A recent article by Ken Gaebler introduced readers to "intent data" as a concept and explained how to go about purchasing it from third-party providers. In a word, intent data is an actionable dataset for B2B marketers that enables them both to understand what new leads and current prospects want and to serve the most optimal content, message, or product across owned Web and email channels.
The thrust of Gaebler's article is that marketers can procure intent data through a variety of third-party providers, such as Bombora, TechTarget, and Madison Logic. Those vendors amass intent data from a variety of sources. The most common source is partner networks of publisher sites—content-rich hubs of activity in which your current customers and future buyers are regularly consuming business content.
The content that is consumed on those sites is used as proxy for intent. In its simplest form, it works like this: If a person is reading a series of articles across Forbes, CIO Insight, and Aberdeen Group about the topics "Web virtualization" and "pure storage," it's reasonable to assume that person's intent is to learn more about those topics, with the ultimate intention to buy a Web virtualization product from Pure Storage.
Third-Party Upsides and Downsides
It's easy to see why getting intent data from third-party vendors is so attractive to B2B organizations. To generate first-party intent data requires an organization to have a large corpus of business content that covers a breadth of topics, as well as a high amount of buyer interactions with that content from which the organization can determine intent.
Third-party intent data providers bypass those requirements and thus dramatically reduce both the operational and the institutional changes required from some B2B organizations to know what their buyers want and need.
That said, using intent data from third-party providers has downsides. Fundamentally, third-party intent data is never as accurate as first-party intent data. First-party data comes directly from your visitors and tells you exactly how they interact with your content and products, not someone else's content and products.
By contrast, you have to trust that the third-party intent data provided by vendors is accurate in identifying individuals (i.e., this is the correct person/account), and that the topics collected are accurate (i.e., these truly are their interests). That alone should throw up a red flag for B2B organizations that are looking to act on third-party intent data—either through marketing automation (e.g., content personalization) or human interactions (e.g., a sales call).
Accordingly, it is important to note that B2B marketers can generate their own first-party buyer intent data if they have both the content and the content interactions to do so.
How to Generate First-Party Intent Data
First, B2B marketers have to understand something that third-party intent data providers have themselves understood for some time: Content is not merely a vehicle to engage, convert, and retain an audience—it is also a means, as explained above, through which you can understand your buyers and predict their intent.
When buyers interact with your content, it is often because they are researching a problem or solution that can be resolved by your product offering. By tracking those content interactions, you can build a more complete picture of their intent and motivations and, in turn, ways you can best meet their informational needs.
Most modern marketing automation and CRM tools display the clickstream (series of URLs) an individual contact has visited on your site. You can see this each time you open Salesforce or Pardot (for example). However, a URL alone won't give you context about what a particular page is about. To capture that insight requires your content to be tagged with metadata that describes the meaning of each piece of content.
Topics can be people, product, places, organizations, and so on. For example, this article could be tagged with the metadata "Andrew Davies" (person), "web virtualization" (concept), "MarketingProfs" (product) and "Pure Storage" (organization).
Of course, one article alone isn't enough to build an accurate picture of you, the reader, but if we were to track your reading arc around MarketingProfs, very soon we could build up an increasingly accurate picture of which topics are interesting to you and use that to identify your informational needs or purchase intent.
Adding tags is an arduous task, even more so when dealing with thousands of content items sitting across multiple CMS systems, which is a common scenario for large B2B enterprises. However, as I wrote previously, machine-learning technology, such as content intelligence, automatically adds descriptive metadata to content and uses that to capture the interests of buyers as they consume content on your site, thus eliminating the manual effort associated with the task.
Whether automating the process or doing it manually, tracking the content topics of interest for both anonymous Web visitors or an identifiable buyer is enough for B2B marketers to start understanding intent. Doing that yields first-party data that is yours and is accurate (not based on extrapolated, external datasets).
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Third-party intent data can certainly be effective for B2B organizations that have few content items or buyer interactions. However for large enterprises with myriad product offerings and content topics and lots of onsite traffic, first-party intent data is invaluable.
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