In the latest episode of our podcast, learn about the future of technology intelligence and how it is evolving to help companies spot trends earlier, make more accurate predictions, and uncover hidden opportunities.

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Interview Transcript

Benjamin S: Welcome to the last episode of technology intelligence week on the MarTech Podcast. This week, we’ve been doing a technical deep dive into one of the most powerful and underutilized data sources for B2B marketers, technology intelligence. Each day this week, we’ve published an episode that discusses how you can understand, identify, and reach your customer base based on what software, services and hardware they use to run their business.

Joining us again today is Elizabeth Cholawsky, who is the CEO at HG Insights, which is a sponsor of the MarTech Podcast, and a platform that uses advanced data science methodologies to process billions of unstructured digital documents to produce the world’s best technology installation information, IT spend, and contract intelligence to accelerate their customers’ sales, marketing and strategy efforts.

Okay. Here’s the last installment of technology intelligence week, where
Elizabeth and I discuss the future of technology intelligence. Elizabeth,
welcome to the last episode of technology intelligence week on the MarTech Podcast.

Elizabeth C: Thank you, Ben.

Benjamin S: We’re coming to the end of the road here. We’ve covered a ton of ground. I appreciate you sticking with me for the entire week. We talked a little bit about what technology intelligence is, the ability to understand what services, software, and hardware a company is using, how it can be useful, figuring out your total addressable market, figuring out how to segment your customers, figuring out where they are in their buying cycle, and what are some of the other supplemental technology products they’re using.

We also talked a little about the overlap of sales and marketing, and how
technology intelligence can support that, and the different ways that people
can access technology intelligence data to make it actionable. Technology intelligence is something that is not new, but using the data processing and machine learning processes that HG Insights has built is a newer technology, and being able to operationalize it into things like your ABM campaigns is new. Where do you think we are in terms of the life cycle of technology intelligence? Have we hit maturity? Are we at the beginning of the road? Talk to me about the future of tech intelligence.

Elizabeth C: This is an exciting topic for me, because I think we’re just scratching the surface with what we can do with technology intelligence. If we look at some of the discussions we’re having with some of our customers about what they’d like to see next, it really centers around deeper understanding of markets, so not just products but technology topics maybe, as well as trends and predictions. But with some sophisticated modeling around the longitudinal information we have, we can start to tap into those kind of accurate predictive models for next technologies to buy and the right times to do so. We’re working a lot on that.

Benjamin S: I’m also the host of an SEO podcast called the Voices Of Search Podcast. It’s with a company called Searchmetrics. One of the things that I think is interesting about what Searchmetrics does is there are financial analysts that are trying to understand a business’s performance based on their online visibility, based on their SEO performance. It seems like there’s a big opportunity here outside of sales and marketing, but for people to evaluate and understand how B2B SaaS businesses are actually performing, and what’s happening under the hood with this type of intelligence. Do you see technology intelligence being used as a prognosticator for business performance, and is this something that companies can use to understand whether they’re heading in the right direction from a strategic
planning perspective?

Elizabeth C: Yeah, absolutely. We have some companies that we’re working with for some experimental uses of what we can do. I mentioned topics. If you think about it, you might want to know which companies are really looking at, say, self-driving cars, and starting to work in that area. You don’t know of a particular product, but you know the area that you want to understand for which companies are interested in that. Or maybe just AI research. You just want to know what companies are really starting to look into that area. Well, given that we’ve got so many documents that we start with, there’s a lot of information in there that can tell you the conversations that are going on at various companies. We’re starting to really take a look at how much and where that kind of information can be applied. We’ve got some interesting research going on there.

Benjamin S: It seems like this gets into the Forrester and Gartner type analyst business, where their jobs are to evaluate what is happening in a given industry, and also make some predictions about which trajectory companies are on. Have you worked with the Gartners and Forresters of the world? Are you in this predictive industry analysis game, or is this just a data source that’s underutilized?

Elizabeth C: It’s very interesting, because we have worked with all the industry analysts at times, they’ve been customers of ours, but we also have complementary services to what they have. If you think, just at the basic total addressable market level, certainly the Forrester wave and the Gartner magic quadrants, people live and die by those, and pay a lot of the money for them each year. But if you think about what we do on demand, you can get a similar cut of a technology sphere. It’s based on data, not surveys and opinion, and you can get all the way down to the individual companies. So it’s very complementary to those market assessments from Gartner and Forester, but give you a totally different unique view of what’s in that magic quadrant or what’s in that wave. I think we’re going to see, and we have been seeing, much more demand from our customers to provide that supplementary market analysis, to do what the Foresters and the Gartners of the world do.

Benjamin S: It seems like, on a company level, on an industry level, technology intelligence would be useful. Then there’s also looking at a macro level. I’m thinking of the Mary Meeker yearly report, understanding the direction the Internet’s heading, what are the biggest trends. How do you figure out what’s happening at a macro level using technology intelligence? Are there any interesting data points that you know of that tell us which direction we’re heading from a technology perspective?

Elizabeth C: If I had that, I’d probably be keeping it to myself.

Benjamin S: Well, you just say it and we’ll just keep it between the two of us. I won’t tell anybody else.

Elizabeth C: This gets into some of the research that we’re doing with the corpus of documents, and really determining whether we can pinpoint new topics that are being talked about and then trend them over time. Here’s an interesting one. We can actually show you, over time, the three cloud providers, AWS and Azure and Google Cloud, and show you the different kinds of trends, at a regional level, for each of those three products, and who’s winning and who’s losing, and who’s dropping off, and also the adoption of cloud over time. That’s a really critical piece of information for a lot of different companies, but it’s also a critical piece of information in terms of predicting how quickly in general it’s going to go away. It’s information about markets. It’s not necessarily down to the company level. It gives a much broader perspective from the same sort of information that we’ve got at a company level.

Benjamin S: Give me a view into the future for HG Insights specifically. You have the ability to tell your customers what the technology products that have been adopted, what the contracts look like, what some of the spend is. Are there other data signals that you’re developing, other products that are coming down the road that we can look forward to?

Elizabeth C: Yeah, I’ll give you a sneak peek of one that we’re working on and I’m excited about. From the information that we’ve gotten raw level, we can actually assess movements of different types of positions from company to company, or the growth of a certain position at a company, or a certain type of skill set. I really believe that we can pull out personas, and help companies better target exact personas that match up to their technologies at different companies. The reasons that’s an exciting area is, I think, over time, that’s going to replace the need to go down to the contact level. We really know how difficult it is getting to be, because privacy laws, to go the contact level. So I think over the next few quarters, you’ll see us doing more in that area around personas.

Benjamin S: I think that’s really smart, and really interesting that understanding what technology people have already adopted gives you a sense of what they are interested in, and who might be your customer. But when somebody starts to hire out a team, a new product line, they’re going to need new services, right? Hey, Apple is hiring 50 new machine learning experts. All right, well the machine learning software is something that should be sold into that platform, that company.

Elizabeth, I think technology intelligence is fascinating. I think that there’s a couple of data sources that I’ve learned about through hosting this podcast. Understanding search intent is one that’s really interesting. Location data, understanding what events and locations people have gone are at. Also understanding the technology that people have adopted enables marketers to be smarter and more sophisticated. At the end of the day, all of these data sources that enable you to understand more of your potential consumer behaviors help you spend less, understand your target market, and be more efficient with your marketing. I really appreciate you coming on the show and telling us all about technology intelligence. Thanks for being our guest.

Elizabeth C: Thank you very much, Ben. It was fun.

Benjamin S: Okay. That wraps up technology intelligence week on the MarTech Podcast. Thanks to Elizabeth Cholawsky for joining us. If you’d like to get in touch with Elizabeth, you can find a link to her LinkedIn profile in our show notes. You can contact her on Twitter, where her handle is ECholawsky, E-C-H-O-L-A-W-S-K-Y. Or you can visit her company’s website, which is