A Practitioner’s Brief on Intent Data

Whether you’ve already jumped in or haven’t yet started with intent data, 2022 is going to be a big year. To help you sort through the details, BrightTALK is hosting a virtual summit: Leveraging Intent 2022: Discover, Personalize, Scale. On March 30, industry thought leaders (including a few TechTarget colleagues) will explore the many ways intent data can support your go-to-market (GTM) efforts, including how to identify more in-market buyers, personalize campaigns for engagement success and accelerate sales opportunities.

And yet before exploring the many possible use cases for this relatively new category, it’s important going in to have a clear understanding of what real intent data is (and the critical nuances between types), so that you can get the most out of your intent data-based initiatives in your business. Below, we review a few of the foundational elements of the intent data category we feel are essential to effectively incorporating intent into any organization’s plans.

What is purchase intent data exactly?

As originally coined, “purchase intent data” was a category of behavioral data (data created by the behaviors of people) that provided a strong indication of an impending product or service purchase. Recently however, not only has the term been abbreviated to simply “intent,” but some players have broadened the idea to include any behavior, regardless of whether it can be reasonably associated to an impending purchase. For example, personnel changes happen all the time. And while a new leader might drive new purchases eventually, there’s going to be a significant time period before they get their feet on the ground, plan, budget and take new actions. The connection of the change to a new buyer’s journey is very distant, and so, while they are useful to Sales and Marketing, personnel changes aren’t really a form of purchase intent data.

Generally speaking, purchase intent data is most frequently used by marketing and sales teams to prioritize account focus and within accounts to guide interactions with specific customers and prospects – the real people who have signaled an interest in buying in a particular solution category. In a nutshell, it’s about maximizing visibility into market demand and optimizing the focus and precision of your actions. Currently, there are many different types of data labeled “intent” that have very different characteristics, and therefore, very different utility across your go-to-market teams. To keep them straight, we use five basic criteria to help bucket the types of intent data by their different attributes and potential uses.

1. Are the behaviors observable? When considering any new source of data, in order to confidently assess near-term value, we believe that data buyers should understand what has really gone into it. One example would be to compare an analytical product output built from invisible sources to a simpler data set comprising of direct observation of visible behaviors. In the former, no direct purchase behavior may have been observed at all. To take action quickly, and to build the confidence of the users you serve, a simple, easy-to-understand data set can go a long way to building initial acceptance and self-sustaining program momentum.
2. Is the source known, understood and trusted? Outside of your company, data can basically be sourced via two supplier models. Most outside-sourced data is only assembled by the company that sells it to you. While they make the outputs you buy, they don’t make the data itself. Instead, they source it from a variety of other suppliers. That’s why it’s called third-party data – because you get it from one company who has gotten it from at least one other (and usually many more). This creates two distinct challenges to be aware of. First is that you may not be able to understand and evaluate the actual source of the data. Second is that as privacy rules become more complex, complex sourcing makes compliance more difficult.Within the B2B intent data space, there are also a number of second-party intent data suppliers. These companies make their own data from observed behavior that is recorded in a direct manner within their own systems. Of course, you also do this! From suppliers like this, you can easily understand exactly what the behavior is, how it was produced and what is being done to meet the relevant privacy and compliance requirements.
3. Is the content (that created the behavior) known and understood? Since third-party data suppliers don’t create the data they sell to you, they usually don’t have easy access to the content which drove the behavior in the first place. So, while they can tell you what search term may have been involved, they can’t tell you anything about what content was “returned” by Google. Nor can they tell you who was searching. It’s an issue of precision. When you don’t know exactly what someone wanted to read, you think that it might be relevant to your products, but it could just as easily be about something completely irrelevant. For example, take home security vs. network security, or data backup for a PC vs. a network. This inaccuracy can be a big problem if you expect to use it to guide sales. The last thing a marketer wants in their intent data initiative is to lose Sales’ confidence in the data being supplied to them.From second-party suppliers, you can often know exactly what content has been consumed and even the person consuming it. What’s more, you can know if other people at the same account in related departments or functions are also consuming that content or similar material. In this way, you can start to see buyers’ journeys taking shape because you can see the buying group in action. This is valuable both for Marketing and Sales in two ways: One, when you can see a buying group becoming active around a topic, you can be confident there’s a buyer’s journey in progress. And two, when you know the content being consumed, you can shape your marketing messaging and personalized sales outreach in ways that will maximize deeper engagement.
4. Is the behavior truly indicative of purchase intentions? As practitioners and continuous learners, all of us consume tons of content relative to our market category and professional function on a daily basis. And as news pops up in our field, our search behavior may surge. While none of this really indicates an impending purchase, many intent data providers will pick this up but aren’t able to distinguish it from real purchase intent. Similarly, while leads are a behavioral signal, they tell you only about a single individual’s interest in a single asset at a single point in time. To be confident in what actions the data tells you to pursue, you’ll want to see evidence that there are patterns forming that clearly suggest an active buyer’s journey.It starts with seeing patterns of purchase-relevant content consumption over time. And it must include more than one other functionally relevant person consuming similar material at the same time. Since in B2B, we know that many buying groups will at least include technical specialists, businesspeople and finance, clarity around that is extremely valuable as well. We use all of this and more to make our decisions about where to guide our teams to act each week.
5. Exactly who are the individuals exhibiting these behaviors? If you don’t know exactly who is exhibiting a behavior, you can’t know if it’s relevant to your business. Furthermore, these days, even if you know who the person is, you may have no justifiable business reason – in GDPR terms, “legitimate interest” – for reaching out to them. Unlike third-party intent data suppliers, second-party sources may utilize explicit opt-ins or log-in credentials to identify the individual (their role, function, etc.), exactly as you do in your own lead gen. Some of them also take an important step further and include explicit clarity around sharing their data directly with you. When you know who the people are and what they’re consuming, you have what you need for a truly personalized interaction. You can share this as a “snapshot” with your sales team to inspire them to take the right actions with the right tonality. When you deploy an intent data resource like this end-to-end across the teams in your go-to-market, you will see improvement, from strategy, through campaigns, to pipeline health, conversion rates, sales productivity and closed-won revenue.

Purchase intent data categories, summarized

As mentioned, there are three common sources of behavioral data commonly used to support marketing and sales activity:

1. First-party intent data refers to data that is based on observed behaviors in your company’s systems. For example, this includes when a prospect visits your company website and downloads a white paper. The observed action is recorded in your company’s system and the content that spurred the action is known and understood by you. First-party intent data from website behavior can be anonymous as well – you may be able to see the account but not the people (or their role or function) taking specific actions. In cases like this, you have an intention of some kind, but it’s often not actual purchase intent.
2. Second-party intent data refers to data usually from observable behaviors that are captured in a second company’s system. The data is collected by the second-party organization and shared with users, usually for a fee.
3. Third-party intent data is supplied by providers who obtain the data they sell from other, un-owned or controlled sources. In many cases, the third-party data provider pays publishers (second-party providers to them) for a data feed including only aggregate, anonymous, high-level information about visitor account content consumption. Alternatively, third-party data providers may “scrape” publicly available data from open websites or through manipulations of the Google advertising bidstream without explicit permission from the website operator or the end users exhibiting the behavior and with no real visibility into the content being exchanged.

Differences in the “strength” or “precision” of various purchase intent data signals

The strength and therefore reliability of an intent data signal depends a great deal on a combination of factors. First is your ability to identify which account and individuals the behaviors are coming from. This is the overwhelming determinant of how much immediate and strategic value over time the source can promise. Second is how the data is obtained, or more specifically, whether or not you can understand the specifics of the content consumed well enough to determine its relevance to purchase intent and your offerings. Across the five purchase intent data elements we’ve discussed, the more of the criteria that are met, the more precision is available to you for the various use cases you want to deploy. Conversely, the fewer criteria that are met, the less precision there is available, and therefore the use cases for you to extract value from can become much reduced. Some sources of behavioral data marketing themselves as B2B “intent” may not have any strong signals of impending purchase at all. Right now, unfortunately, it’s very much a buyer beware situation out there.

Strong-signal purchase intent data will include good coverage of all five elements outlined above. When all of these attributes are available and covered well, you’ll find the data easy to understand and explain to others. Your users and support colleagues alike will believe in the data and trust that they can use it to their advantage.

Today, thousands of B2B companies are experimenting with intent data in many forms and for many use cases. Those who have made well-informed choices about their sources are beginning to move ahead of their competitors because they’re using stronger signals to take more concerted and higher quality actions, wasting less resources on unproductive activity, and are enabling more parts of their GTM with this valuable resource. To learn more about how intent data can improve performance across your GTM, don’t miss Leveraging Intent 2022: Discover, Personalize, Scale. Register here today.