An Introduction to Intent Data
Ed recently joined Meghan McGrath (@MegMcGMarketing) for a discussion on Intent Data during an episode of the Talking Marketing podcast of the American Marketing Association (AMA)'s Boston Chapter. You'll find a link to the episode and a lightly edited transcript below:
Meg is the president-elect of AMA Boston (@amaBoston), and a talented and powerful voice in the rapidly growing Boston area marketing community. She and her colleague Chris Goodnow (@CGoodMarketing) are doing a great job building the podcast. So be sure to listen, and if you like it, give them some 5 star ratings love, subscribe and share it.
Their efforts are enabled by another Suzanne Bates (@CEOCoachBates) - an amazing woman entrepreneur. Meg & Chris both work in the marketing team at Bates Communications in addition to their roles with the AMA.
Transcript
Megan McGrath: Hi everyone, and welcome to Talking Marketing, an AMA original podcast series keeping marketers in the know. I'm Megan McGrath, VP of content marketing for AMA Boston, and we're excited to welcome today's guest onto the show. Ed is an international business consultant and the CRO of intentdata.io. Is that right?
Ed Marsh: That's it.
Meg: He's graduate of Johns Hopkins and a former US Army airborne ranger. He's deeply involved in the Boston area MarTech scene, working with Hubspot, Drift and others. Ed's a board leadership fellow with the National Association of Corporate Directors, a keynote speaker and the Export Advisor to American Express.
Meg: Ed, welcome to the show.
Ed: Thank you very much, Megan, I'm thrilled to be here today.
Meg: So today, we're talking about intent data, and Ed, I was hoping you could start us out by setting the scene on what it is and why it's important to marketers.
Ed: Sure. I think implicit in the name is data, and data is so much a part of what marketers are doing now. You have CFOs that are now running marketing departments in many cases because it's about the numbers. And so to the extent that marketers can embrace data, both to understand what they're doing, what works, what doesn't, but also to enrich their understanding of the prospects, it becomes a really, really powerful tool.
Meg: And so today you'll probably dive into how we should be using data. So do you want to start out by defining for us what intent data is?
Ed: Absolutely. And you say how we should be using data. I think the interesting thing is that this is really wild west. There's no common understanding of terms, of definitions, of how to use it. Many companies are experimenting, and the best practices are really being developed because it's been rather immature, and as the quality of the data and the types of data improve, then the way people are using it chang as well.
So what is it? On the one level, G2 Crowd has called intent data the ultimate conversion tool. It really is potentially powerful stuff, and it's going through this amazing growth right now. There's recent series A investments that that we've seen, Leadfeeder in Scandinavia. There's also consolidation that's already happening. Aberdeen just recently acquired Big Willow. So it's at this weird phase where it's growing really rapidly, but it's also starting to consolidate.
But to try to step back and understand what we mean by intent data, at least using some commonly accepted understandings, we have to think and understand in terms of first, second and third party data, and the differences are pretty easy. First party data is what you see on your own site, on your own properties with your own social media accounts, etc. Second party data is what you can obtain ... TechTarget's a great example, where you buy leads from their opted-in subscribers, and they report specifically what kind of action somebody's taking. Third party data is data that's obtained from the rest of the internet, and there's some misunderstandings and limitations with that that we'll probably get into a little bit later. But that's the basic premise of it.
And then there are different models that result in many of conflated terms, misunderstandings and confused definitions. There are database enrichment tools; there are tools to help you de-anonymize visitors to your site. There's syndicated subscription and content models with opted-in readers. There are predictive tools that will look at your own database or other databases and say based on what we see and who's been good customers for you, we think these are likely to be good candidates for you. There's data that's extracted from tools like Bid Stream and AddThis. There's even stuff that just watches anonymous IP address activity surges, and then apends some other personal information on top of that.
Most, and this is I think consistent across a lot of data, most intent data is operating at an account level. And so that's an important thing for marketers to understand, because obviously that can be important information. But so much of what we're talking about these days is built around personalization, that understanding that difference between the account level data and the contact level™ data is really important to help pick the right solution and also understand, as you talked about, how you use it.
I think in a nutshell, maybe the things to keep in mind is that if you look at what works for most companies, obviously people have that first party data. Second party data tools like TechTarget are tremendously popular in the tech community because they're very effective. Third party solutions that mine all of the unstructured data across the internet can be really powerful if they incorporate certain capabilities.
Just quickly, and we'll probably dive in deeper later, but the ability, for instance, to specify keywords, it sounds insignificant, maybe I just pick a topic, demand gen, that's important to me, but demand gen covers such a wide spectrum, and if you really want to use data effectively to personalize, you need to understand where somebody is in their buying journey. So having some granularity of view in that is really important.
I guess the final thing I'd say is variety of signals. Having not just anonymous IP activity, but understanding if somebody is interested in attending an event, understanding if they're particularly following a thought leader, understanding where they are in their buying journey by a specific term, having all the right kinds of signals, even if they're hiring for a certain kind of position, all that stuff becomes really important to maximize the value of intent data.
Meg: I bet most people don't even know that much about the first, second and third party data. That was really interesting. So what are some of the common use cases if someone wanted to use intent data as a tool in their marketing?
Ed: Obviously this is a marketing podcast, and we'll talk mostly about marketing, but one of the really cool things about intent data is that it's not just marketing. There are use cases throughout the customer journey, and then we may even have a few minutes to talk about what that means in terms of alignment, which I think is really exciting for that traditional battle between marketing and sales and ways to overcome it.
But in terms of use cases, on the marketing side of it, the simplest is lead generation - understanding where people are in their buying journey, when they're actively searching. It's said that only 3% of the potential buyers are active at any given time. Who are they? That's kind of the holy grail we've always wondered about, right?
Meg: Right.
Ed: Intent Data is very effective for event marketing. Also, ABM or account-based marketing is becoming so important and popular. It's a powerful tool to plug into that. It can be used by product marketers for competitive marketing, understanding what's going on. And there's another great example in the Boston marketing community. Right now, Drift is a hot topic in conversational marketing, and using intent data to plug into conversational marketing can really create a dynamic in that dialogue as well. (editors note - that's why IntentData.io, Inc. offers conversational marketing add-ons as part of data and service packages.)
And sales, we won't talk long about sales on a marketing podcast, but in sales it can give you insight into complex buying teams. They say 6.8 buyers in a complex buying team these days. How do you know who all those people are? How do you figure out what each is worried about, what they're looking at? 3rd party contact level intent data can give you a great intelligence in that way, gives you competitive awareness where you've got pending deals. Who else is a prospect talking to when they said, "Oh yeah, you're getting the deal."
And it can give you some really interesting information from a sales reps perspective, from the AE's perspective, on what target accounts and prospects are doing. To get a real time alert saying, hey, this interaction has just happened, that's incredibly powerful (particularly at the contact level - if you're selling to organizations with more than 20 or 30 people, account level signals aren't nearly as instructive for reps.)
And then of course on the customer success end of the spectrum, for that entire customer life cycle, there's the opportunity to reduce churn. You see existing customers, they're taking action with a competitor, or the up-sell / cross-sell opportunity too. If you see an existing customer that now is taking action that indicates they're getting ready to buy another product or service that you sell, what a great opportunity for your success team to step in and increase the value of that account.
Meg: Right. Yeah, absolutely.
It's interesting when you make the distinction between marketing and sales, I think in the modern business world, those lines are blurring much more. I think CEOs are demanding marketers prove their ROI more than ever. And we really, I think that age old problem of marketing and sales needing to align is even more serious today because the nature of revenue growth is changing so dramatically.
Ed: Alignment is such a big topic. We see it in the birth of the CRO position, this continuum of that relationship with the prospect and customer. There's a lot of talk about aligning sales and marketing. Unfortunately, a lot of the pitter patter doesn't match the chitter chatter. And this is such a cool tool in order to put actionable information in front of the salespeople, and for the marketers to take credit for it. Now that you've really got that handshake and that collaboration, it's a neat opportunity.
Meg: Yeah, absolutely. And the ROI aspect of it is really interesting too, because I think maybe in the past marketers weren't equipped with as much data to sort of prove their value. It's sort of seen as a fluffy part of the business.
Ed: Like "brand awareness."
Meg: Yeah, exactly. You pick our colors, you make us look pretty. But I think now people really have the opportunity to show their value. So that's great, Ed.
So how do we know when it works?
Ed: Obviously the best case is a company that's got enough size and marketing and sales resources to run intent data side-by-side with the other stuff they're doing. In that case, they have internal first party demonstrable proof that it works.
At a higher level, how do we know it works? Well, anecdotally, I can tell you the churn rate is really low, so that's an indicator that it works. Second, from cases that we've got where people have been willing to share data with us and run it side-by-side, we can tell you that we see 50% close rates and an 82% acceleration of the sales process. Now that's data that's obtained in cases, again, where companies are willing to let one set of marketing and sales resources work with our intent data and another set work with other sets of data.
And then anecdotally, there are some great stories. I've got a client for instance that traditionally sells into the food industry on a B2B basis. One important note - this data is for B2B. And I saw in their dataset, one week in November, a large global toy manufacturer that was taking a lot of actions, a number of people were taking action indicated that they were looking for the kind of equipment this company sells. The sales rep was a little bit dismissive of it, because they normally sell to food companies, and we saw the next same thing the next week, and the sales rep was again a bit dismissive.
And about three weeks later, I get an email at 5:00 in the morning, I'm sitting at my desk working, and the sales rep had just climbed into a car at Frankfurt Airport on the way to the factory of this manufacturer, and with them in the car was the global director of engineering for this global toy company, who was headed there - because guess what? They've got a project and they're buying this kind of equipment.
So you hear stories like that, and you realize, geez, this stuff, not only is it neat at a high level, you look at the metrics, it performs better, you get better ROI on it, but it also works in a very practical, real world sort of way too.
Meg: Sure. That makes sense.
What strikes me about that story in particular too is that I think a lot of times marketers are charged with constantly bombarding people with information about their company. But what could be really key with a tool like this is that you're bombarding them at the right time, instead of bugging them with a consistent cadence.
Ed: Oh, for sure, absolutely. Right people, right time and right message. Again, that granularity, understanding based on keywords or competitors where they might be in their buying journey and what problem they're trying to solve, lets you really ... it's the idea of marketing, everyone talks now about how marketing needs to help people, well now you really can help somebody. It's like being a resource that says I just happen to know, even though you don't know that I know, but I happen to know what's important to you, the problem you're trying to solve, and here's a great solution.
Meg: Right. That's great.
So with all of that in mind, what are some of the barriers that you see to implementation?
Ed: The biggest barrier to implementation is people who think they can just buy data and suddenly the world is different somehow. It's really powerful information, but people have to think creatively about it, and they have to be rigorous in their process of execution. Activation is really important. They have to be willing to use marketing automation and CRM. They have to be willing to run some ads against custom audiences from this data, which they can do on Facebook and LinkedIn. They have to be willing to have an engine of BDRs and SDRs and AEs and all the tools around it, including conversational marketing and ABM that they're willing to apply to it.
If they just think, "Oh, we can buy a list of leads and have salespeople cherry pick and call a couple," often they're disappointed. But if they plug it into that real, well-designed, well-thought out revenue growth engine and get creative with how they use automation around it, that's what we see makes it work. And so the barrier would be if they were more cavalier about it.
Meg: I think that makes a lot of sense. It reminds me of, I've been talking a lot about AI with different marketers recently, and I think people are really apprehensive about AI in the business world. Is it gonna steal people's jobs? Is it going to make everything look completely different? And one of the things that I keep saying as a sound bite is that I think AI is really just going to enable us to do our jobs better. I think at a certain point the technology has to stop and we're still going to expect humans ... at least in my lifetime, I don't know what's going to happen beyond there.
Ed: I know you had Michael Brenner on this podcast recently, and that's exactly the point he made. He said he'd be worried if he was a radiologist, but as a marketer, he thinks it's going to help marketers do better work. It's a neat story.
Meg: Yeah, he's got some great insights on that.
So when we're talking about data, we can't help but talk about privacy. So what are some of the implications about privacy and intent data?
Ed: Of course that's a question that always comes up, and it's asked in a variety of different ways. Should we be nervous to use this? Is this GDPR compliant? People ask the question different ways. The short answer is obviously that you have to understand the specifics of the data source that you're using. So I can speak for intentdata.io, which is entirely GDPR compliant. People can take data, they can take that out of the phone book and be noncompliant with how they use it, but the data itself is GDPR compliant.
The key is to understand how the data is being obtained. Is it obtained from all of the unstructured activity across the web, publicly available information, and aggregated in a way that helps to identify the actual contact? Or is it obtained through some tools that could potentially be an issue with some of the terms of use? A lot of the Bid Stream data and AddThis sort of information may be aggregated and presented in a way, albeit anonymous, but perhaps contrary to what some of the terms of use. (editor note - Shashi Upadhyay, CEO at Lattice Engines discusses this in an interesting article here.)
So I think it's really important for a company considering intent data to not only understand are they getting actual contact details or just arbitrarily apended contact details on top of account level signal, but how was the information collected, in order to be comfortable that it is something that's appropriate from a privacy perspective, because people are particularly aware of that and acutely sensitive to it now.
Meg: Right, absolutely.
We just had a panel discussion, an AMA Boston panel discussion on GDPR, which was really interesting. And I think one of the things that people were curious about was where does the blame fall? Not to throw you a softball here, but where should marketers be cautious when they're working with data. I know you were talking about the first, second and third party data. Where should they stay away from, particularly if they're in a small business or something like that?
Ed: So I actually do a lot of work in my consulting business with US subsidiaries of German companies. And so I live that GDPR discussion in a variety of different ways. My experience with these conversations is if you talk to attorneys and if you talk to other experts, you'll get wildly different opinions on where the line is. And so it becomes really a business risk decision in many cases. And behind that business risk decision, I believe is a philosophical commitment. If you are trying to just sell more, you're probably in jeopardy. If you're trying to help people discover a good solution to their problem, then I think you've got more of a defensible position. And I think that philosophical alignment is probably reflected in the way you work with the data. And so it's not just the philosophy, but it's the resulting execution of it as well.
Meg: Right. And I'm sure working with a data expert like yourself would wouldn't hurt either.
Well do you have any closing thoughts for our audience before we wrap up?
Ed: I would say the thing that strikes me every day as I talk to people about data is how little it's understood. It's not very widely known. Intent data is something which many people have heard of, but they're not familiar with it. And the process, going back to one of your early questions of how you actually work with it effectively, those rules are still being written, those activation and orchestration best practices aren't clear yet.
So I think that it's a great opportunity for people that consider themselves very creative and inquisitive. It's a great opportunity to jump in and experiment with it. If you want something that's proven where there's a playbook and you can follow step 13a and 13a1, it may not be the best fit for you. I think mid-size companies are in a particularly good position because they've got the heft and the resources they need to execute on it, but they've got the agility that lets them be very flexible with it.
And I would just say, step back and take a moment and learn about intent data, because whether you've heard of it and think you know or haven't heard of it, there's an amazingly powerful tool that you can begin to incorporate in a variety of ways across that revenue growth engine.
Meg: Yeah, makes a lot of sense.
Well Ed, thanks so much for being on our show today. Those were some great insights and a great conversation.
Ed: Well thanks for having me, Megan. It was a pleasure
