Intent data was a term rarely discussed in B2B marketing circles 10 years ago, but today it’s a staple in every marketers’ toolbox.
The idea behind intent data is simple. People partake in all sorts of activities online. They visit vendor websites, fill out forms, engage with chatbots, and they type search terms into search engines.
But does any of this activity mean they’re actually ready to make a purchase, or at least have a serious discussion about your products and services? Not always.
Any of the above actions, for example, can indicate some level of intent. But the goal of intent data is to help marketers find signals that someone is actively researching a product or service. When marketers can track multiple signals, a digital footprint begins to emerge. If they’re reading the right pages and searching for the right terms, they start to differentiate themselves from other visitors.
There are, broadly speaking, three different types of intent signals.
Implicit Intent Signals
Implicit intent signals were used by many B2B marketers long before intent data became a household term. Implicit intent signals are based on a user’s behavior. They include signals like the website pages someone visits, time spent on a page, or content downloads.
Many B2B marketers construct their websites with these various intent signals in mind. They build high-intent pages, and use links to other pieces of content and web forms to guide the visitor along a journey. You can’t make someone go from low-intent pages to high-intent pages, but you need to make it easier for them to move along the funnel if they are ready.
Explicit Intent Signals
Explicit intent signals are based on a user’s declared intent. The most common example of explicit intent is filling out a form requesting to be contacted.
Explicit intent is the most solid form of intent that exists for many B2B marketers. While there are other possible explanations for the activity that’s considered implicit intent (like a competitor exploring your website, for example), explicit intent is the virtual equivalent of a visitor raising their hand. It is a declaration intent.
Inferred Intent
Inferred intent is based on data analysis and requires more complex tools and processes. Machine learning algorithms can combine multiple data streams to identify visitors who are demonstrating inferred intent.
Unlike the examples given for explicit and implicit intent, which can rely on web analytics tools and lead capture, inferred intent can include data from outside sources to paint a picture of intent signals from across the web, not only your website.
RELATED ARTICLE: How to Leverage ABM Intent Data
The 6 Most Common Intent Signals in B2B Marketing
B2B marketers will incorporate a number of intent signals into their strategy in order to paint a full picture of visitor behavior and reduce false positives. Here are the six most common intent signals analyzed by B2B marketers.
Search Queries
Analyzing search queries will help you identify potential customers who are actively searching for solutions like yours. Understand search queries and their intent is the foundation of a search engine marketing (SEM) strategy. But looking at the search terms people use to find your website also helps you create content and build high-intent pages to improve your organic search performance as well.
Website Behavior
Once a visitor arrives at your website, tracking their behavior gives you insight into why they visited and where they are in the buying journey. Your website and content strategy should identify the funnel position (top, middle, or bottom) and/or intent (high, medium, low) of your web pages. Visitors spending most of their time on high-intent or bottom-funnel content are more likely closer to making a purchase decision.
It’s also important to look at the sources of traffic coming to your website. For example, TechnologyAdvice offers its Intent Clicks program to give software vendors the opportunity to capture traffic from high-intent pages like Top Product listings and send that traffic to the vendor’s website or landing page. Visitors coming from pages where they are researching products and services are more likely to be in market for a solution.
Content Consumption
In addition to web pages, other types of content – such as whitepapers, data sheets, videos, and virtual events – can be classified as high intent or low intent. Data sheets and product comparisons, for example, will demonstrate higher intent than a thought leadership piece on strategy. Monitoring content consumption also extends to your social media presence, where prospects and customers can engage with your content.
Firmographic Data
Firmographic data includes details like an organization’s size in terms of employees or revenue. When you combine firmographic data with data sources like web analytics, a more clear picture emerges of visitors that are a strong potential fit for your brand.
Intent Data from Third-Party Providers
Third-party intent data providers sell intent data from their own websites or from networks or co-ops of sites around the web. This allows marketers to analyze a broader view of activity and identify visitors to other websites in addition to their own and gauge their intent.
How Reliable Are B2B Intent Signals?
This is a common question asked by B2B marketers and their leadership teams, especially when they’re considering investing in intent data tools and providers. In many cases, however, it’s the wrong question to ask.
Yes, if you’re going to make an investment in intent platforms, you want to be certain you’re getting accurate, relevant, up-to-date information. But instead of looking at intent data as a strategy of its own, a better approach is to view intent data as part of a larger intent strategy to help identify your target audience.
Think of your B2B marketing data as a stew. Intent data is one ingredient, but it tastes better when it’s cooked up with the other goodies. Combine your intent data with demographic and firmographic data to better understand whether the people demonstrating intent are actually good fits for your products and services.
For example, Intent signals that identify an organization that’s outside of your ideal customer profile (ICP) because it’s too small or located in a region where your business doesn’t operate aren’t very valuable. Adding firmographic and demographic data will identify that account as one you can skip.
The opposite is also true. Adding firmographic and demographic data to intent signals can identify organizations that fit your ICP, but may not be included in your target account list. This is one way to grow your list.
According to a survey by Demand Gen Report, website behavior, search keywords, and content downloads are the intent signals B2B marketers trust the most. Each was cited as most trustworthy by more than 60 percent of the marketers surveyed.
This isn’t surprising. These intent signals are the easiest for marketers to track and rely mostly on first-party data.
Like any type of data, there are a number of factors that determine the reliability of intent data. The first is the quality of the data you have available at the start. There’s an old saying about data quality: “Garbage in, garbage out.”
If you’re using visitors’ website behavior as part of your intent data, for example, then make sure your web analytics platform is set up correctly and the data is accurate.
Another important aspect of data quality is using fresh data. When it comes to intent data, understanding who was in market for your products last quarter is ineffective. Prioritize fresh data in your intent strategy. Traction Insights from TechnologyAdvice lets vendors list their products on relevant pages in the TA ecosystem and gain access to intent data. The Traction Insights data is updated every 15 seconds to help marketers understand who is researching right now.
In addition to data quality, the quantity of data also impacts your intent data’s reliability. Using a broad data set from a number of sources will help. Using a range of intent signals will help you be more precise and help prevent wasting marketing dollars on visitors who were just browsing.
Intent Data is Only as Effective as Your Overall Strategy
Intent data is very useful for today’s B2B marketers, but it doesn’t exist in a vacuum. It’s a part of your overall B2B marketing strategy.
If your organization hasn’t invested the time and resources into developing a profile of your ICP and customer personas, or it doesn’t have a good handle on its customer journey, intent data alone will likely be ineffective.
Helping shepherd your potential buyers through the funnel toward a purchase is a bit like solving a puzzle, except you, dear marketer, don’t get to decide which piece you’re going to place next. That’s because today’s buyers have all of the control over the process.
Intent signals will help you guide prospects as best you can, but ultimately the decision to engage is theirs. And once they do engage, your product needs to fit their needs and budget.
Intent is a worthy addition to your marketing data stew, but the best result comes when it’s combined with all your data and B2B marketing tactics.
