How to Leverage Intent Data to Drive More Revenue

Targeting and Personalization


As key drivers of the revenue team, marketing and sales are constantly looking for the next innovative method to get a competitive edge—particularly in generating revenue for the business.

One method that continues to pique interest is intent data.

Having created numerous products that leverage massive volumes of data in the marketing and sales space, we get asked many questions about how to best leverage intent data. In this blog, I’ll walk you through what intent data is, how to use it to drive revenue, and how to evaluate a vendor:

What is Intent Data?

Intent data is behavioral information collected about an individual’s online activities, combining both topic and context data, which I’ll explain in more detail below.

Topic Data: When you search for something or visit a website, you are expressing an interest in that topic. For example, people who read this article are expressing some level of interest in “intent data.”

There are several different categories of topic data:

  • Anonymous 1st Party Behavioral: People visiting your website who are identified by their IP address, which is then mapped to their company’s name. You can use solutions like Demandbase and Marketo Web Personalization to leverage this information to personalize the content displayed.
  • Known 1st Party Behavioral: People visiting your website who have also filled out a form online. Because they provided their contact information, they are considered “known.” Using a marketing automation platform, you can then track their page views.
  • Anonymous 3rd Party Behavioral: People visiting other websites that you don’t own, but indicate some relevance (e.g. for business professionals). Their IP addresses are collected by vendors like Bombora and Big Willow.
  • Known 3rd Party Behavioral: People visiting other websites who have also filled out a form on that site providing their contact information. In this context, they become known to the website owner, and vendors like TechTarget make that information available to marketers.

However, topic interest alone is not all that actionable without knowing the context of the individual.

Context Data: Context is all about gaining insight into who the person is that’s taking the action in question. For example, if the person reading this blog is a marketing professional, it’s possible they are in the process of evaluating a product that leverages intent data. But if the person is an industry analyst, it may be more likely they are writing a report and looking for more information on the subject.

Levels of context range from higher-level, more general information (e.g. Which company does this person work for? What is their official role within the organization?) to really granular, personal insights (e.g. Does this person have expertise in using technologies or best practices associated with my product? Does this lead and company match with my ideal buyer or could they be an influencer?)

Without this context, you’ll be wasting your time and budget engaging with prospects who may be making all the right behavioral signals but will never become customers (e.g. trying to sell your product to the industry analyst).

How to Use Intent Data

Now that we’re clear on what intent data is, let’s go over some specific scenarios in which you can use it to drive revenue.

1. Personalize your website experience for anonymous visitors

When people visit your website before they fill out a form, their activities are considered to be “anonymous.” This term is a bit misleading because the visitor is not, of course, completely anonymous. With the right technology, you can identify the company and/or industry a visitor represents based on IP address alone. However, that visitor is still considered “anonymous” on a personal level. You don’t know who they are or where they fit within their given company or industry. They could be the CEO or CMO—but they could just as easily be an intern or a student.

After you identify visitors “anonymously” on your website and track the pages they view, you can use web personalization to serve customized content to incentivize them to take a specific action. In most scenarios, anonymous personalization is a means to encourage visitors to identify themselves via a form fill so marketing and sales can engage with them (or not).

2. Prioritize inbound leads based on engagement

With the wide adoption of marketing automation, many companies are already using 1st party behavioral data (i.e. context of the individual) to optimize their lead scoring model. This scoring model attempts to quantify the intent of the visitor based on a culmination of activities. For example, when leads visit your product overview page, their lead score will increase by 5. If they visit your pricing page, indicating an even greater interest in buying, it will increase by 10, and so on. Then, when a lead’s score reaches a threshold agreed upon by marketing and sales, an alert is sent to sales to reach out to that prospect.

3rd party intent data can be incorporated into your existing lead scoring model as well. Consider the scenario where a lead has researched topics related to your product on other websites, but has not yet hit the 1st party behavioral scoring thresholds set. You shouldn’t wait for them to then hit the behavioral thresholds (e.g. downloading your whitepaper) before engaging with them. If they’re clearly interested, you want to strike while the iron is hot.

3. Nurture known leads with personalized emails

Nascent personalization and lead nurturing leverage job titles to segment inbound leads. The problem? Job titles in the B2B space are not standardized, change frequently, and often give no real insight into the seniority, buying power, or even specific functions the lead serves within their company. This often results in improper categorization, sending unqualified leads to sales, and delivering “personalized”, but irrelevant content to leads.

To most accurately categorize leads and place them in the right nurture campaigns, you must combine their known 1st and 3rd party behavioral data to identify not only the context of who they are and their role within the organization but also the topics they are interested in.

4. Identify potential customers who haven’t yet engaged with you yet

Your prospects’ purchasing decisions are strongly influenced before they even reach out to you or visit your website. For example, people consume content within their social media feeds and read reviews on G2Crowd, which shape their opinions and push them in one direction or another. These activities are considered 3rd party behavioral data.

3rd party behavioral data is highly unstructured and the volume is massive. As a result, very few companies possess the budget or expertise to integrate such data into their existing marketing and sales processes. In turn, marketers have increasingly turned to predictive analytics platforms that integrate with marketing automation and CRM platforms to help them sift through the noise to determine which 3rd party topics are actually relevant.

Anonymous 3rd party topic data can be incorporated into predictive account scoring models to determine prospective accounts’ likelihood to buy. This information is used to identify target accounts for outbound initiatives as well as prioritize new inbound inquiries from leads within high scoring accounts.

Questions to Ask an Intent Data Vendor

It’s all too common that people will buy in on the conceptual value of intent data only to be disappointed that the solution they bought cannot be applied to all of their desired use cases.

To ensure your vendor can support your objectives, make sure they can properly tie topic data to buyer context (i.e. intent) by asking the following questions:

  1. What level of context can you provide me about the buyer? Company only? Lead only? Ideally, you want both.
  2. Can you deliver the context (i.e. company, person, and topic attributes) used in your modeling process so I can use the information in my existing lead and account scoring workflows? Steer clear of “black boxes,” predictive models which don’t let you look “under the hood” and view the data that informed the model.
  3. Can I get set up with a quick win and then grow with your offering into more sophisticated uses of intent data?

If your vendor cannot deliver on the above, it will be difficult for you to leverage intent data to its fullest potential. Instead, you’ll risk putting yourself and your organization at risk of buying a solution that doesn’t help you achieve your business objectives.

Are you leveraging intent data today? If so, I’d love to hear how you’re using it and what you think in the comments section below.