Intent data helps businesses determine if a prospect is likely to buy by analyzing their activities and behaviors.
By understanding the intent of potential customers, companies can tailor their marketing and sales strategies for better results.
But there's a problem.
Lots of that intent data is not as powerful as it seems.
Hint: The most powerful intent data in 2025 is first party, real-time website behavioral data. Read the full article to find out why.
Key Takeaways
- Traditional Intent data is key for understanding potential customer behavior, revealing their interests and possible purchase readiness to enhance B2B sales.
- Leveraging intent data allows for personalized outreach and early engagement with prospects, significantly increasing the chances of closing sales before competitors.
- Combining first-party and third-party intent data provides a comprehensive view of buyer behavior, improving targeting and marketing strategies.
- However, the first-party data on your website offers the most accurate view of intent data due to the large volume of data available to process with AI and machine learning.
- For example, leveraging a website buyer behavior model, companies like Okta, Payscale, Boomi, and Truckstop are getting game-changing results, such as doubled conversion rates, 11x sales team efficiency, 27x ROI, and more.
Understanding Intent Data
Buyer intent data is market intelligence that tracks and analyzes the online research behaviors of leads.
The difference between intent data and intent signals is that an intent signal is the output from processing intent data. For example, a lead score might be the signal, while the prospect's website behavior made up of many data points is the intent data behind the signal.
Intent data as a category has grown - today it encompasses a comprehensive range of digital footprints left by potential customers, from search queries to social media engagement and changes in jobs, providing valuable insights into their interests and actions.
Intent data is most useful in B2B sales environments, where b2b intent data is instrumental for comprehending customer requirements and developing robust sales pipelines.
By tapping into this resource, marketers and sales teams can gain an advantageous edge by better recognizing customer triggers and patterns indicative of purchasing behavior. This insight allows them to uncover hidden opportunities that propel business growth while maintaining an edge over competitors.
However, not every intent signal conveys equal significance when deciphering buyer intentions.
General signals such as pricing page visit counts or general search terms may not accurately represent genuine purchase intents.
Additionally, intent data from third party providers may be dated, inaccurate, or irrelevant.
Instead, deep and specific details within user behavior on owned platforms like websites tend to provide stronger indications regarding buying intent. Here's why.
Types of Intent Data
First Party Intent Data
Direct interactions on your own digital properties provide you with first-party intent data, which is highly regarded for its dependability and volume.
Pros of First Party Intent Data:
The best example of first party intent data is on your website.
All of the data regarding your website visitors and their actions can be collected, captured, and processed by you and nobody else. Therefore, it's "first party" intent data.
This type of intent data is powerful because:
- You can capture ALL of the possible intent data allowed for by your platforms (not just piecemeal)
- The higher volume of first party intent data allows more accurate intent signal outputs
- The intent data can be captured and processed in real-time rather than latent time
- You have full control over the intent data (as it's owned by you)
The downside of first-party intent information is that it may not capture the full spectrum of a potential buyer’s journey if they have yet to show interest in engaging directly with your brand’s site or platforms. Third-party sources complement this by revealing activities across competitors’ domains and wider online behavior patterns.
Third Party Intent Data
Third party-related intelligence is typically purchased from other companies who collect it.
Pros of Third Party Intent Data:
Typical examples of third party intent data include keyword search surges, researching competitor products and services, changes to job titles and funding, etc.
- Third party data is great for identifying prospects who are early in their decision-making process rather than those already considering making a purchase.
- Third party intent data can capture information about prospects who haven't engaged with you or your brand at all T
The Downsides of Third Party Intent Data
- It may be dated and therefore no longer timely or relevant
- It may be inaccurate (as this intent data is often acquired from networks outside of the provider's control)
- It is sparse in volume (typically a handful of high level data points that are not enough to depict intent)
- They typically only provide data on known accounts and contacts - leaving anonymous website visitors without any useful data to work with.
Ultimately, leveraging both varieties of these datasets allows your company to get an expansive view into consumers’ purchasing signals - but there's more to unpack.
Subtypes of Intent Data
Now we know that data can be first or third party, but there are different categories within those data sets, including:
- Search Intent Data: Information about what potential customers are searching for on search engines, including search volume, clicks, and impressions.
- Engagement Intent Data: Measures interactions with content, emails, or other marketing materials, such as email responses, content downloads, and social media interactions.
- Firmographic Intent Data: Details about prospective companies, including size, location, industry, and revenue/
- Technographic Intent Data: Information about the technologies, software, hardware, and networks a business uses.
- Behavioral Intent Data: Data about users' online behavior, including complex website actions and pattern recognition (but note that many providers believe that "visiting the pricing page" of your website is behavior, when in reality it is simply an engagement metric).
Why Intent Data is Crucial for B2B Sales
Utilizing intent data in B2B marketing and sales strategies allows your company to refine prospect targeting, engagement strategies, lead prioritization, and personalization in order to increase revenue and pipeline.
Speed is one of the critical elements here. Given that over half of the sales opportunities are seized by those who engage first with buyers, it’s imperative to quickly identify and reach out to prospects effectively.
Tips for Leveraging Traditional Intent Data
Intent marketing leverages intent data to target potential customers effectively.
Historically, it's been used in the following ways:
Creating and Refining Target ICP / Account Lists
Integrating buyer intent with both firmographic and technographic data to narrow down the Ideal Customer Profile list for sales teams to work with.
Personalization of Content and Outreach
Utilizing intent data, marketing and sales teams can tailor content and outreach based on the data at hand, allowing more customized communications that are more likely to convert (rather than generic, copy + paste spam content).
Early Engagement of Sales Ready Prospects
Intent data enables sales teams to contact prospects early in their research process, enhancing engagement opportunities.
Quick responses increase the chances of winning sales, as 50% go to the vendor who reacts first. Early engagement helps influence prospects before they form strong opinions.
For this to work, real-time intent data is essential. That's why that first party website intent data is critical - more specifically, the behavioral intent data shown by visitors.
The Future of Intent Data - Predicting Conversions by Behavioral AI
The problem with most of the traditional approaches to intent data is that they lean on third party intent, which is prone to inaccuracies.
However, there is also a problem with first party intent data - companies believe that a potential customer visiting your website is a strong intent signal. It's barely a drop in the ocean.
Furthermore, some intent data providers think that a visitor going to your pricing page is "buying behavior" - when it's also just a high level engagement metric.
The problem is this - buyer behavior is far more nuanced, deep, and complex than a handful of engagement metrics.
To demonstrate this, Lift AI ran a study on the most common website intent data - pricing page visitrs.
They found that 88% of high intent website visitors don't visit the pricing page at all, and out of those that do, 94% of them are not buyers.
Instead, Lift AI measures hundreds of micro behavioral signals for every website visitor, then uses an AI model to score those behaviors in real-time. It leverages pattern recognition and eliminates co-occurrence bias to accurately predict which visitors are likely to convert, and which are not.
Lift AI's model was pre-trained on billions of data points including millions of live sales interactions to understand what true buying behavior looks like, which means it can accurately score the buyer intent of website visitors in real-time even if they're completely anonymous.
Those buyer intent scores can then be integrated with your entire tech stack to optimize the user journey, engage likely buyers, retarget to high intent visitors, or prioritize sales team follow up with high intent visitors that left the website.
The Proof is in the Data: Success Stories with Lift AI
Lift AI has transformed B2B sales strategies for various companies by using real-time behavioral website buyer intent data to detect and engage high-intent buyers.
- RealVNC increased web shop revenue by 13% within the first 60 days of implementing Lift AI.
- Boomi more than doubled conversion rates from Drift conversational marketing by using Lift AI scores to target high-intent visitors in real time.
- PointClickCare saw a 168% increase in qualified leads from chat by shifting its strategy with Lift AI.
- Chronus integrated Lift AI scores with their 6Sense “Buying Stages,” achieving an 11.6x increase in sales team efficiency by targeting high-intent Lift AI visitors also in a wider account Buying Stage.
How to Start With Intent Data
In summary, intent data and AI are revolutionizing the way businesses predict buyer behavior. By understanding and leveraging intent data correctly, companies can enhance their marketing and sales strategies, making them more targeted and effective.
The best place to start with intent data is on your website - after all, why invest in finding more buyers for your products or services when there are already buyers on your website right now?
Then, once you have exhausted the opportunity of anonymous website visitors (and known accounts, if you have an ID reveal tool) on your website, then you can layer in the additional third party intent data to get a wider view of your ICP list and off-site activity.
It’s time to take action and start leveraging intent data and AI to predict buyer behavior. Get started with a free 30 day Proof of Concept with Lift AI.
Frequently Asked Questions
What is intent data?
Intent data is all about understanding the online behavior of potential leads, like the searches they conduct and the websites they visit. It helps you gauge their interest and tailor your approach accordingly.
What are the main types of intent data?
The main types of intent data are first-party and third-party. First-party data comes from your own site interactions, whereas third-party data is gathered from external platforms.
How is intent data collected?
Intent data is collected using cookies and IP addresses for first-party data, along with tracking user behavior across different websites for third-party data. This combination helps companies understand consumer interests and intentions.
What are some challenges with buyer engagement?
Navigating the complexities of responsibly handling intent data, with a keen focus on obtaining consent and safeguarding privacy, is imperative for buyer engagement. There are obstacles presented by disjointed third-party data. It’s essential to confront these challenges in order to cultivate significant relationships with your buyers.
