Intent Data: The Ultimate Guide for B2B Businesses

67% of the B2B purchase journey is now done digitally. 

Your prospects are reading analyst reports, comparing vendors on G2, watching product demos, and building internal business cases. By the time they fill out your demo form, they’ve likely already decided whether you’re in or out. 

The linear awareness to decision marketing funnel no longer matches how B2B buying actually happens.

Three fundamental shifts have rewritten the rules:

Shift 1: The Rise of the Buying Committee

Today’s B2B purchases involve an average of 11+ stakeholders across multiple departments, each with differentpriorities: 

• The CFO cares about cost and ROI 

• The IT Director focuses on technical requirements 

• The VP of Operations wants ease of implementation 

• The CRO wants to see pipeline and revenue 

• Security teams need compliance assurances 

A single champion isn’t enough. One dissenting voice can kill your deal. You need visibility into the entire buying committee to address each stakeholder’s concerns.

Shift 2: The Digital-First Research Phase 

Your buyers are doing their homework online (often anonymously). Buyers are: 

• Reading articlesand reports about their challenges

• Viewing case studies and whitepapers 

• Watching competitor demos
• Checking reviews on G2 and Capterra 

Most of this happens off your radar. You don’t know who’s researching or what they’re exploring during the most critical phase of their journey.

Shift 3: The Limits of the MQL 

Marketing Qualified Leads (MQLs) still matter, but they don’t tell the whole story. One person downloading a whitepaper doesn’t represent an entire account. 

When 5-11 stakeholders are researching independently, a single lead score can’t tell you if the broader buying group is engaged or moving toward a decision. 

The result? Sales receives a contact labeled “qualified” with zero context about the rest of the account. The lead stalls. The opportunity goes cold.

The Intent Data Opportunity 

The companies that win can see into anonymous research behaviors. 

Intent data shows you which accounts are actively exploring solutions like yours, what topics they’re investigating, which personas are engaged, and where they are in their research journey. 

This is why leading B2B organizations, such as Nvidia and Oracle, are shifting from lead-based to intent-based demand generation strategies. They engage buyers earlier with hyper-relevant messages, before competitors can influence the decision. 

B2B Intent data reveals which companies are researching solutions like yours, before they fill out a form or book a demo on your website. 

It tracks behavioral signals across the internet: the content prospects consume, the topics they explore, how much they research, and how their activity evolves over time. 

Think of it as a window into the 67% of the buyer journey you normally can’t see.

What Intent Data Shows Businesses 

Account identification 

Which companies are showing relevant online research activity 

Topic and keyword visibility 

What specific topics, pain points, solution categories, and vendors those accounts are exploring 

Signal strength and recency 

How strong, frequent, and recent their activity is, so you can track changes in engagement 

Buying group activity 

Which personas within an account are actively researching, including their individual and collective interest levels 

Persona-level insight 

Which job functions and seniority levels are researching specific topics

What Intent Data Is NOT 

It’s not lead generation 

It identifies accounts and personas researching, not necessarily contacts ready to buy. They need to be properly nurtured and scored before being passed to sales. 

It’s not predictive analytics 

It shows current behavior, not pipeline predictions based on historical patterns. For that, you need to combine it with your own first-party data (CRM, CDP, MAP). 

It’s not a replacement for first-party data 

It enriches what you already collect through your own analytics and CRM. It doesn’t replace it. 

Intent data works best when integrated into your existing tech stack. Think of it as a directional signal that’s powerful for focus and timing, but not a substitute for first-party engagement.

Why Intent Data Matters Now 

Consider these stats: 

• 92% of B2B buyers have a shortlist of vendors in mind before formal evaluation begins 

• In fact, 41% have a single preferred vendor already identified 

• 61% of B2B buyers would prefer not to talk to sales reps at all 

The most crucial stage of the buying journey happens before the form fill or demo request—when buyers form opinions, establish evaluation criteria, build shortlists, and discuss with their buying committee. 

Intent data helps you identify these moments to engage at the right time with the right message. 

B2B organizations using intent-driven strategies report higher pipeline generation, improved forecast accuracy, lower customer acquisition costs, and faster sales cycles.

Intent data providers collect and interpret privacy-compliant behavioral signals to show which accounts and personas are actively researching B2B challenges, interests, solutions, and vendors. 

At Intentsify, we monitor more than 1.1 trillion intent signals each month, then apply AI models to classify, weight, and organize those signals into actionable intelligence aligned with your unique offerings and use cases.

Signal Collection 

Intent data comes from multiple sources: 

Publisher networks 

Content consumption across partnered B2B publications 

Content engagement signals 

Research activity across articles, reports, and resource hubs 

Review platforms 

Activities indicating vendor comparison and evaluation from sites like G2 

Topic and keyword signals 

Research activity drawn from multiple sources—topics use AI to automatically classify content being consumed and keywords tracks pecific terms or phrases 

Buying group and persona signals 

Activity patterns and interest levels tied to specific job roles and functions, presented by persona or as an aggregated view across all buying roles 

First-party data (1PD) 

Website, email, event, and product-interaction data you supply and integrate into your account scoring 

Together, these sources provide a unified view of how companies research B2B solutions across the web.

How Intent Data Helps Each B2B Department

Data for data’s sake is useless. The goal is actionable intelligence that drives results. 

This means: 

• Sales teams prioritize accounts showing the strongest buying signals and tailor outreach based on specific topics, solutions, and vendors propsects are exploring

• Marketing teams  build campaigns aligned to current research interests, not just generic persona messaging 

• Customer success teams identify churn risk as well as cross-sell and upsell opportunities before other vendors engage 

When combined, these insights transform intent data from passive observation into a proactive competitive advantage. 

To get a complete picture of buyer behavior, you need to understand first-party, second-party, and third-party intent data and how they work together.

1. First-Party Intent Data

What it is: Data from your own digital properties: your website, email campaigns, virtual and in-person events, product usage, and CRM interactions. 

The upside: High accuracy. You know exactly what prospects have done on your owned properties. 

The limitation: It’s limited to known contacts who already engage with you. It mostly captures late-stage signals.

2. Second-Party Intent Data

What it is: Someone else’s first-party data that you access through a trusted partnership or data exchange. 

Examples: Webinar signups from a partner platform, engagement from publisher sites, or activity from review and comparison sites 

The upside: Identifies more niche audiences (e.g., IT professionals), but offers less signal coverage than third-party intent data.

3. Third-Party Intent Data

What it is: Data from external sources like publisher networks, advertising platforms, and review sites. 

The upside: Offers the highest volume of intent signals and surfaces early research behaviors before prospects visit your site. Reveals competitive intelligence and anonymous research at scale. 

The limitation: Less precise than first- or second-party data on its own.

The Most Effective Approach: Use All Three 

Combine second-party intent with your own first-party data to enrich your account intelligence, then layer third-party signals to scale your reach. 

Prospects showing both external intent signals and engaging with your owned properties? Those represent your highest-quality opportunities.

Intent to Learn vs. Intent to Buy 

Not all research signals indicate purchase readiness. AI-powered intent helps you distinguish between: 

Intent to learn (early-stage educational research): 

• “What is account-based marketing?” 

• Industry trend reports and analyst research 

• Thought leadership content 

• General business challenge exploration 

Intent to buy (active vendor evaluation): 

• “Best enterprise marketing automation platforms” 

• Vendor comparison content 

• Product reviews on G2 and similar sites

• Pricing page research 

• Implementation timeline questions 

Understanding the difference means you can engage early-stage researchers with messaging aligned to learning, not conversion.

How Topic and Keyword Intent Work Together 

Early intent data solutions relied on simple keyword matching. You’ll see when someone researched “marketing automation.” Simple, but limited. 

Keyword signals remain important. They capture the exact terms buyers use when researching. But on their own, they can be broad or ambiguous.

Topic models analyze semantic relationships, group related concepts, and interpret how terms are being used. This reduces noise and helps distinguish genuine interest from general browsing. 

Together, topic and keyword signals create a more accurate view of account behavior. Custom AI models strengthen this further by learning your company’s specific terminology, solution categories, and competitive landscape.

The intent data market has evolved dramatically. Early providers in the mid-2010s offered basic keyword tracking with limited context. By the early 2020s, solutions like Intentsify began using AI and natural language processing to analyze topics and buyer behavior. 

Today, Intentsify trains custom, solution-specific intent models that interpret nuanced signals unique to each business.

The Limitations of Generic Intent 

Most intent providers rely on prebuilt topic taxonomies with broad categories like “marketing automation” or “cloud security.” 

These create three major problems:

1. Noise and false positives

“Marketing automation” may capture signals from small-business email tools, enterprise platforms, event marketing software, and social media management solutions. High volume, low precision.

2. Lack of competitive context

Standard topics often miss high-intent behaviors, like prospects comparing your company to your competitors.

3. One-size-fits-all modeling

Predefined frameworks can’t account for your solution’s unique language, differentiation, and value proposition. 

The result? Generic intent highlights broad market activity but misses the nuanced, high-quality signals that reveal genuine buyer interest in your specific solution.

How Intentsify’s Custom Intent Models Work 

Forrester named Intentsify a Leader in The Forrester Wave™: Intent Data Providers For B2B, Q1 2025, with the highest overall score for Current Offering and the highest score possible across 12 of 21 categories. 

Intentsify is the only advanced intent data solution that uses natural language processing (NLP) and large language models (LLMs) to train solution-specific intent models based on your unique offerings and positioning. 

Here’s how: 

The AI ingests your content 

Web pages, case studies, product collateral, competitor comparisons—everything that describes how your solution is positioned and differentiated. 

It maps semantic relationships 

Instead of relying on static keyword lists, it understands the connections between your products and services, messaging, value propositions, and use cases.  

It uniquely weights signals 

The model detects when your target accounts and personas are researching topics that align with your specific value propositions, not just broad categories, and weights them by relevance. 

We act on this intelligence 

These intent signals power the targeting, messaging, and creative for your media activation strategy through our fully managed programmatic advertising and content syndication programs. 

The Critical Importance of B2B Buying Groups 

Traditional account-level intent shows that a company is interested. Buying group intent goes further by identifying who inside that company is driving the research and what they’re interested in. 

Modern B2B purchases involve large, distributed teams, often including ten or more stakeholders influencing the decision. Without persona-level clarity, targeting and personalization remain guesswork. 

What buying group intent reveals: 

Active personas 

Which roles are showing intent: finance, IT, marketing, operations, etc. 

Persona-level focus 

What each persona is researching based on the topics with which they actively engage with

Stakeholder interest level 

How interested each decision-maker and influencer is in a solution like yours, based on their research behaviors, and their collective interest level 

Engagement progression 

How persona activity is changing over time, from early research toward deeper evaluation 

Different stakeholders seek different information at different times. Buying group intent captures these dynamics, giving your teams the insight to engage each decision-maker with precision and context.

Fuel Predictable Growth with Real-Time Buyer Intelligence 

B2B buyers complete most of their research before engaging with vendors. Traditional lead generation only captures late-stage interest and misses the early indicators that drive pipeline growth. 

Intent data changes this by revealing: 

• Which accounts are actively researching your solution category 

• What topics and challenges they’re exploring 

• Who within the buying group is engaged 

• When they’re moving from learning to evaluation 

Generic intent platforms surface broad activity with limited precision. Intentsify builds AI-powered, solution-specific intent models that reflect how your actual buyers research. 

With access to over 1.1 trillion monthly signals and activation across content syndication and programmatic advertising, Intentsify gives you clear direction on where to focus and when to act.