TRANSCRIPTION OF EPISODE
Chris Battis: On this episode of intent topics. We’ll be talking about intent data with Ed Marsh and John McTigue with intent data.io. Logan how’s your day going buddy?
Logan Kelly: Good man. How are you doing?
Chris Battis: Great, great. I’m psyched. So today we have John McTigue and Ed Marsh of intent data.io welcome gentlemen.
Ed Marsh: Thank you Chris. Great to be here with you guys.
John McTigue: Nice to be here.
Chris Battis: You got it. You got it. So today I wanted to talk about all things intent data. I guess we probably won’t cover all things but definitely specific intent data conversation today. But real quick, before we get going, John and Ed, do you mind giving just a quick background on yourself?
John McTigue: Ed, why don’t you go first?
Ed Marsh: Yeah, sure. Absolutely. I mean for the last 10 years I’ve been into digital marketing community. I think where we’ve been, well, many of us on this call have been traveling in the same circles together. But before that I’ve done a lot of industrial stuff. I’ve done a lot of international stuff set up and ran a company in India, was partners with a German company. I’m a consultant also for industrial manufacturers on strategy and revenue growth and so done a lot of different things over the years.
Chris Battis: Very cool. John, how about you?
John McTigue: Well, same here. I started out in the oil and gas business about a 100 years ago, but I’ve been in sales and marketing for about 40% of that and more recently was the co owner of Kuno Creative, which is one of the first HubSpot partners and inbound marketing agencies. I semi retired from Kuno in 2017 and Ed and I wrote a book together called Common Sense Sales and Marketing and so we’ve been collaborating for quite a while and I joined him a few months ago to come on board with intent data and take it to the next level.
Chris Battis: Nice. Yeah, real quick on that. So I was definitely not the first HubSpot agency by any sketch of the imagination. But back in the day, I always aspired to be like Kuno and read everything I could get my hands on that you guys put out. So John, it’s great to connect with you again years later
John McTigue: You were the one guy that wrote that read everything.
Chris Battis: I skimmed it, let’s say, all right. But when I saw that so intent data.io was on our radar, I had been noticing, but when I say join I was like, Oh wow, this is cool. Because for Logan and I and us at union resolute we very much think of these days, they remind us of the early days of inbound marketing and it’s exciting.
Chris Battis: We don’t know exactly where it’s going and we’ll talk about your predictions a little later, but we feel like there’s just a big business shifts going on right now. So I was intrigued when I saw you join intent data and that’s why we originally reached out. So it’s good to have you on the show.
Ed Marsh: Thanks for having me.
John McTigue: Yeah.
Chris Battis: So I guess, Ed, why don’t I start with you. So how did you guys get into this intent data business?
Ed Marsh: So the same way most of us get into things that we’re doing by accident, right? I mean you have a plan. You know the kinds of things that you enjoy doing, the kinds of people you like working with generally the type work you like doing, but life’s an adventure.
Ed Marsh: And so I reconnected with a classmate of mine from college who was a data scientist and who had developed a set of tools to do things with intent data that nobody else was doing that were really intriguing and started working on that with him and some others and developing the market for it and understanding the applications and the use cases and then reached the point where the casual way that we’re doing it wasn’t doing a justice.
Ed Marsh: As you say, this is an early stage and rapidly developing market. And so one handle recommended back on the beginning of this year that we set it up as a separate business start running it that way. I thought that made a lot of sense. And so that’s how we ended up where we are now.
Chris Battis: Awesome. Yeah, and it looks like from what I can see on YouTube that you’ve generated quite a bit of content around this topic, so you’ve definitely been thinking about it for quite some time now?
Ed Marsh: Yeah, absolutely. And it’s funny to hear you say on YouTube because I tend to think of this is a perfect sub topic about content and how people engage and what things are interacting with I think a written content first and YouTube second and everything different for different people.
Chris Battis: Yeah. It’s interesting not to go too far down a rabbit hole, but we, Logan and I are as a union we’re definitely very intrigued by more video content and the ability to use that words that you read versus visual content. So we’re making a big push right now. And the other thing that’s interesting is there’s not a lot out there explaining all this going on right here. So there seems to be an opportunity there.
Ed Marsh: Absolutely.
Chris Battis: So yeah. So John, how did you get into it? Were you looking at intent data before you started intent data IO? Or how did this come about for you?
John McTigue: Well, I’ve been a data nerd since the very beginning of time. So I actually, one of my first jobs at Shell Oil was data manager. So my job was to combine databases across Shell Oil exploration and production and make sense out of it. So I’ve been in that mode for a long, long time. And when it comes to sales and marketing data same idea, how do you manage all these different applications and how do you manage data and make sense out of it and make inferences that you can use in sales or anything else.
John McTigue: So it’s a passion of mine. And I’ve been interested in what Ed was into and working on. So that was really what attracted me in and having an opportunity to help it grow is also fun for me as well.
Chris Battis: Of course. Yeah. That’s half the fun there. Yeah. And it’s interesting that the whole inbound marketing rotation though it probably already existed. It really drove people to think in a data-driven way about their marketing. And that was a big pillar to that. So I could see it being a natural fit for you. I’ve seen you speak quite a bit about data-driven marketing decision making and stuff like that.
Chris Battis: So it ties in naturally. So I guess there’s a bunch of data sources out there at varying levels of where they are as a business right now. Could you probably started with you Ed, could you talk a bit about the different data sources and maybe specifically about the content level data that you guys are creating and how these different data sources differ and how to use them et cetera.
Ed Marsh: Yeah, absolutely. So you flipped my switch by asking that question. So if you need to show me up, just tell me I’m saying but-
Chris Battis: Let them run.
Ed Marsh: You’re absolutely right. I mean I think our space like every space these days must have a minimum of 1,700 competitors and it seems like there’s so many companies doing it, but you’re also absolutely right that there are differences and those differences are in the business model. They’re in the way data is collected there in the way data’s delivered there in the insights that the data provider supplies the degree of coaching and consulting.
Ed Marsh: And so just quickly among all the data options there’s databases. A lot of people are familiar with those from an outbound sales perspective. Some of those are incorporating some intent signals in the background. There’s website de anonymizer so that when somebody visits your site, if they don’t convert, you try to figure out who the company is and maybe suggest some contacts.
Ed Marsh: There’s predictive tools that look at projects you’ve worked on, companies you’ve won or lost, deals with and try to extrapolate from that who might be good target accounts for you. There are ABM tools that now include some third party data. In many cases third party intent data, which is really primarily what we’re talking about is designed to tell you what’s happening everywhere else on the internet as opposed to things on your site.
Ed Marsh: But that’s only a small portion of what’s going on. But the different models include harvesting signals in different ways from different ranges of sites. In some cases its small collections of publishers sites. In some cases it’s the entire web. Some of the ways signals are observed range from looking at activity from IP addresses and trying to resolve those.
Ed Marsh: And other cases that’s looking at people who’ve been shown bit stream ads. So there’s lots of different ways to approach it. Our model is based on watching people take action online publicly. And those are really two key elements of it take action and public. And so we think that in the world today, those are important in terms of people’s comfort with what goes on online and what that does is lets us deliver contact level information, which is really unique.
Ed Marsh: There’s a lot of data providers that will provide static sourced contacts to match accounts where they see activity, but it’s just a pure groups about who’s taking that action. And if you’re selling to enterprises where the department has 100s or 1,000s of people, that’s often not really enough. And so we’re really excited about providing contact level data.
Ed Marsh: And then with that contact information comes a lot of insight. You can understand the context of the actions somebody’s taking and their job titles. So you know seniority and function is stage and buying journey and problem they’re trying to solve and competitors are engaged with and all kinds of cool stuff.
Chris Battis: Very nice. That’s awesome. Have you been finding a lot of success with companies using your data and in a lot of testimonials and case studies coming out of it or is it going as well as planned?
Ed Marsh: Yeah, absolutely. I mean people are, I guess the honest answer is people that are a little skeptical at first, many people have tried some third party intent data. Many people have tried products that are called intent data and they get an interesting inkling, well, geez somebody at Oracle is interested in doing something and then they say, “Well, that’s really cool to know, but what’s next?”
Chris Battis: What am I supposed to do?
Ed Marsh: And so for people, I’ve had that experience, as soon as they actually see the data we’re able to provide, they get really excited. Light bulb comes on.
Chris Battis: Yeah. They can probably move towards creating a playbook for you see this, this is what we need to do prior to the having the data it’s just trial and error, right?
Ed Marsh: Right. Exactly yeah.
Chris Battis: Or analyzing your past experiences. So that’s a big piece of what we do at union is there’s the data there’s folks like you that provide the data and what we’re trying to do is shape content and do human outreach using this data. And we’ve been having great success with it. And nothing’s more fun than hearing a client get excited about how they just can’t believe that we reached out to someone and that person was like, “Oh, as a matter of fact I happened to be like looking for XYZ.”
Chris Battis: And we’re like, “Oh, what a coincidence right?” So that’s always good for us because it helps validate what we do. Especially because in any sales environment it strikes and gutters on a day to day. So to have that reinforcement is always good there. Hey Logan, can you talk to some of your experience using some of the tech data that you’ve been able to get hold of? Has it been working for you? Any tips or tricks that you’ve been finding success in?
Logan Kelly: Yeah. So I think with the contact level data, it’s really opened up where it’s way behind the curtains of what we’ve seen with some of the other stuff, like a Bombora, which is very high level. At the account level and then you have to, it’s hard to triangulate who the contact is and really figure out what the approach is as opposed to what we’re starting to build with the intended data or stuff where it’s like we know where we’re going to approach in the company, who we’re going to approach and then also what they’re looking at, which is amazing.
Logan Kelly: So Ed, how have you helped some of your clients sort of approach the fact that you could have from say sea level all the way down to a manager. How have you helped your clients approach where the ICP but also like the ideal role and those difficulties when they’re building the outreach?
Ed Marsh: Well, I’ll answer quickly, then I’ll let John run with it. But I saw the other day to CEB or I guess it’s a challenger sales organization now or whatever the name is, has updated their 6.8 buyers on a complex buying team stat to 10.2 and you talk about strikes and gutters, I mean sales is getting hard. It is really, really, really hard. And the reality is knowing who’s involved and what stage different people are at and in their buying journey and the problems that each are trying to solve and titles and functions is critical Sales intelligence and critical marketing intelligence to help BDRs personalize what they’re doing.
Ed Marsh: But I love the way John brings his data analysis. So when he talks about doing all a scatterplot or this or that and thinking about it in ways that aren’t as natural to me. So John, how would you answer a Logan’s question?
John McTigue: Well, I think, the interesting thing about intent data that you don’t get otherwise is sort of the time dimension. So when are people doing what they’re doing? What they’re doing is very important. Are they searching on certain keywords, are they following certain people? Are they attending a certain conference? What are they doing? And why is very important. But also as when. Well, as you start to see different people sort of grouping together.
John McTigue: So an example would be a buying team and you can see that several of them are active right now, yesterday. So you can infer from that, that they are talking to each other. They’re sharing resources, they’re looking at the same stuff, they’re talking to each other. So it’s a different dynamic. It’s not just a single person that is showing intent, it’s a whole team. And we can start to prioritize accounts that way. These guys are really about to make a decision, we need to jump on this so we need to get, ramp up the activity of it.
Chris Battis: Yeah. So I love that you said that the time dimension, right? And in our earlier months, Logan was more of the guru went on this and he was trying to get us up to speed or more specifically me, but the phrase that resonated with me was the right contact with the right content at the right time and that’s front and center on your website, which I love because that is exactly what this is about because it’s not terribly hard in 2019 bringing on 2020 to contact the right person with the right content. But the right time is, it’s just the killer here and I think that’s a special piece of what’s going on here. So I like that you call that out.
Ed Marsh: Sure that Chris is that there’s a third dimension. The right contact at the right time with the right or the right contact with the right content will be different depending on the situation. Let’s say for instance decision makers, everyone loves to talk about decision makers except the decision maker is not the person often really involved in the evaluation and comparison and research and all that stuff.
Ed Marsh: And so if you say, well, we see signals from an account, so let’s go find the contacts if we’re some marketing software, let’s go find a CMO. Well, the CMO probably will have to sign off on it, but isn’t really the one that’s leading that effort. And so how do you know who it is is leading that effort. And that’s why dimension is really complex.
Chris Battis: Yeah, it’s totally, and we talked about there, Logan talks about that a lot and I think what he’s called is organizational altitude, right? And everyone seems to think that you want to talk to the top of the food chain, but that’s certainly not the case, especially when it comes to evaluation of a product or service. So that’s an important piece to articulate.
John McTigue: The other thing is that the entire buyer journey is something to focus on now too, not just the initial sale. So as the customer matures and has support problems or issues and they might start looking around at other competitors of yours. You’d want to know that and what kind of data you keep running. It’s not just a sales thing, it’s a support customer experience things. So it’d be very valuable throughout the journey.
Logan Kelly: Yeah. One of the interesting things that we’re seeing because that being in the business we’re in, we hear and we talked to a lot of like MQL providers, right. And they’re selling these leads that are so early funnel. So yes, you can send me an ebook or, because we’ve seen them potentially looking at other content, et cetera, which is another use case for intent data is generating MTOs.
Logan Kelly: And it’s interesting to see how much more effective it is to actually serve the content to somebody and then harvest them as a sales qualified lead two or three months later, five or six touches later than it is to necessarily just be looking at it where like it’s like, “Oh this person is about to make a decision.” Because I don’t see that as intent data or I don’t see that as the real power of intent data.
Logan Kelly: I feel like it’s more, and you guys can agree or disagree, it’s more of understanding where that organization is in the buying journey. And that’s what’s interesting about like the scatterplot and graphic and art. Because we look at it like a curve. There’s the rise of the data signals and then there’s the fall as conversations start to become more internal and more in that sort of buying group where you don’t get intent data what’s going on in the board room. Right? So have you guys seen the same thing?
Ed Marsh: I think it’s reflected in conversations that we have about what’s the right to describe intent data. Some people call it leads, some people call it sales intelligence or marketing intelligence. And on the one hand that feels like an insignificant semantic difference. On the other hand, it really changes the way you think about it. And I agree Logan and I’ll let John speak for himself, but I think he does as well that it is intelligence that really fleshes out in a multidimensional way what’s going on as opposed to a lead, like somebody that converted on some syndicated content or something.
Logan Kelly: Right, exactly. Yeah. And like, I think the big thing, at least in my eyes what the lead is like, when are or what is the involvement of a sales person with that lead? And so is it like they’ve consumed some content so you get it into the hands of the sales person or is it there’s a good reason for that salesperson to be engage in that conversation as opposed to, “Hey man, here’s a list of 30 people that have like looked at something, go for it.”
Logan Kelly: And I think that involvement of the salesperson is really how we have to look at is it a lead or not? And that’s an art at an organizational level.
John McTigue: Well, and if you think about the word intent, you might think that the word means that they’re going to buy right now. And that’s not really the case. There’s a whole spectrum of intent that includes not even knowing whether you need something or not. And it’s your job to influence that whole process throughout the journey. And that involves social media, content, distribution the whole nine yards. So it’s about targeting, but it’s not about waiting too late and the journey you’d want to be there ready to go as soon as possible.
Logan Kelly: Absolutely.
Ed Marsh: And in fact, part of what we do with our data in contrast to topic based models that are opaque and you pick a few topics and you try to interpret based on action across those topics, even though you don’t know what’s behind them, we say, okay, here’s the key term for instance, if somebody has taken action with, and so you’re able to gauge where they are in the buying journey and you’re able to tailor the sales enablement content that you share or the sales outreach or whether, in fact there’s not even sales outreach, but maybe just social engagement or maybe just paid social ads with very carefully tailored inappropriate messaging to help somebody along over the course of a month or two to the point where they do convert and then they’re ready to have a conversation.
Chris Battis: Yeah. And, and assisting them trying to figure out what they’re trying to solve too, is the ability to do that more powerful than ever.
Logan Kelly: Yeah.
Chris Battis: Well so cool. So-
John McTigue: All good and said you’re getting to this, but you can envision not too distant future where predictive algorithms start looking at this behavior over time. Not what sort of a static approach to, “Hey, this looks like a qualified lead and you might want to contact this person.” It’s more like we think that this person’s already done this and this and this and this and the next step is this and you should take this step. It’s right there I think is where we’re heading with this thing.
Chris Battis: Yeah. Like the predictive playbook. Logan’s I hear you’re charming in.
Logan Kelly: Yeah. And that’s what when we look to onboard clients at union it’s like are you looking at specific verticals and are you looking at specific industries? And I think the more under stair, the deeper and understanding a company has of who they’re selling and what the value prop is and what the differences between different verticals is really how we can drive to that.
Logan Kelly: That as Chris said, the predictive playbook and that’s what I see a big value with intent data.io because you’re getting so much information that can then be sort of float into these internal systems that if you’ve got to set up right intended at data.io, it’s just a massive amount of really powerful insights and that’s, I think you guys have the best chance of being able to build that prediction where as that like ambiguous topic based stuff. It’s a cool signal, but I’m not sure how actionable it is in my experience. And so that’s what’s really interesting over the coming say year.
John McTigue: Yeah. And I think most BB companies suffer because they don’t have much internal data. They don’t collect, they don’t have that many visitors. Let’s face it. And so you can’t do that much with their own data. So this is quite a nice addition to that arsenal.
Chris Battis: Yeah. So Ed I’ll start with you and John you brushed on this a little bit, but Ed, where do you see this entire intent data business going in three, five, 10 years?
Ed Marsh: So I believe that intent data will become background noise and discussion will be about marketing and customer data and not just in the context of regulatory and privacy concerns, but in the context of how companies actually use it and interpret it to improve the customer experience, the prospect experience and the buyer experience and the customer experience.
Ed Marsh: And so I think that intent data as we know of it today will be an important piece, but it will be subsumed into a much bigger topic where right now as a buzzword, it’ll become an element of a bigger topic over how to manage data.
Chris Battis: Yeah. And how to read it and make decisions off it and probably even visualize the data. There’s probably things coming out there.
Ed Marsh: Right.
Chris Battis: John, what do you think kind of same sentiment or anything you’d add to it. Where do you think this is going?
John McTigue: Yeah, I’ll just take off on that last point because there are so many sources of data and there’s so much data to consume and there are so many applications that use it that it’s become almost impossible to manage that even from a large company’s point of view because they don’t have the resources.
John McTigue: It’s becoming a thing hiring data scientists and operations people and all of that. But there’s still a lot of challenges in involved in orchestrating all that data and doing something useful with it. So that’s a problem we’re working on ourselves as sort of an a new service that we’re rolling out this next year and-
Chris Battis: Yeah interpretation service in a way.
John McTigue: … well, orchestrations a good word for it. Really putting all the data together, normalizing it taking the errors out, sort of making one source of truth for customer data and then automating the process of putting it out there where it’s useful. It’s going to have some AI in it. All those buzz words. But the practical and the practical business end of it is that it’ll be a lot easier for marketers to hit the right people at the right time with the right content using all these different signals.
Chris Battis: Right. Well, cool. So you must be talking to a fair amount of hopefully a ton of companies that are talking about thinking about trying to make decisions around using intent data. What advice would you give a business that wants to start or knows that they should be starting to implement this into their sales process? What advice do you give or would you give companies looking to do this?
Ed Marsh: John you want to go first?
John McTigue: Well, I think the first thing to do is think about what you’re going to do with the data. It’s important to understand it’s not just about calling a list, that’s 10 year, 15 year old thinking. It’s about really putting it to work and like you guys do, finding the patterns, finding the meaning or the insights.
John McTigue: And then figuring out what to do with it in terms of marketing or sales and we ask people when we do our own sales, we ask people how they’re going to use it because it’s so important. And I think people need to think more about that going forward. Not just about logistics. It’s about really strategy and how you going to utilize this data to make it work.
Chris Battis: Yeah. It’s turned into this thing that people know they need to be talking about, but you really need to zoom out or zoom up. Right? And set some goals. Like what are you really trying to accomplish here? It could be many things. And how about you what advice would you be giving?
Ed Marsh: So two things. One high level and one tactical. Number one, although a CEO or a CMO is not going to typically get involved in a conversation about intent data, aside from perhaps saying yes, it’s something that we think should be part of our stack. I would argue that they probably should be not in the day to day granular detail of it or looking at it or reviewing it.
Ed Marsh: But the reason I say that is because the right intent data, and obviously I’m speaking specifically about contact level intent data can have applications across silos, across departments and across the entire enterprise and more than just demand gen tech, target accounts sales and churn reduction, but really across the enterprise.
Ed Marsh: And that can enhance alignment, it can enhance cooperation, it can even do things like you’ll find opportunities in the corporate development space or places that are really strategic to the organization that people don’t think of when they think of intent data in the typical demand gen context.
Ed Marsh: So that’s a valuable thing. I would say more tactically, be aware that you’re going to encounter limitations in the typical Martech stack. And then often we have conversations with people and they say, “Well, who should we contact first? Or where do we start? Or how do we begin to interpret it? And so an easy answer as well, good question. Let’s look and see where there’s overlap between recent first party data that you have.
Ed Marsh: In other words, people from your logos that have taken action on your site with your content new conversion. That’s where that intersects with the third party data. You know, maybe there’s one person that converted on your site, but there’s five people from the same company taking some related actions that you see in third party data.
Ed Marsh: You got to see that connection that intersection and people say, “Oh, that’s great absolutely.” We’ll go do that and then they stop and say, “Wait a minute, how are we going to do that in our typical Martech stack?” Regardless, marketing automation platform, the CRM, that’s actually deceptively hard to do. So people need to be ready to start to think about their marketing technology stack a little differently.
Chris Battis: Yeah, and being nimble. Yeah. Great. Well, this has been a great chat guys. Thanks for joining us. I’m Chris Battis.
Logan Kelly: And I’m Logan Kelly. Thank you so much for stopping by. Please give us a five star review on any podcast after you listen on and we will see next time. Thanks guys.
Chris Battis: Take care.