Understanding Different Types of Intent Signals for B2B Marketing

What Are Intent Signals?

Intent signals are behavioral clues that indicate a potential buyer’s interest in a particular topic, solution, or product category.

They’re the digital breadcrumbs people and companies leave behind as they research online — whether that’s reading blog posts, searching Google, visiting pricing pages, comparing vendors, or engaging with content on review sites like Gartner.

Common examples of intent signals include:

• Repeated website visits to your product or pricing page
• Downloads of solution guides, whitepapers, or case studies
• Increased search volume around keywords like “best [category] software” or “alternatives to [competitor]”
• Engagement with comparison articles, review platforms, or webinar replays
• Spikes in activity from a specific company or account across multiple channels

Here’s an example: Let’s say you sell a B2B project management tool.

One of your target accounts—a mid-sized tech company—has a buyer persona from their operations team visiting your site three times in two days.

• They read a blog post titled “10 Ways to Eliminate Workflow Bottlenecks”
• Download a gated comparison guide between your solution and a competitor
• And then later, you notice that the same company name spiked in third-party intent data for the keyword “project management software for agile teams.”

All of these actions are clear intent signals that indicate the prospect’s interest level and give you an idea of where they are in the buying journey.

Recommended → What Is B2B Intent Data? How to Get It, Use It, and More

Types of Intent Signals

Engagement Intent Signals

These are observable behaviors that a prospect or account performs directly with your owned assets or channels, such as your website, emails, webinars, or product interface.

These actions reflect a clear and deliberate interest in your brand, offering, or specific product.

Examples:

Website Activity

This is simply prospects landing on and navigating through your website.
Here’s what to track:

• Visits to high-intent pages (e.g., pricing, demo, contact, product features)
• Number of page views per session
• Depth of scroll and dwell time on content
• Returning visits within a short timeframe

Content Downloads

When a user fills out a form or accesses gated content, they’re signaling a deeper level of interest in the topic or problem.
Here’s what to track:

• Whitepapers, guides, playbooks, or case study downloads
• Frequency of downloads from the same account
• Topic relevance to product or service
• Downloading bottom-of-funnel content (e.g., implementation checklist)

Email Engagement

This is also an early indicator of interest, but it needs context. Opening an email is one thing; clicking or forwarding is much more meaningful.
Here’s what to track:

• Open rates (combined with recency/frequency)
• Click-through rates on specific CTAs
• Link engagement and dwell time (did they just click or actually read?)
• Email forwards or multiple opens (e.g., viewed by multiple stakeholders)

Webinar and Virtual Event Attendance

This behavior reveals real-time intent, especially when the topic aligns with your offering or product use case.
Here’s what to track:

• Registrations vs. actual attendance
• Duration watched (did they stay till the end?)
• Questions asked, polls answered, or chat participation
• Follow-up resource downloads after the event

Use Cases

• Real-Time Alerts. Notify SDRs or BDRs when high-value accounts hit key pages.
• Personalized Retargeting. Show specific ads or offer custom landing pages based on page visits or downloads.
• Segmented Nurtures. Trigger nurture sequences based on past engagement type and content category

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Pro Tip → Using Demandbase, you can select an account list and date range to see accounts ranked by Intent Engagement Minutes, along with the keywords they are reading about. You can also find the keywords that are being read about by the most companies.

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See Demandbase in Action

Research Intent Signals

These signals reveal that a potential buyer is actively investigating a problem or exploring a specific topic, solution, or challenge related to your industry.

They typically happen outside your owned channels (third-party websites, publisher networks, and search engines) and show early to mid-stage buying interest.

Examples:

Keyword Searches on Third-Party Sites

These are searches conducted by buyers on platforms like Google, Bing, or publisher co-ops (e.g., TechTarget, Foundry, Bombora’s B2B Data Co-op).
Here’s what to track:

• High-intent search queries like “best CRM for SaaS” or “enterprise security platform comparison”
• Volume and frequency of searches from specific IPs or accounts
• Trends in topic clustering (multiple related searches)
• Mentions in social media or press

Topic Consumption Across Publisher Networks

Many B2B data vendors (like Bombora, G2, or Foundry) aggregate reading behavior across thousands of niche blogs, trade journals, and professional communities.
Here’s what to track:

• Number of articles read within a topic cluster (e.g., “ABM,” “email automation,” “cloud security”)
• Changes in consumption intensity over time (surge behavior)
• Patterns across buying committee members

Review Site Activity (e.g., G2, Capterra, TrustRadius)

Review platforms offer some of the most explicit mid-funnel signals. When prospects are comparing vendors, reading reviews, or exploring competitor pages — you can infer serious interest.
Here’s what to track:

• Page visits (your profile, competitors’ profiles, category overview pages)
• Comparisons viewed or downloaded
• Topics and features read the most
• Account match if available (via G2 Buyer Intent or similar)

Forum and Community Engagement

Buyers often seek peer recommendations and answers in niche Slack groups, Reddit communities, Stack Overflow, or private tech circles.
Here’s what to track:

• Mentions of your product or competitors
• Questions related to your use case (e.g., “Anyone using an API-first email platform?”)
• Topic-specific group participation

Use Cases

• Account Prioritization. Assign scores based on surge behavior and research topics, and segment by buying stage.
• Content Planning. See what topics prospects care about most, and double down on high-interest themes.
• Sales Enablement. Inform reps on what accounts are researching and reading — before they make contact.

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Pro Tip → You can set up TrustRadius and G2 integration on Demandbase to ingest product review intent into your account.

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Hiring Intent Signals

These signals uncover organizational shifts that indicate future buying intent. They reveal macro-level movements within a company, such as team expansion, leadership changes, job postings, or funding events.

Examples:

Job Postings for Roles Relevant to Your Solution

When a company advertises for new positions, especially within functions your product supports, it often signals that a strategic investment is either underway or imminent.
Here’s what to track:

• Roles like “Marketing Operations Manager,” “Salesforce Admin,” “Security Analyst,” “DevOps Engineer,” etc.
• Keywords in job descriptions (e.g., “familiarity with HubSpot,” “experience with SOC 2 compliance,” “automation strategy”)
• Volume of openings within a specific department or job family

Executive Changes in Key Buying Roles

Leadership shifts, especially in senior roles like CMO, CIO, VP of RevOps, or Director of Security, often lead to new initiatives, budget reallocations, or tech stack changes.
Here’s what to track:

• New hires, promotions, or departures in VP+, director, or key stakeholder roles
• Leaders with a track record of implementing similar tools at previous B2B companies
• Recent leadership updates in core departments (marketing teams, sales, IT, HR, finance)

Department Growth or Team Expansion

A spike in hiring across a particular department (sales, product, IT) can indicate that the company is preparing to scale operations, which often requires new tools, automation, and systems.
Here’s what to track:

• Growth in specific departments (e.g., 10+ open roles in engineering)
• Budget increases (indirectly inferred from hiring scale)
• Geographic expansion (e.g., setting up a new regional office)

Use Cases

• Pre-target ABM Campaigns. Serve ads or send outbound campaigns before traditional buying signals appear
• Sales Trigger Alerts. Notify reps when a strategic account posts a relevant job or hires a new exec
• Buyer Persona Tracking. Align role-based signals (e.g., “New CMO at X”) with customized messaging

Technographic Intent Signals

These signals reveal which technologies a company is currently using, has recently adopted, is planning to upgrade, or is actively researching.

Examples:

Technology Installations

This involves tracking the tools and platforms a company already has in place.
Here’s what to track:

• Current systems in use (e.g., Salesforce, Microsoft Azure, Shopify)
• Tool categories by function (CRM, marketing automation, analytics, payment processing)
• Specific tools you integrate with or compete against

Recent Tech Stack Changes

When a company adds, removes, or replaces core technologies, it often signals change readiness, pain points, or the need to plug gaps.

Here’s what to track:

• Net new tech added in the past 30–90 days
• Removal of key tools (e.g., removing Salesforce may indicate migration)
• Upgrading from free to premium tools

Software Upgrade Patterns

Intent signals can also be found in platform upgrade activity. When companies move to higher-tier subscriptions or enterprise-grade versions, it’s a sign they’re scaling or looking for deeper integrations.

Here’s what to track:

• Tier changes (e.g., HubSpot Starter → Pro → Enterprise)
• Volume increases in licenses/seats
• More integrations enabled or features activated

Use Cases

• Segment your outreach based on current tech (e.g., “For Salesforce users” vs. “For HubSpot teams”)
• Create integration-based messaging (“Works with [company] in 2 clicks”)
• Tailor onboarding journeys (e.g., “How to get started with our tool if you use X”)

Related → What Is Technographic Data? How to Get and Use It

Where Do Intent Signals Come From? (Data Sources)

Intent signals come from three main data sources:

• First-Party Intent Data. Collected directly by you
• Second-Party Intent Data. Shared with you by partners
• Third-Party Intent Data. Purchased or accessed from external providers

Let’s explore each one in full detail.

First-Party Intent Data

These are behavioral signals captured directly from your owned channels such as website, emails, landing pages, and product interfaces. 

Because you’re collecting this data yourself, first-party signals are the most accurate, reliable, and privacy-compliant.

What They Include:

• Page visits (e.g., pricing page, product tour, demo request)
• Content engagement (e.g., downloads, time spent reading a blog, video views)
• Email behavior (e.g., opens, click-throughs, CTA interactions)
• Product usage data (e.g., trial activation, feature engagement, login frequency)

Limitations

• Limited Visibility. You only see behavior after someone has found your brand
• Requires Good Data Hygiene. Broken tracking or dirty CRM fields reduce its value
• Misses Top-of-Funnel Interest. You can’t see early research on third-party platforms

Second-Party Intent Data

Second-party intent data is another company’s first-party data shared with you through a partnership. They are highly valuable because they are direct user behaviors, just not on your own site. 

What They Include:

• Webinar registrations and attendance hosted on a partner platform
• Buyer activity on review platforms like G2 or TrustRadius, when you subscribe to their intent data programs
• Engagement from syndicated content via media partners

Limitations

• Dependency on Partnerships. You need ongoing access or joint campaigns
• Data Format Inconsistency. May require manual cleanup or mapping
• Not Scalable Alone. Usually limited in volume

Third-Party Intent Data

These data are collected from a network of external websites, ad exchanges, forums, and publisher co-ops. They are aggregated and analyzed by intent data providers to detect which topics an account is actively researching. 

They also help identify anonymous interest and intent from companies that haven’t yet interacted with your brand. 

What They Include:

• Article reads across tech blogs and industry sites
• Ad clicks or retargeting engagement
• Topic surge analysis (i.e., increased frequency of a topic searched by users from a company IP)
• Downloading guides or whitepapers from content syndication partners

Limitations

• Anonymized by Default. You often see company-level intent, not individual users
• Data Quality Varies by Provider. Precision and freshness differ
• Requires Enrichment Tools. You may need to match anonymous intent to known accounts
• Privacy and Compliance. Must ensure vendors are GDPR/CCPA compliant

Intent Signal Source	Source	Strength	Use Case	Limitations
First-party	Your website, emails, product	High accuracy	Lead scoring, nurture, retargeting	Limited to known users
Second-party	Partner platforms (e.g., G2, TrustRadius, Gartner)	High trust	Early-stage targeting, review monitoring	Limited scale
Third-party	Publisher co-ops, ad networks	Wide coverage	Discovering in-market accounts	Lower precision; requires enrichment

5 Ways to Use Intent Signals in B2B Sales and Marketing

Identify In-Market Leads

The traditional lead gen approach is to ‘blast’ a lead list — and hope someone in your target audience happens to be in-market. 

But in reality, only 3–5% of your potential customers are looking to buy at any given time. Hence, rendering that approach useless. 

Meanwhile, intent signal flips the model by focusing your marketing efforts on accounts that are already demonstrating buying behavior. 

Here’s how it works: 

By tracking third-party intent signals—like topic searches, content consumption, or product comparisons—combined with first-party activity (like visits to your pricing or product pages), you can spot which companies are actively showing buying intent. 

For example, let’s say you notice a specific company is spiking in third-party research activity around keywords like “data security for SaaS platforms” or “SIEM alternatives.” 

At the same time, someone from that same company visits your site and checks out your product and solutions pages. 

Even if you don’t have a contact name yet, the account-level behavior tells you this company is actively researching. 

With this, you can now: 

• Add this account to a targeted LinkedIn campaign or retargeting list
• Route it into your “high-priority” ABM workflow
• Alert sales with a context-rich snapshot of what they’re researching
• Use content that speaks directly to the problem they’re exploring

This shifts your approach from waiting for inbound to proactively focusing on accounts that are already in a buying mindset.

Improve Lead Scoring and Prioritization

Traditional lead scoring models often rely on static demographic or firmographic data, like job title, company size, or industry. 

But that barely scratches the surface of actual buyer readiness. On the flip side, intent signals help you understand what they’re actually doing. 

By layering buyer intent data—especially third-party signals and behavioral trends—into your lead scoring framework, you can assign more accurate scores based on how ready an account is to buy. 

Here’s how to make it work: 

• Add intent signals as a weighted layer in your lead scoring model. For example, a contact from your ICP showing high intent on third-party research can score +20 points automatically. 
• Use keyword-level intent to prioritize accounts based on relevance. A lead researching “best CRM for SaaS startups” might be more valuable to you than one researching “how to use spreadsheets for sales.” 
• Surface and prioritize leads that match intent + fit. High-intent behavior + high-fit profile = sales-ready. 

For example:

• A lead who visits your blog might get a +5 points.
• But a lead from a target account who’s surging on a buying keyword (like “customer data platform”) and viewed your pricing page twice in one week can get +30 points. 

Here’s a sample score sheet to guide you:

Signal Type	Points
Visited pricing page	25
Third-party surge on “account-based analytics”	20
Requested demo	30
Attended product webinar	15
Downloaded implementation guide	10
Spent >3 minutes on 2+ solution pages	15
Viewed 3 competitor reviews on G2	10
Opened newsletter	2
Bounced from homepage	-5

Personalize Campaigns and Content

Intent signals give you valuable insight into what those accounts care about right now. And that’s exactly what you need to personalize campaigns that land.

Instead of sending the same generic message to every lead in your nurture stream, you can tailor content based on the topics they’re actively researching. 

There are three primary levels of personalization you can execute with intent signals:

1. Topic-Based Personalization. This reveals what topics your prospects are researching across the web.

Example: A segment of accounts is showing surging interest in “multi-touch attribution.” Rather than pushing a generic campaign, you deliver ads and email nurtures that offer:

• A downloadable guide: “How to Transition from Single-Touch to Multi-Touch Attribution”
• A case study: “How [Company X] Improved Attribution Accuracy by 44%”
• An invitation to a webinar on attribution modeling

2. Stage-Based Personalization

This helps you determine where the buyer is in their journey — early-stage awareness, mid-funnel consideration, or late-stage decision-making.

Each stage requires different messaging, tone, and offers.

Buying Stage	Sample Signals	Best Content Type
Awareness	Topic surge (e.g., “what is PLG?”)	Educational blogs, explainer videos
Consideration	Visits to product pages, comparison guides, reviews	Product webinars, case studies, guides
Decision	Pricing page visits, competitor research, demo requests	ROI calculators, proof-of-concept offers

Example: If an account is researching “employee engagement software” across third-party platforms and has also downloaded your “2024 Buyer’s Guide,” you can assume they’re mid-to-late funnel.

• A live demo link
• A competitor comparison landing page
• A pricing FAQ resource

This keeps your messaging relevant, helpful, and conversion-focused.

3. Account-Level Personalization

This allows you to customize experiences for entire organizations — even when individual contacts are unknown.

How to apply it:

• Dynamically personalize homepage banners or landing pages for target accounts showing high intent
• Send ABM-style email campaigns that reference specific content they’ve engaged with (e.g., “We saw your team reading about zero-trust security — here’s a deeper dive”)
• Create industry-specific messaging or vertical-based nurture paths triggered by account behavior

Example: Company A is surging on “employee experience platforms” and has recently hired a new CHRO. You tailor a nurture sequence:

• Subject: “For HR Leaders Shaping Modern Workplaces”
• CTA: “How your peers in fintech are building EX strategies with [Your Solution]”

This is 10x more likely to engage than a generic campaign, boosting conversion rates.

When you tie it all together, here’s how a Signal-to-Personalized Campaign should look: 

• Signal Detected:

Bombora detects a surge in “ABM strategy” from 5 users at a mid-market healthcare company.

• Enrichment:

Demandbase confirms they’re your ideal customer profile (ICP), uses Salesforce, and attended your recent webinar. 

• Personalized Campaign Launches: 
  • Website headline changes to: “How ABM Leaders in Healthcare Drive Results with [Your Product]”
  • SDR outreach includes subject line: “Saw you’re researching ABM – here’s how we help healthcare teams”
  • Display ads offer a healthcare-specific ABM case study

This coordinated personalization nurtures them through the sales cycle, creating relevance across every touchpoint.

Create Effective Account-Based Marketing (ABM) Strategies

Account-Based Marketing (ABM) is all about precision and relevance—i.e., identifying high-intent leads and engaging them with content and marketing campaigns tailored to their specific needs. 

But ABM only works when you have real, actionable intelligence on what those accounts care about right now. Intent data helps you achieve this. 

Here’s how to make it work:

• Spot early-stage interest in target accounts. If a high-value account starts researching keywords tied to your category, but hasn’t engaged with you yet, that’s your window. Launch a 1:1 ABM campaign, or route them into a tailored ad sequence. 

• Trigger competitive takeover plays. If intent data shows a target account is engaging with your competitor’s content (e.g., branded search terms, comparison guides, or third-party reviews), it’s time to move. Arm your sales team with counter-positioning content, competitive battlecards, or customer stories that show why companies like them switched. 

• Use account-level insights to personalize outreach. Pair firmographic data with the topics they’re researching to shape outreach and campaign messaging. 
  • If an enterprise software company is researching “SOC 2 compliance automation,” your SDRs can lead with a pain point the buyer is actively thinking about. 

For example, let’s say Demandbase surfaces that three of your Tier 1 ABM accounts are showing purchase intent around “best alternatives to [competitor name].” 

That’s your cue to serve up a comparison landing page, retarget with competitive positioning, and equip your sales team with a timely follow-up sequence.

Uncover Churn Risks and Expansion Opportunities

Let’s split this into two phases: 

• Identifying churn risk through negative or shifting intent
• Identifying expansion opportunities through positive intent

Identifying Churn Risk Through Negative or Shifting Intent

Intent signals can alert you when a current customer:

• Starts researching competitor solutions
• Stops engaging with your platform or content
• Begins consuming content about problems you should have solved
• Reduces interaction across channels (low login frequency, no webinar attendance, etc.)

These are early red flags, giving your CS team time to investigate, realign, and save the account.

Signal Type	What It Suggests
Surge in competitor brand/topic	They may be evaluating alternatives
Visits to “best alternatives to X”	Buyer dissatisfaction or intent to switch
Drop in product usage metrics	Decreasing value perception or adoption struggles
Reduction in engagement with CS	Diminishing relationship health
Searches about features you lack	Functionality gaps prompting vendor evaluation

 

Churn Risk Example:

You offer a collaboration tool for mid-sized agencies. One of your customers — a 100-person firm — suddenly surges on “Notion vs. Confluence,” “top project management platforms,” and “how to migrate files from Monday.com.”

Simultaneously, their login frequency drops by 40%.

Action:

Flag the account in your CRM → CS team gets an automated Slack alert → Account manager reaches out with a check-in, offers an optimization session, and shares product roadmap addressing known gaps. 

This timely, signal-driven engagement can salvage the relationship before it’s too late.

Identifying Expansion Opportunities Through Positive Intent

On the flip side, when intent signals show a growing interest in adjacent solutions or use cases, that’s your chance to expand the account. 

Whether it’s an additional product module, a usage tier upgrade, or a cross-sell, intent gives you the behavioral context to pitch the right solution at the right time.

Signal Type	Expansion Indicator
Surging interest in adjacent topics	New needs evolving in their business
Content consumption on advanced features	They’re outgrowing current setup
Job postings in relevant departments	Scaling and adding headcount (need for more seats)
More stakeholders from the same account	Cross-functional team interest
Product usage spikes	High engagement = upsell readiness

Expansion Opportunity Example:

A customer using your CRM’s basic email module begins researching “marketing automation platforms” and “lead scoring models.” Their product usage report shows increased online activities in lead segmentation.

Action:

Sales or CS sends a personalized email:

“Saw your team exploring advanced automation strategies — want to explore how our premium plan can support this with native lead scoring and automated journeys?” 

This results in an upsell conversation triggered by signal intelligence and not guesswork.

Recommended → How to Use Intent Data for B2B Sales and Marketing

Demandbase Helps You Spot Interest. And Close It.

You don’t have a “we need more data points to enrich our leads” problem. 

In fact, you’re sitting on more data than you can use—ad clicks, CRM activity, social media mentions, product usage… it’s all there. 

But that’s the problem — it’s too much. Too many signals, platforms, and dashboards telling you different stories. And none of them are telling you what to do next.

That’s because your system isn’t built to work together—it’s built to collect.

We understand this, and we’ve seen it happen in the best teams, at the best companies. 

So we built Demandbase to do something different. 

Instead of ‘more data’, you get orchestration, so the data you already have finally works together.

From Anonymous Signals to Account Wins—Demandbase Does It All

Lindsay Hasz, Director of Insights and Optimization at SAP Concur, puts it like this —

“Demandbase allowed us to create segments based on journey stage combined with our own first-party behavioral data”

Read Case Study → SAP Concur Increases Funnel Velocity by 4X Using Journey Stages to Personalize Web Experiences

But enough about others, here’s what it means to use Demandbase: 

• You stop wasting time on accounts that aren’t moving. Demandbase shows you exactly which accounts are actually researching, actively surging, or consuming competitor content. You no longer rely on form fills or assumptions—you know who’s in-market, and who’s not. 
• You get one unified view of every account across all platforms. Sales sees what marketing sees. Marketing sees what sales is acting on. Demandbase pulls in behavior from ads, web visits, third-party intent, CRM activity, and product usage into one account-level view—so your GTM team stops flying blind and starts working in sync. 
• You personalize campaigns based on what buyers are already thinking about. Why send a generic nurture when you know the account is researching “SOC 2 automation” or “data warehouse tools”? Demandbase lets you match content and messaging to the exact topic or competitor they’re engaging with. 

• You alert sales at the perfect moment. When an account surges in intent, visits your pricing page, or reads competitor comparisons, Demandbase triggers an instant alert to your reps. It also includes the context they need to start a meaningful conversation.
• You turn anonymous activity into a qualified pipeline. Instead of guessing who’s behind the traffic spike or paid campaign click, Demandbase helps you map intent and engagement back to real accounts—even before they self-identify.

That’s the difference Demandbase makes.

Already a Demandbase user? Reach out to your account team and ask about our Intent Audit. This service consists of analyzing your existing keywords across historical pipeline to highlight and provide insight into which keywords are correlated to pipeline generation. In addition, net new relevant keywords related to your keyword set topics are identified to help you ensure you aren’t missing any valuable in-market signals.   Intent’s Just Noise—Unless You’ve Got Demandbase →