis: Mm-hmm (affirmative). Right.
Logan Kelly: Anybody who has ever been on a website and then gone to Facebook as a person, like you’re in your private life, you’re a consumer, has experienced where intent data is. But where and Google and retargeting and affinity audiences and in-market audiences, on all these cool platforms that are B2C, they were here in like 2005. So intent data is awesome. It’s powerful. It’s solving for problems that don’t exist in the B2C world.
Chris Battis: Right.
Logan Kelly: But third party intent data is beginning to allow sales leaders, marketers in that B2B space to start to have much more intelligent conversations. It’s never going to be as easy as B2C marketing is.
Chris Battis: Right. So B2B is just now catching up to it and it’s a lot more complicated, right?
Logan Kelly: Yes, yes.
Chris Battis: But the bridge to B2C, I think an example of this would be, say I’m researching on Airbnb a vacation or something, and within minutes, seconds I switched to a different platform. There, they are serving the exact same list. It’s this cross platform observation of what I’m looking into. Right?
Logan Kelly: Right.
Chris Battis: And that’s where the shift is moving into, because that would be a lot easier if everyone was doing business the same way we were as consumers, but it’s a lot more complicated. Right?
Logan Kelly: Right.
Chris Battis: And you’re talking about the enterprise and the IP addresses are different and what people are searching is different, the problems being solved are different.
Logan Kelly: Yeah.
Chris Battis: But that’s kind of the analogy I would use. That helped me understand early on.
Logan Kelly: Yeah. But now let’s add the complexity of B2B. I can go on LinkedIn for Union. Right now off this podcast, I can take a pixel from LinkedIn. I can put it on the website, on UnionResolute.com.
Chris Battis: Yeah.
Logan Kelly: We can re-target people who have been to our site. Right?
Chris Battis: Totally. Yup.
Logan Kelly: So the idea here is we need to, with intent data, we need to start to look at B2B data with a respect for the complexity. It’s not as straight line, right?
Chris Battis: Right, right, right. Yeah.
Logan Kelly: If you re-target somebody who’s been on your website, you might be retargeting the executive assistant of the CEO who does not want to see that in their LinkedIn newsfeed.
Chris Battis: Well, yeah, yeah.
Logan Kelly: Now this is where we get into the third party intent data.
Chris Battis: Mm-hmm (affirmative).
Logan Kelly: Yeah. Cool?
Chris Battis: Yeah. So one thing I’d say is, so with the B2C, it’s like one to one, right?
Logan Kelly: Yes, yes.
Chris Battis: What’s happening with me is going to be different from my wife, different with you. Whereas when you’re looking at B2B, if different people with different roles in the company, and you like to use the word altitude.
Logan Kelly: Altitude.
Chris Battis: Right. So there’s that whole extra dynamic or dimension of what’s going on.
Logan Kelly: Yes, yes.
Chris Battis: Rather than just basically what I’m doing on my phone on the couch. Right?
Logan Kelly: Right, right.
Chris Battis: Cool.
Logan Kelly: Yeah, exactly. Exactly. All right, so let’s go into the three types of intent data, yeah?
Chris Battis: Yeah. Yep, go for it.
Logan Kelly: Cool. Sweet. So we’ll get into kind of the deeper dive on how we use this. But there are three types of intent data that we currently use in our game on a daily basis with all of our clients. There’s account level.
Chris Battis: Number one. Yep.
Logan Kelly: Number one, account level intent data. So what this means is X company is showing signs of researching for particular topics more so than they have been in the past 52 weeks on a scale of zero to a hundred. Okay?
Chris Battis: Yep.
Logan Kelly: It’s important to note that this is at the account level, the company level, the firm level. So it doesn’t care whether Jack Smith who works at Coca-Cola in Atlanta, or John, I don’t know, Smith in Seattle at a Coca Cola plant or whatever searches.
Chris Battis: Just as a sidebar, there’s definitely two John Smiths at Coca Cola. There’s got to be.
Logan Kelly: Oh, definitely. Yeah. Or at least a Jay Smith, right? Maybe not John, but definitely a Jay. Okay. So let’s use the Coca Cola example, right? So account level intent data. If you’re listening while I explain, don’t let what as we go down in the types here, account level intent data, it’s not specific to anything other than the company. But that doesn’t mean it’s not effective. In fact, in many cases it’s all you need and more effective than the other kinds. Cool.
Chris Battis: Right, right.
Logan Kelly: Cool. So now say we moved down, we go to a location-level intent data. Now what we can see is Jack in Atlanta researching certain topics. John in Seattle not…
Chris Battis: Yep.
Logan Kelly: I’m going to look at, but I still don’t know who it is.
Chris Battis: Yup.
Logan Kelly: Okay.
Chris Battis: Yeah. If you could add different locations, maybe they’re doing different things, right? Like they’re all still Coca-Cola, but they could be different divisions, who knows?
Logan Kelly: Exactly. Exactly. Yeah.
Chris Battis: This helps us put the puzzle pieces together, right?
Logan Kelly: Absolutely. Yeah. So with this you can see here’s the location, you can’t see who they are. Then you have contact-level intent data. Okay?
Chris Battis: Yep, yep.
Logan Kelly: Contact level intent data, we use it. It’s definitely the newest kind and it’s nowhere near as scary. It’s nowhere near as scary as what Facebook and Google are doing to us. Okay? This is not picking up data on your phone and and geofencing your daily commute.
No. There are certain websites and certain platforms that people are on that they interact with content, they’ve signed terms and conditions, we get that data. We can start to understand who they are. So we put it together. You’ve got account-level intent data, location-level intent data, and contact-level intent data.
Chris Battis: Yeah.
Logan Kelly: Okay. So have I been clear or am I moving too fast?
Chris Battis: Crystal clear. Gin clear. Yep.
Logan Kelly: Gin clear. It’s five o’clock.
Chris Battis: Well, that’s as clear as it gets, right?
Logan Kelly: Mm-hmm (affirmative). Yeah. Not after you’ve had a bunch of gin.
Chris Battis: That’s about as unclear as it gets.
Logan Kelly: Yeah.
Chris Battis: Yelling at everyone. Yeah. All right.
Logan Kelly: So let’s kind of go into how we use these things. All right?
Chris Battis: Okay.
Logan Kelly: So at the end of the day, so for Union, what we do is sales outreach, one-to-one. We’re looking for conversational, personalized, high touch outreach to prospects.
So with that said, and if we back up to the conversation about why retargeting, it’s a great marketing tool, but I wouldn’t say that it’s not as nuanced sometimes when you use it in the B2B space. It’s hard to get that and it’s hard to get the ROI on that. And that’s why pure B2B companies sometimes don’t necessarily believe in it. Unless you got a huge budget. Because if you have a huge budget, just do stuff.
Chris Battis: Right, yeah. There’s a statistically high likelihood that what you put in front of someone, sure might be the right person maybe. Maybe the messaging’s correct.
Logan Kelly: Yeah, yeah.
Chris Battis: Doubtful.
Logan Kelly: Yeah, yeah.
Chris Battis: Right?
Logan Kelly: Yeah, yeah, yeah. That’s where MQLs suck generally, because a marketing qualified lead, think about this, they go to a site, they download an ebook or whatever. That just kind of ignores the nuance of we need to have the right person involved in the conversation. Just inbound or a media-driven MQL is not necessarily the most effective lead. Media has a place in this but not in actually generating a lead.
Chris Battis: Sure.
Logan Kelly: It’s air support. Right? [crosstalk 00:14:21]
Chris Battis: And I go so far as saying this could drive more intelligent, productive media.
Logan Kelly: Oh yeah, absolutely. 100% yes. So let’s talk about the end result of all of this, whether it’s account-level, location-level, or contact-level intent data. The end result is we need to be starting conversations with the right people at the right time. Okay?
This is what we’re doing, is really working with data providers to understand what signals are they picking up for particular clients. And then just because somebody’s surging that means they’re doing research. That doesn’t mean they’re having necessarily boardroom conversations.
Chris Battis: Right.
Logan Kelly: So if we think about it, when we’re having a conversation, we have two other partners in this company. Right? So you and I have a conversation about something we want to do. We go out, we research, we talk to people, blah, blah, blah.
Then what do we do? We set up a meeting with our team, we start to have conversations, we start to go through a budgeting process.
Chris Battis: Oh, yeah.
Logan Kelly: All of those things you cannot see inside of a company. That’s like Watergate stuff, right?
Chris Battis: And not to mention the speed at which we can act as a smaller company compared to say the Coca Cola, right? Or even as a HubSpot, right? I’d have initiatives, there’d be goals I have to improve things and I do research, I’d prepare a presentation, I tried to get internal buy in, I’d have to revise it.
I mean, there’s a period in my life where I literally walked around for like six months with this same slide deck trying to get buy in, trying to refine it and it took forever. So the point being, just getting the signal loan does not show the actual full story. Right?
Logan Kelly: Right.
Chris Battis: There was just a phase of the sale [crosstalk 00:16:24] and these things take time and ask to get to the right person. Right?
Logan Kelly: Right, exactly.
Chris Battis: Then if I was in a meeting and somebody knew what I was talking about, they’re like “oh yeah, that’s right.” So that needed to be a piece. So selling into something like that requires all these puzzle pieces to understand how to navigate it. Right?
Logan Kelly: Exactly. Yeah. Yeah, exactly. So let’s make it simple. So now once you understand that that the company is surging, now you need to understand there’s certain things that will give you a pretty good idea of what’s happening.
Chris Battis: Right.
Logan Kelly: Let’s look at the structure of the company. Do they have particular roles in their company? This is easy to do on LinkedIn. It’s easy to do in different… And EverString, ZoomInfo or something like this. Right? Do they have roles with specific titles that are relevant to you?
Chris Battis: They’re already hiring, right?
Logan Kelly: Yeah.
Chris Battis: Okay, we’re ramping up, there’s initiative going on where they’re hiring, for example, if they’re hiring a bunch of engineers for their internal business systems. Okay, well what are they building? There’s probably an opportunity there.
Logan Kelly: Exactly. Yeah. So those are different signals. We use hiring as an intent signal as well. Right?
Chris Battis: Right.
Logan Kelly: You can glean a lot from somebody’s advertising for employment.
Chris Battis: Yeah. Yep.
Logan Kelly: But what I’m saying is, look at how a company is constructed. How many VPs do they have? Do they have VPs of everything or is it C-level director? There’s all these different things you want to start to understand.
And this is where we want to start to message into a company. Like all right, we understand the four or five sort of intent signals that we’re getting six, twelve, whatever it is. Now we build our narrative, right?
Chris Battis: Yep.
Logan Kelly: How can we assimilate our client, or union for that matter, into that buying cycle, buying process? Then we need to understand, and this takes time, what’s the typical cycle?
I mean there are companies that we added to our Internal Salesloft that just this week are ready to have a conversation with us. And we added them probably three months ago. But they’ve read everything, they’ve been to the website. We have that first party data.
Chris Battis: Yep.
Logan Kelly: So, you need to have that understanding. Then you need to start to understand how are you messaging into specific roles based on the narrative you’re trying to build.
For instance, C-levels. Don’t talk about tactics. Talk about teams, your organization, your teams, your people.
Chris Battis: Your North Star.
Logan Kelly: Yeah, yeah. But the manager, the director, who’s probably there’s an element of rolling up the sleeves or an element of dealing with people who are really kind of in the trenches on a daily basis.
Chris Battis: Yeah, how we’re actually going to pull this off. Right? Yeah.
Logan Kelly: Exactly. Yeah. Yeah. So they’re looking at a solution in a much different way. Arm those people to have conversations that might be above them in the organization.
But I can tell you, there are so many people who look at C-levels as if they are the only people that they should talk to.
Chris Battis: Oh my God, yeah. Top of the food chain.
Logan Kelly: Yeah. It’s crap. Because I can tell you that that some of the first people, this is a Andrew Grove book, Only the Paranoid Survive, right?
Like Intel pretty much had made the transition to processors without the upper level of the company knowing.
Chris Battis: Right.
Logan Kelly: It kind of happened because these people are making decisions, they’re optimizing their own units. So I think it’s really important to understand that a director, a manager, a VP might have more sway in the decision making process than you would have imagined.
It is a complete failure to say the C-level’s the only person I should be talking about. And this is to say this is where you got to be careful things like location-based intent data, contact-level intent data. We use it, but use with care because the thing about it is there might be some false signals.
Chris Battis: Yeah.
Logan Kelly: A center for GE, like Crotonville, there’s a lot of research going on. That’s their center of excellence though. Right?
Chris Battis: Right.
Logan Kelly: People are going there to research to have conversations. They’re not necessarily making decisions there. So I think that that’s the piece that people have to really be careful on. You need to get the right signals and then match that to the correct roles. Does this make sense?
Chris Battis: Oh yeah. Mm-hmm (affirmative). Yeah, yeah, yeah.
Logan Kelly: Cool. Cool. What I am not saying is taking intent feed from an intent data provider, load that into ZoomInfo and then just blast out 10,000 emails a week. That’s not what I’m saying.
Chris Battis: Mm-hmm (affirmative).
Logan Kelly: Just to be clear.
Chris Battis: I love it. I love it. So, talk about, I don’t know, I guess, what were the key takeaways? I understand the data. I think you’ve done a great job explaining.
Logan Kelly: Sure.
Chris Battis: Let’s talk about the takeaways. Let’s assume everyone understands.
Logan Kelly: Cool. Yeah, yeah.
Chris Battis: So give like one, two, three… Three key takeaways with your experience on other business.
Logan Kelly: Yeah, yeah, yeah, yeah. All right. Three takeaways. First one, figure out what’s actually predictive. There’s a lot of signals that seem cool. That might be awesome. You can see who’s looking at your competitors. You can see who has these… We do things like build the…
This is a different episode, but understand the signals that will be predictive to your outreach. The only way to do that is to get started. The only way to do that is to collect data. But you got to figure out what’s actually predictive.
Then number two, understand your target roles inside the account. Okay?
And number three, strategize on how to build those conversations to be different, but also with the mind that, or with keeping in mind, that those conversations eventually are going to come together. Right?
Chris Battis: Right.
Logan Kelly: So understand what the roles are and then at the end of the day, those people are going to have to talk for a decision to get made.
Chris Battis: Right, right, right.
Logan Kelly: So you need alignment there. So figure out what’s actually predictive. Then figure out who you’re actually trying to talk to. And then figure out what are you going to say, how do they align. And when the conversations do begin, how do we make sure that that pipeline, that lead has good velocity right through your pipeline.
Chris Battis: Okay. Nice. This wraps up today’s episode of Intent Topics. I’m Chris Battis.
Logan Kelly: And I am Logan Kelly. Thank you so much for listening. We will see you next time on Intent Topics. Please give us a five star review on whatever podcast app you listen on. We’ll see you next time.
Chris Battis: Take care everyone. See ya.
