The Holy Grail of Data for B2B Technology Companies
An Interview with HG Data Founder and R&D Leader, Craig Harris
In our company video, you mention that HG stands for the Holy Grail of Data and that the mission of the company is to live up to its name. Can you elaborate a little on that?
When we first started HG Data we had a general sense of the type of data products that we wanted to bring to the market. To validate our assumptions, we spent a lot of time talking to marketing and sales individuals in different roles, including managers, directors, VPs, and CMOs. During that market validation process, we would preface our interviews by asking folks to describe to us what their Holy Grail of prospect information was. The way we would ask the question is:
“Describe for us the data sets or profile of a prospect that you dream of…what you wish you could buy if it existed? Really, we want to understand the essence of what your Holy Grail of marketing and campaign data is?”
We were so inspired by what we heard in those interviews that when it came time to name the company we decided on HG Data — not because it rolls off the tongue or is exceptionally memorable, but because it reminded us of our mission, which is to build the Holy Grail of data for B2B marketing teams.
Can you describe some of the things you learned in your market validation assessments?
We met with hundreds of marketing and sales executives and asked them all to describe the Holy Grail of data from their lens. A recurring theme that kept coming up amongst different individuals was a strong desire to know which companies were using their competitor’s hardware and software technology.
The other thing we heard when we talked with software and IT firms was a great interest in understanding the overall software and computing environment for their prospects, not just for competitive purposes, but for complementary purposes. For example, companies that sold robustly through the Salesforce Ecosystem or the AppExchange, wanted to know which companies were running Salesforce so they could target campaigns to them directly.
We refer to this data as technographics because it focuses on the hardware and software technologies companies use to run their business. This is what our market validation interviews revealed marketing and sales teams desired time and time again.
Were there any surprising discoveries you made in your interviews?
Most companies in the B2B space were familiar with using third-party firmographics to segment their prospective customers. As such, they frequently used criteria like company location, size, number of employees, annual income, and SIC code to develop their marketing segments. What surprised us was the huge discrepancy between what companies said they wanted and what they used in practice. In other words, when we asked companies what their Holy Grail of data was, not a single organization described company location, size, revenue SIC code, etc. as their Holy Grail. Not one.
How do you get access to this type of information?
We’re able to provide deep technographic profiles by using advanced data science to dig deep into the billions of offline and online documents we process each day. Our approach involves a combination of automated processes, as well as human involvement, such as the continuous refinements our data scientists make to our data processing algorithms, and the validation and testing our quality team performs on the data output to ensure we extract the technographics or other similar insights our customers need to achieve better results in their outreach.
You mentioned it’s not easy to get this type of information. What are some of the challenges?
The main challenge is getting quality data at scale. It’s not just a challenge for us, but for many of the companies who provide data to the MarTech ecosystem. Everyone has a different way in which they gather their data. Some companies don’t use any form of artificial intelligence or machine learning at all. Instead, they use large teams of analysts who pick up the phone and call companies to figure out what they’re doing, what they’re planning, and what their budgets are. Those are some very useful products out there in the marketplace, but in most cases they’re not very scalable. For example, you might find a vendor chooses a very particular niche, and maybe they’ll track 5,000 companies in a particular category.
We were after both quality and scale. The extent to which we use data science, machine learning, artificial intelligence, just name your buzzword, is about answering two questions:
“How do we build the most accurate data set available?
How do we do this at scale worldwide?”
In order to achieve what we were after, we needed a solution capable of not just processing, clean, pre-parsed data sets, but also extracting facts from messy, unstructured documents that come in a wide range of formats. This was a problem that had never been fully solved at the scale in which we operate.
In our case, we felt it was essential to use advanced machine learning and natural language processing (NLP) techniques. This means we’ve got a team of really smart engineers and data scientists that are building intelligent algorithms and training sets that auto-generate rules, so that every time we learn something new, whether we get something wrong and want to correct it, or we get something right and want to repeat it, we have a very sophisticated environment that allows us to do that. This is how we can really achieve our pursuit, which is both accuracy and scale.
How is your offering unique in the marketplace
We’ve created a proprietary collection of company-related documents that number in the billions. Using data science, we have managed to extract and verify data on millions of companies. For us, each one of these documents is a piece of a puzzle, it’s a vignette, it’s a story. And because we’re doing this at such a large scale, we often have hundreds, thousands or millions of documents that are related to a particular company.
The science that we’ve created is really the ability to go and query those documents and look for signals and look for facts, and to aggregate facts at scale. It’s one thing to hear a fact one time from a company on a specific point in time, but it’s quite another thing to hear that fact hundreds or thousands of times over an expansive or compressed period of time. When you amass and are able to parse through that much data a clear story begins to emerge about what technologies companies are using, the rate of technology adoption, and other important trends our customers find very useful.
How do you differ from your competitors?
There’s a handful of companies that also track installed technologies. One of the simple ways you can do this is by digitally scraping the code from a website. For example, if a company is using Google Analytics, Omniture, Marketo or something where the code is readily available on the website, there are companies who can provide you with this digital signature information. However, what we’re doing at HG goes much deeper than this. Because we’ve amassed such a large quantity of offline and online resources, we’re able to provide our customers with deeper insights on the technologies companies are using in their business, including hardware and software that does not leave a digital footprint. And we provide this type of information on millions of companies.
There are other companies in the marketplace who build their data sets using models. For example, some third-party data providers will identify a very small number of companies that use a certain type of CRM or marketing automation platform and then proceed to build a model to extrapolate other companies who may be using the same technology. We’ve spent a lot of time talking with customers that consume this type of information and some things just can’t be modeled effectively.
Where HG differs from others in the space is that we are all about empirical facts. We don’t use models to build our dataset because we know that when you start with really high-quality, factual, and empirical data you’re going to get a better result. At HG, we use our team of scientists, data analysts, and engineers to build the most accurate, most scaled and insightful fact repositories in the industry.
What does the future look like for HG Data?
For the last several years, we’ve been hyper-focused on nailing our technology and data curation process, much less so on creating experiences and integrations around that data. Consequently, we’ve been selling primarily to the Fortune 500 or Fortune 1000 technology companies. A lot of our customers have sizeable analytics and data teams that are able to work with large and complicated data feeds.
Now that we’ve established our expertise in the technology and data aspects of our business, we’re entering a really fun and exciting next phase in which we’re now democratizing access to the insights our data provides. Our goal is to make sure that all companies in the B2B world, including small to midsize companies, are as successful with our data as our Fortune 500 customers, many of whom have been using our technographics for years.
One big step we’ve taken in that direction is the release of our new HG Data for Salesforce App, which allows teams to use technographics directly from within Salesforce, the most widely-used CRM. Our product team has done a wonderful job with the integration so that our customers can use our tech install information to create campaign segments, score and prioritize leads, and deploy workflows and triggers to build more intelligent business processes. This is exciting stuff and it’s what we’ll be doing more and more of in the months and years to come.
How does your new focus on product affect or change the mission of your company – are you still the Holy Grail of data?
The foundation for our company will always center around making sure we deliver the most comprehensive and accurate data in the industry. That’s not going to change. What is changing is how customers consume our data. We have a product team that is dedicated to creating marketing and sales platforms that integrate smoothly into workflows and systems companies already have in place. However, at the core of anything we do is our data. You can have the prettiest, easiest-to-use interface in the world, but if the data behind it is bad or otherwise inadequate, people are not going to find a whole lot of value in it.
So to answer your question, yes, our mission is still to provide the Holy Grail of data for our customers. It is this focus on the data and building processes centered around extracting the most relevant set of data for our customers that I believe will allow us to not only grow our existing customer base in the IT and software market but also enable us to expand into other vertical markets.