How Does Research Intent Work?

Last updated: September 15, 2026

Overview

Vector's Research Intent signal helps you understand when contacts are researching topics relevant to your business across the web.

Rather than looking at individual keyword searches, Research Intent uses broader topics to identify patterns of research activity. This gives you another piece of evidence about what someone is exploring, which you can combine with ICP fit, website activity, and CRM context.

New to Signal Library?

Research Intent is one of the signals managed in Signal Library. You add the topics you want Vector to monitor in Signal Library, then use Research Intent as a data source when building Segments.

Learn more about Signal Library here.

How Research Intent Works

Research Intent is designed to capture research activity around a topic, not individual searches or mentions.

1. Research Topics Instead of Keywords

Research Intent topics are broader than individual keywords.

Think of a topic as an umbrella that groups together related content and research activity across the web. This helps capture someone researching a subject in different ways rather than relying on one exact search term.

Examples might include:

  • A product category

  • A competitor

  • A technology

  • A broader industry topic

2. Research Activity Across the Web

Vector analyzes engagement across a large network of publishers and web content related to your selected topics.

This can include activity on:

  • Industry publications

  • Educational content

  • Review sites

  • News articles

  • Other relevant web content associated with a topic

The goal is to understand whether a contact is researching a topic—not simply whether the topic appeared on a page.

3. AI Helps Classify the Topic

Vector uses AI models to understand the context of the content someone is engaging with.

This helps distinguish between content that is genuinely about a topic and content where a keyword may only appear incidentally.

Research Intent is evidence of research activity, not proof that someone is ready to buy.

How Research Intent Fits Into Signal Library

Signal Library is where you choose the Research Intent topics you want Vector to monitor.

Once you've added your topics:

  1. Go to Signal Library → Research Intent → Configure.

  2. Add the topics you want to monitor.

  3. Build a Segment using Research Intent as the data source.

  4. Filter by those topics and combine them with ICP, account, or website activity filters.

This lets you turn research activity into audiences and workflows inside Vector.

Understanding Intent Frequency

Research Intent includes three frequency levels to help you understand how often someone has researched a topic during a 14-day window.

Low intent level = 2+ interactions with the topic in the last 14 days.

Medium intent level = 5+ interactions with the topic in the last 14 days.

High intent level = 10+ or more interactions with the topic in the last 14 days.

Higher frequency means more repeated research activity around the topic. It does not automatically mean someone is ready to buy.

How to Use Intent Frequency

Different frequency levels can be useful for different marketing and sales motions.

Low Intent (1 interaction)

Best for:

  • Brand awareness campaigns.

  • Educational content.

  • Building larger audiences around early research activity.

Medium Intent (5 interactions)

Best for:

  • Nurture campaigns.

  • Thought leadership.

  • Driving visitors to additional educational content on your website.

High Intent (10+ interactions)

Best for:

  • Smaller, more focused audiences.

  • Combining Research Intent with ICP or account filters.

  • Triggering additional marketing or sales workflows when paired with other evidence of engagement.

The strongest workflows typically combine Research Intent with other signals, such as website activity, account stage, or ICP fit.

Best Practices

  • Start with a focused set of 5–10 Research Intent topics.

  • Combine Research Intent with ICP or account filters instead of targeting every contact researching a topic.

  • Treat Research Intent as one signal among several, alongside website activity, CRM context, and campaign engagement.

  • Use different intent frequencies depending on whether your goal is awareness, nurturing, or more targeted follow-up.

Key Takeaways

  • Research Intent identifies contacts researching topics relevant to your business across the web.

  • Topics are broader than individual keywords or searches.

  • Research Intent is configured in Signal Library and used as a data source in Segments.

  • Intent frequency measures repeated research activity over a 14-day period.

  • Research activity is useful evidence—but it should be combined with other signals before making marketing or sales decisions.