What is Intent Data and How Can it Fuel Your Content Process?

Definition of Intent Data

Intent data (sometimes referred to as buyer intent data or buying intent data) is essentially a business’ insight into the online behavior of potential customers. 

When prospects enter the interest stage of the sales funnel, they begin to engage in market research. Their behavior can include reading guides, watching webinars, and looking at case studies as they try to decide which product or service is the best fit for their needs. 

This online activity leaves behind a trail of evidence – this is what intent data is. By identifying potential prospects’ web content consumption and digital interactions, you can piece together what your prospects are thinking about and how close they are to their buying decision.

From the buying signals gathered, you can understand which prospects have the highest chance of converting. You can then target these prospects with personalized content strategies to help drive sales or, if they’re already close to purchasing, use intent data to identify sales-qualified leads (SQLs). 

Importance of Intent Data

Intent data is critical for modern B2B marketing strategies because of its customer-centric nature and broad scope of use. B2B buyer intent data can be used to personalize outreach, improve lead scoring, optimize account-based marketing (ABM), and help shorten the overall sales cycle.

With this form of data-driven marketing, you can get ahead of your competitors by providing prospects with the information they need, when they need it, instead of waiting for them to come to you. 

You’ll also be able to tailor your approach to different audience segments, helping your messages to resonate and avoid losing your audience’s interest.

First-party intent data comes directly from your own digital properties. It might include interactions that prospects have with your website, emails, webinars, and social media. 

This type of intent data is often considered the most valuable because it tells you how prospects are interacting with your business specifically, not just the wider market. This makes it more useful for understanding how interested these prospects are in becoming your customers.

First-party intent data is usually more granular than other types of intent data, which makes it ideal for creating high-quality personalized experiences. 

Here are some examples of first-party intent data and how you can use them to identify important information about prospect intent:

• • Topics engaged with – by analyzing the topics that prospects are engaging with, you can get an idea of how close they are to buying. For example, blog content focused around ‘What is…?’ terms indicate that a prospect is in the early stages of topic research, while ‘How to…?’ terms imply the prospect is further into their buying journey. 
  • Type of content viewed – the type of content that prospects view can also indicate their level of interest in your offering. For example, a prospect who invests half an hour of their time in watching your webinar is likely more interested in your business than a prospect who reads a two-minute-long blog post.
  • Form submissions – prospects who voluntarily give you their contact information through webinar signups, contact pages, and gated content downloads are giving you heavy signals that they’re interested in your business offering. 
  • Engagement frequency – the frequency with which prospects engage with your business is a strong indicator of their intent to become a customer. As a prospect starts interacting more with your social media channels, emails, or website, it’s likely that they’re edging closer to their buying decision.

First-party intent data can be used to enhance various aspects of your marketing strategy. From administering ad retargeting and triggered email campaigns, to identifying audience segments and creating personalized content experiences, it allows you to recognize what potential customers are looking for and to proactively offer them a solution.

Second-Party Intent Data

Second-party intent data is data that comes from another organization. It’s often the organization’s own first-party intent data, but can also be intent data about your business that has been gathered by the organization – for example, from a second-party survey.

Second-party intent data is usually acquired through a trusted partnership or data-sharing agreement. For example, a B2B software company might partner with a review website to gain insights into customer feedback on similar products. Doing so helps them understand common customer pain points and purchasing hurdles, so that they can refine their own buying journey.

While second-party intent data isn’t as common as first-party or third-party (we’ll get to that in a minute), it can still be a highly valuable source of information. It provides a broader understanding of customer behavior across the market and can help you identify gaps in your own strategy. 

The data that you gain access to will depend on the details of your data-sharing agreement, but might include the following:

• • Topics of interest – audiences interacting with content that’s closely related to your products or services can indicate potential interest 
  • Behavioral patterns – second-party audience behavioral patterns can offer a fresh perspective on your own audience’s buying behavior
  • Event engagement – attendance and participation data from events relevant to your offering can highlight prospects’ level of interest

Second-party intent data can help you expand your reach to potential customers who are interested in similar services but not yet interacting with your business. It can also be used in your wider marketing strategy to enhance customer profiles and identify opportunities for cross-sell.

Third-Party Intent Data

Third-party intent data is gathered from multiple external sources across the web. It’s normally aggregated and shared by specialist intent data providers and offers a fuller picture of buyer intent.

While this type of intent data provides the most complete overview of buying intent across your industry, it can also be less reliable than first or second-party intent data due to the nature of it passing hands multiple times. It’s also common for third-party intent data to contain information that’s less relevant to your offering, so can require some careful analysis to extract useful insights. 

Because of these reasons, third-party intent data is generally most helpful when it’s used as a complement to first-party data. It can give you a better idea of wider market trends, which you can use to give context to your own prospects’ behaviors.

Here are some examples of third-party intent data:

• • Search data – search query data provides valuable insights into what potential buyers are actively researching, including specific pain points and emerging trends
  • Community engagement – community discussions and interactions on social media and online forums can reveal important information about buyer intent  
  • Website visits – another strong signal of buying intent is if a company is frequently visiting competitor websites and industry publications 

Third-party intent data helps strengthen your marketing strategy in multiple ways. You can discover new market segments, identify content opportunities, and use the insights found to improve lead scoring and enhance ABM strategies.

Content personalization is one of the most impactful ways to improve the buying journey and maximize sales. Intent data allows you to create hyper-personalized content that serves the needs and interests of specific audience segments, leading to higher engagement and more successful content marketing campaigns.

The reason why intent data is so effective for content personalization is because it naturally aligns with the buyer’s journey. It can tell you not only what products or services your prospects are interested in but also what stage they’re at. 

For example, prospects who are currently researching educational content are likely early in the buying journey. Those looking at the pricing structure page on your website, on the other hand, indicate a much higher readiness to purchase.

Using intent signals, you can identify which content topics and formats are most relevant to your prospects so that you can nurture them with personalized content hubs and other strategies. Combining firmographic data like company size with intent signals helps further tailor content for greater engagement. 

Optimizing Content Distribution

Intent data can also tell you when your prospects are most open to engaging with content and which channels they prefer to interact with. You can then optimize content distribution around these preferences to ensure it reaches the right audience at the right time.  

The timing of your content distribution can be calculated using multiple factors, including the time of day, day of the week, and buying journey stage. The aim is to look for patterns in behavior and design schedules that align with these existing patterns.

Another strategy for effectively integrating intent data into content distribution is to set up buying signal triggers. For example, when a prospect visits your pricing page but doesn’t complete the inquiry form, you can automatically trigger the distribution of case studies of businesses that have found success through implementing your solution.

Measuring Content Effectiveness

Intent data can be used to track and measure the effectiveness of content, adding depth to your understanding of what works and why. It can highlight which channels, topics, and individual pieces of content are driving prospects further into the buying journey, and which ones are adding limited value to your content strategy.

Intent can be derived from engagement metrics like click-through rates and time spent on page. If audiences aren’t clicking on CTAs in your content or spending very long reading it, this can indicate problems with the content’s effectiveness. 

Tracking changes in traffic from commercial and informational keywords provides insights into whether your content strategy is achieving its goal. For example, if your aim is to increase top-of-the-funnel acquisition but most of your traffic is coming from keywords with commercial intent, you might need to expand your informational keyword coverage.

Enhancing Lead Scoring and Qualification

Integrating intent data into lead scoring models can enhance the accuracy of identifying high-potential leads. Instead of qualifying leads based solely on how well they fit into predetermined criteria, it allows you to create more advanced lead scoring models that factor in unique behavior. 

Optum, a leading health services company, strengthened its lead scoring by integrating webinar intent data with its existing model. Data including in-webinar engagement levels, poll responses, and attendance levels helped refine lead scoring accuracy, contributing to a 300% lift in marketing-qualified leads (MQLs).

Improving Account-Based Marketing (ABM)

Another practical application of intent data is in account-based marketing (ABM), where it can be used to identify and engage with key accounts that are showing buying signals. By revealing specific interests, pain points, and engagement patterns, intent data facilitates timely and relevant outreach that maximizes campaign impact.

ABM technology leader Demandbase successfully used intent data to improve its account targeting. Insights from webinar audience engagement data were integrated with the business’s CRM system to help sales teams prioritize leads and reach pipeline generation goals.