As big data increasingly becomes more accessible, marketers are looking for ways to make it more scalable and actionable in order to better target prospects in various stages of the buyer journey. Intent data is synonymous with this topic, but it understandably causes a great deal of perplexity for many marketers.
It can be difficult to sift through all the terminology: It’s variously referred to as activity, behavioral, internal intent data, or external intent data. Pairing intent data with other customer signals — like those housed within a company’s marketing automation system — provides an especially unique opportunity for businesses to understand and leverage customer insights.
Nonetheless, it’s a topic that will continue to gain steam as more companies look for new ways to identify and predict where customers are in their buying journey.
To start, it’s helpful to define common termsfor a clear understanding of the various types of intent data out there, and how they can be applied. Simply put,intent datais information collected about a person’s or company’s activity. For the most part, it falls in one of two main categories, each of which best serves a different purpose:
1. Internal intent data (also known as first-party data) is the activity a company captures on its website via its marketing automation platform or through application logs. This kind of information contains highly predictive buying signals, since the content is relevant to the purchase decision — for instance, which pages a prospect touched, links they clicked on and how long they spent on each page. Predictive-scoring vendors often build customized behavior scoring models that use a company’s first-party data to help them identify which prospects are in-market and ready to buy.
B2B external intent data is only available through third-party providers like Bombora, The Big Willow, IDG and TechTarget. These intent data providers are working to help businesses determine their “Total Interested Market.” For example, they help some of their customers achieve this by identifying which of their accounts are showing surging interest surrounding a particular keyword or topic.
Use cases for third-party intent data include targeted advertising, building target account lists from surge lists for account-based marketing (ABM) strategies, and personalizing content marketing programs.
There is also great value in knowing what people are doing before they get to your website. So let’s take a deeper look at internal and external intent data to determine whether it produces predictive signals to help surface net-new leads.
Internal intent data can help predict prospects.