The Intelligent Business Show, or TIBS, consists of two things: “intelligent businesses” and how to make businesses more intelligent. Check out our first mini-sode where Jessie chats with Aberdeen’s own Senior Data Analyst, Ben Cavicchi about the innovation of technographic data sets.

Leveraging technographic data is an already outdated approach — scraping job boards can only get you so far. What if there were a method to collect data that determined if a technology was not only installed, but actually used? Well, we’ve done just that. In our first TIBS mini-sode, we’re chatting with Aberdeen’s own Senior Data Analyst, Ben Cavicchi about how he’s leveraged our massive data set to develop a new offering unlike anything else available in the Intent space: Behavioral Technographics.

This Week’s Guest:

“We’ll be able to create [with this data] a highly targeted list of companies; the only ones that {an organization] should be talking to rather than wasting all of their resources focusing on other companies that really, in the end, are gonna say no.”

Benjamin Cavicchi is a Senior Data Analyst with Aberdeen. Benjamin holds a master’s degree from the University of New Hampshire in Economics.

Each week on The Intelligent Business Show (TIBS) podcast, our host, Jessie Coan (Aberdeen’s VP of Marketing), will chat with marketers and sales folks who are leveraging data and exploring new ways to find customers and close deals. We’ll also be featuring novel and exciting insights from our very own esteemed resident thought leaders. Tune in every other week to learn about the latest innovations and the best tricks from your peers and competitors.

Below is the transcript of this episode for your reference:

[00:00:00.00] [MUSIC PLAYING] [00:00:03.37] SPEAKER: Welcome to The Intelligent Business Show, a podcast from Aberdeen discussing the latest trends in marketing and sales to keep you and your business at the top of your game. And now, here’s your host, Aberdeen’s VP of marketing, Jessie Coan. [00:00:17.44] JESSIE COAN: Hi, everybody. It’s Jessie here from The Intelligent Business Show. And we are doing something neat this season. In between our regularly-scheduled episodes, every other week, we’ll be interviewing somebody from the Aberdeen team. I know it sounds a little self-serving. It’s not, I promise. They’ll be interesting conversations. But we’re doing some really interesting things over here, and they’ll be in conjunction with what we’re talking about in between the episodes with our outside guests. [00:00:44.17] So today, I’m happy to have Ben Cavicchi here from our data analyst team. He’s our senior data analyst. Say hi, Ben. [00:00:52.03] BENJAMIN CAVICCHI: Hello, everybody. Thanks for having me, Jessie. [00:00:54.25] JESSIE COAN: Thanks for coming since we sit so far apart. [LAUGHS] [00:00:56.84] BENJAMIN CAVICCHI: [INAUDIBLE] [00:00:57.64] JESSIE COAN: So Ben’s here. We’ve invited him to chat and be our first Aberdeen guest, actually. We’re going to be talking about a new offering that Aberdeen’s put out there. Outside of the new offering, Ben’s doing some really interesting things with our intent data set, and we thought you would all be interested to hear a little bit more about how he’s working with the data, and what he’s finding, and we’ll dive in a little bit. So it should be a pretty short episode, but interesting, as well. So– ready? [00:01:25.34] BENJAMIN CAVICCHI: Absolutely. [00:01:25.65] JESSIE COAN: Ready for your podcast experience? Why don’t you tell everybody– we haven’t teased what it’s called yet, so why don’t you give us a little one-liner or two-liner about what you’re working on. What do you call this thing? [00:01:35.83] BENJAMIN CAVICCHI: What I call it, and what we have termed it, is behavioral technigraphic data. And at a thousand-foot level, behavioral technigraphic data focuses on the usage of the technology, as opposed to the install of the technology at a company. [00:01:49.03] JESSIE COAN: How did you come up with this idea? I know you’ve been doing a lot of digging in our data set and coming up with interesting ways to leverage our intent data. This is a pretty unique one. Can you kind of walk us through a little bit about technigraphic data, and what does that mean, and what does that look like? [00:02:06.26] BENJAMIN CAVICCHI: Well, historical technigraphic data is actually still pretty new for most terms. And the way that it’s most commonly collected, at least in recent days, is focusing on job boards and individual websites to determine whether or not technology’s actually installed at a company. And they do this by, like I said, focusing on the job boards to see if a technology is present within the actual job description. There are a lot of fallbacks to this, and this new method gets around that way. [00:02:32.45] JESSIE COAN: So when you’re looking– companies will post jobs all the time, like if you’re hiring a role. And you’re saying that historically, people have been able to look at those job descriptions and say, oh, OK. We’re looking for an engineer. They have to have the capability of they can answer a VoIP phone. They can use Microsoft Excel. I’m using really silly examples, but there’s specific requirements.
[00:02:50.81] I know in marketing roles that I’ve posted, you put in, here are the tools that you need to have accessible. So that’s the old kind of way of looking at it. [00:02:57.15] BENJAMIN CAVICCHI: Yeah, and it focuses on the technical skills that are typically laid out. But there are major problems with that. A lot of people use duplicate job postings they just copy and paste over and over again. And a lot of the technologies typically have competing or substitute technologies. So what they’re really asking for on the job posting is a set of skills, and they’re getting at that skills by listening a technology.
[00:03:18.56] But there’s no way to actually determine if the technology is used at the company. This new approach gets at the actual usage of the technology. [00:03:25.88] JESSIE COAN: So with behavioral technigraphics, you’re able to determine whether or not a company is actually using a technology that they’re fishing for in the old way of looking at it? [00:03:34.63] BENJAMIN CAVICCHI: For the most part, yes. There’s always room to interpret it, but there’s a simple logic to it, actually. What we do is we focus on the education of an individual about a technology, because that is clear evidence that they use it. So what we’re looking at is a handful or a couple thousand websites that resolve to user tutorials or user forums where people ask questions and answer them about a technology, as well as a host of other, I would say, technology-specific blogs where experts write about it.[00:04:02.94] And the way that I originally approached this is I tried to put myself in the seat of the people that were actually doing this, because I have historical experience doing this. I Google questions when I have to figure out how to do something with a technology. [00:04:14.71] JESSIE COAN: Like the majority of us. [LAUGHS] [00:04:16.37] BENJAMIN CAVICCHI: Yes, exactly. [00:04:17.38] JESSIE COAN: Like the infamous YouLookup. [00:04:18.76] BENJAMIN CAVICCHI: Yes. Everybody uses Google to answer the questions. And for the most part, at least in my historical experience, I didn’t really use the materials that were provided by the company for a given technology. I would just Google single questions as I came across them in my daily work. That’s what I’m focusing on– focusing on these pages that answer these very specific questions that you would have in your daily work working with the technology. [00:04:41.05] JESSIE COAN: Got you. So moving on from how you’ve come up with this idea, let’s talk about some use cases for it, and how we’ve talked to a couple customers or prospects about how we could leverage some of this stuff. I think the use case, in particular, is really interesting in how you can implement this within your organizations. Let’s talk through some of those components. [00:05:00.72] BENJAMIN CAVICCHI: OK. At the highest level, this data begins to provide a look into companies operationally. Now, what that means is that I can determine, again, which technologies are actually used at a company. Depending on what you actually sell, it helps to know this information. If you integrate with certain technologies, it’s good to find the companies that actually have that technology already in place.
[00:05:20.34] Additionally, there are other companies that focus on only servicing certain technologies. So in other words, we’ll be able to create them a highly-targeted list of companies– the only ones that they should really be talking to– rather than wasting all of their resources focusing on other companies that really, in the end, are going to say no. [00:05:34.91] JESSIE COAN: So going back to talk a little bit about the education of behavioral technigraphics, and how you would leverage this, or how it works– I jokingly made the YouLookup joke, but can you talk through that example a little bit? [00:05:47.78] BENJAMIN CAVICCHI: Yeah, absolutely, because I think Excel is probably the best technology to always reference. For the most part, it’s ubiquitous across business. Everybody has touched upon it in some way or another. So the way that I look at it is, you have an individual. Let’s call him John. And John has to do a project, and he needs to learn VLOOKUP to build this project, so John Googles how to use VLOOKUP.
[00:06:07.10] All of the pages that he ultimately visits, we capture, and they’re all indications or signals that he ultimately uses Excel. Now, this individual doesn’t really matter to a company. What you care about is companies, whether or not they use it. [00:06:19.07] JESSIE COAN: John could be Sally, Fred, George. [00:06:20.72] BENJAMIN CAVICCHI: Yeah, exactly. It could be anybody. But the idea is that if you aggregate all of the individuals associated with a company and you look at this historical activity on Excel, you can get a better understanding of whether or not they use it. So other users at his company may be googling other, more advanced things like how to write efficient VBA code, or creating dynamic Excel dashboards.
[00:06:40.58] Well, we capture still all of the page visits that they have, and all of those individual users, all the pages that they viewed, are just signals that John’s company uses Excel, not just John.
[00:06:51.17] JESSIE COAN: Got you. So at a company level, you can tell if there’s increased activity in searches based on a particular topic, category, whatever thing you want to plug in there. [00:07:00.74] BENJAMIN CAVICCHI: Absolutely. Because we capture 365 days of data, we can segment it across basically any dimension of time. And because we cover so much data, so many different websites, we can segment it across individual articles for topics or pain points. So as I said before, if John has other people at his company that Google more advanced things with Excel, those are indications that the company itself is doing pretty sophisticated things with Excel. [00:07:25.70] JESSIE COAN: You can probably assume that they might be interested in learning more about things that plug into Excel. [00:07:29.87] BENJAMIN CAVICCHI: Exactly, or as the way I like to interpret it, Excel is the natural antecedent to a BI solution, a more advanced one. So if you have a lot of people at a company that are writing VBA code, that are trying to create these dynamic dashboards, but they don’t have any activity on any other BI solution, it seems to me that they probably need one. We’re finding the problems of the company, and helping companies to essentially find them, too. [00:07:53.90] JESSIE COAN: Pain points. [00:07:55.01] BENJAMIN CAVICCHI: Exactly. [00:07:56.12] JESSIE COAN: I know that’s your favorite phrase. [LAUGHS] [00:07:57.84] BENJAMIN CAVICCHI: [INAUDIBLE] [00:07:58.58] JESSIE COAN: So it’s interesting, because you’re tying it back to the intent signals. You’re being able to tell– I hesitate to use the word predictive, but we’re firmly headed in that direction with this type of activity– [00:08:12.92] BENJAMIN CAVICCHI: Absolutely. [00:08:13.46] JESSIE COAN: –to be able to understand, OK, there might be some intent here that you should be looking at. If they’re looking at this level of Excel, then BI solutions could say, OK, cool. These are leading indicators or signals that I should be paying attention to. [00:08:25.46] BENJAMIN CAVICCHI: Absolutely. We’re just aggregating different types of signals and ultimately determining not only whether they have it installed already, whether they use it, but what level they actually use it at, and if they have anything else that can replace it right now. And if they don’t, they seem like an optimal target for you to be able to talk to them. [00:08:41.72] JESSIE COAN: Neat. All right, so now that we’ve talked with you– the what, and the how, and the where let’s talk about, jokingly enough, predicting. So what does this mean for the future of data? [00:08:52.47] BENJAMIN CAVICCHI: Well, in terms of intent data, we’re all eventually going to get to prediction. But the way that I look at it, the next immediate step is what I call behavioral profiling. And this is common. This is well known within the B2C space, but for some reason, the B2B space hasn’t been able to figure this out. [00:09:08.23] JESSIE COAN: That’s true. [00:09:09.50] BENJAMIN CAVICCHI: One simple example that I can just tie back immediately to technigraphic data is if you find a company that has a bunch of users active on Python articles, that’s evidence that they use Python, obviously. But the extension of that is understanding who actually uses Python. And in my experience in data science and analytics, it’s a data scientist typically using it, or data science teams, as well as engineering teams.
[00:09:32.19] So it’s being able to take it to the next level and actually profile not only individuals, but groups of individuals in a company. So if you sell, for example, an AI solution or an AI infrastructure solution, knowing which companies are actively using these technologies is very important. And understanding if they have a team that is actually devoted to something that you service is very important, too.
[00:09:54.95] And moreover we can get deeper into those actual articles to find those, in this particular example, with AI. Those that are doing extensive research on actual modeling, high extents of modeling. So we’re finding the companies that not only seem to have a data science team or an engineering team, but those within that set that are doing this research on actual high-level modeling or AI, machine learning, things like that. So these are the optimal fits for this type of company. [00:10:19.94] JESSIE COAN: Interesting. So you’re able to get to another level in terms of identifying– in marketing, we call it not only the buyer, but also an influencer. In a lot of cases, you know, the actual user of the technology versus someone who’s consuming something within the technology. Is that correct? [00:10:35.45] BENJAMIN CAVICCHI: Absolutely. [00:10:36.34] JESSIE COAN: Cool. Very cool. I’m excited. [LAUGHS] I’m excited to be talking about it here today, so great. All right, last question. We ask all our guests this question. What’s the best piece or most memorable piece of business advice you’ve ever gotten? [00:10:52.85] BENJAMIN CAVICCHI: That is a good question. [00:10:53.63] JESSIE COAN: [LAUGHS] [00:10:54.90] BENJAMIN CAVICCHI: I would say it came a couple of years ago, when someone told me not to lose the creativity that I had when you get into the workspace. [00:11:01.88] JESSIE COAN: The creativity? [00:11:02.72] BENJAMIN CAVICCHI: The creativity, yes. Most of the time, I find that people come into work and they get stuck in the same routine, or they get stuck within these workflows, these boxes, essentially. If you lose the ability to think creatively, you lose the ability to address new problems or think of problems in different ways. [00:11:19.16] JESSIE COAN: That’s great advice. I think people who you have a creative field– I think every field, to some extent, can be creative. [00:11:26.92] BENJAMIN CAVICCHI: Absolutely. I think every field in itself is creative. [00:11:29.22] JESSIE COAN: Agreed. That’s a great piece of advice. [00:11:31.07] [MUSIC PLAYING] [00:11:31.67] Well, Ben, thanks so much. [00:11:33.05] BENJAMIN CAVICCHI: Awesome. Thank you so much. [00:11:34.43] JESSIE COAN: Thanks for tuning into this week’s mini episode. In our next episode, I’ll be chatting with Jacki Leahy from Link Squares. I look forward to you listening to it. Thanks. [00:11:43.82] SPEAKER: Thanks for listening to this episode of The Intelligent Business Show. You can find all our episodes on iTunes, Spotify, YouTube, and most other places you tune in to podcasts. Be sure to follow us on Twitter @AberdeenGroup and on Instagram @Aberdeen_Life.

Aberdeen’s Behavioral Technographics provide richer insights to significantly improve account prioritization, ad targeting, and engagement rates. Click here to learn more about how Behavioral Technographics delivers up to 55% greater accuracy than legacy technographic data in determining technology in use, down to company locations.