What are the types of B2B intent data?

There are three main types: (1) First-party intent data — signals from your own website (visitor identification, form fills, email opens, page visits); (2) Second-party intent data — signals shared by partner networks (review sites like G2 and Capterra, partner content); (3) Third-party intent data — signals aggregated from publisher networks, tracking research behavior across thousands of websites. Best results come from combining all three types.

How do intent data providers collect and aggregate signals?

Third-party intent data providers partner with publisher networks (news sites, industry publications, content hubs) and place tracking pixels across their network. When a reader researches topics related to specific product categories, those signals are recorded, aggregated by company and topic, and scored. Cursive processes 60B+ behaviors & URLs scanned weekly across 30,000+ commercial categories, updated weekly.

How do sales teams use intent data?

Common intent data use cases: (1) Prioritize outreach to accounts showing buying signals this week; (2) Trigger personalized outreach when a target account visits a competitor's review page; (3) Suppress outreach to accounts not showing any activity (focus budget on in-market buyers); (4) Identify new accounts in-market that aren't yet in your CRM; (5) Accelerate pipeline by alerting AEs when current opportunities show spikes in research activity.

Resource · Complete Guide 2026

What is B2Bintent data?

B2B intent data reveals when companies are actively researching products or services based on their online behavior. By tracking searches, content consumption, competitor visits, and review-site activity, it identifies organizations in an active buying cycle — so you engage them at the precise moment they are evaluating solutions.

In 2026, intent data has evolved from a niche enterprise capability into a core part of every modern B2B go-to-market strategy. According to Gartner, 70% of B2B marketers now use intent data in some form, up from just 28% in 2021 — driven by a simple shift in buyer behavior: decision-makers complete 70–80% of their research online before ever contacting a vendor. Cursive's Custom Audience is built directly on this signal, pairing intent data with visitor identification so revenue teams see who is interested and what they are researching.

How B2B Intent DataWorks

Raw behavior becomes an actionable buying signal through a three-stage pipeline.

Signal collection

Behavioral signals are captured across the web — searches, content consumption, review-site activity, and your own identified website visitors.

Processing & normalization

Raw signals are deduplicated, baselined against typical behavior per company, and mapped to topic taxonomies that match real buying categories.

Scoring & delivery

Signals become quantified intent scores. A pricing-page visit outweighs a blog read; clustered signals create a surge — then it ships to your tools.

Modern systems process billions of signals daily. A single buyer might search for “best CRM for mid-market,” read comparison articles on G2, visit three vendor sites, and download an analyst report in one week — each action captured, timestamped, and tied back to their company. Cursive's intent audiences segment companies by intent level automatically and route them to the right workflow.

Types ofIntent Data

Three types, defined by where the signal originates. The strongest strategies combine all three.

Most accurate

First-party intent

Signals from your own website, product, and content. Highest accuracy because you observe behavior directly — but visitor identification is required, since 95–98% of traffic is otherwise anonymous.

Mid-funnel

Second-party intent

Signals shared by a trusted intermediary like G2, TrustRadius, or an industry publisher. Strong indicator of active evaluation, limited to that platform's coverage.

Broadest reach

Third-party intent

Aggregated from web-wide data cooperatives. The widest coverage of early research activity, with lower precision — best used alongside first-party validation.

Attribute	First-Party	Second-Party	Third-Party
Source	Your website and app	Review sites, publishers	Web-wide data cooperatives
Accuracy	Very high (90%+)	High (80-90%)	Moderate (60-80%)
Coverage	Limited to your properties	Specific platforms	Broad web coverage
Signal Timing	Late-stage (evaluating you)	Mid-stage (comparing)	Early-stage (researching)
Resolution	Individual + company	Company	Company

First-party data is the most valuable but limited to your own properties — visitor identification is its foundation, because without it 95–98% of your website visitors stay anonymous.

Intent DataSources

Where signals come from determines which providers have the best data for your market.

Search behavior

Explicit queries like “best CRM for mid-market” signal clear research intent — among the strongest signals available.

Content consumption

Spikes in topic-specific reading across publisher networks reveal a company exploring a new category.

Competitor visits

Accounts engaging with competitor content are actively comparison shopping — ideal for displacement timing.

Review-site activity

G2, TrustRadius, and Capterra research is high-quality, late-stage intent from buyers actively shortlisting.

Social signals

LinkedIn engagement and group activity add context — weaker alone, valuable combined with other signals.

Identified visitors

Your own resolved website traffic is the highest-precision intent source, attributable to specific accounts.

IntentScoring

Turning raw behavioral signals into a quantified measure of buying likelihood.

How signals are weighted

Not all signals carry equal predictive value. A pricing-page visit is a far stronger signal than a blog read. Scoring models assign weights based on historical correlation with closed-won deals — demo requests and pricing views at the top, then competitor comparison content, feature pages, case studies, and general educational content below. Weights should be calibrated to your business using your own conversion data.

Scoring models

Rule-based models use predefined weights and thresholds — a pricing view might be worth 20 points, a blog visit 3. Machine-learning models learn which signal patterns predict conversion and adjust continuously, growing more accurate with enough historical data. Modern platforms, including Cursive, use hybrid approaches that combine a rule-based foundation with ML-driven optimization.

Thresholds and surge detection

A “surge” occurs when an account's research activity on a topic significantly exceeds its normal baseline in a defined window. If a company usually generates 5 content signals a week but suddenly produces 25, that 5x jump is a surge. Relative change matters more than absolute volume — a construction firm suddenly reading tech content shows intent that a tech firm reading tech content does not.

UseCases

The most impactful ways revenue teams put intent data to work.

Sales prioritization

Reps work accounts showing active buying signals first. Intent-flagged accounts are ~2.5x more likely to convert than cold outreach.

ABM targeting

Concentrate ad and campaign budget on in-market accounts for 40–60% higher engagement and lower cost per opportunity.

Content personalization

Tailor the on-site experience to what a visiting company is researching, lifting conversion 15–30%.

Competitive intelligence

Get alerted when key accounts research a competitor, then reach out with differentiated messaging in time.

Churn prevention

Surface customers researching alternatives early so CS can intervene — teams report 20–30% better net retention.

Pipeline acceleration

Spot renewed research activity on open opportunities and time the next touch to a real moment of interest.

Accuracy andQuality

Intent data is only as good as its accuracy. Know what affects it before you trust it.

Signal decay

Intent signals have a shelf life. A company researching CRMs three months ago may have already bought. Signals are most predictive within the first 7–14 days, moderately useful within 30, and largely unreliable beyond 60 — which is why real-time or near-real-time delivery matters, and why weekly-refresh feeds beat monthly batches.

False positives

False positives flag an account as in-market when it is not — caused by employees doing competitive research, analysts and journalists, students, or bots. Quality providers use bot detection, role-based filtering, and multi-source cross-referencing to reduce them, but expect a 15–30% false-positive rate even with top-tier data.

Validation methods

Cross-reference with first-party data: validate third-party signals against your own visitor data and CRM records
Track predictive accuracy: measure what share of intent-flagged accounts enter pipeline within 90 days
A/B test outreach: compare intent-driven versus non-intent conversion to quantify the signal's value
Feedback loops: have reps report when signals were accurate to continuously improve scoring
Multi-source validation: require signals from multiple sources before flagging an account

ImplementationGuide

Three phases: choose a provider, integrate your tools, and operationalize the workflow.

Phase 1: Choosing a provider

Evaluate providers on the criteria that matter for your business: types of intent data offered, topic-taxonomy coverage for your industry, geographic reach, integration capabilities, and pricing model. Request sample data for your target accounts before committing. Cursive's free audit shows you intent data for your actual website visitors before you buy.

Phase 2: Integration

Connect the intent feed to the tools your team already lives in — CRM (Salesforce, HubSpot), marketing automation, sales engagement, and ad platforms. The goal is to make intent data visible and actionable where reps work, not in a separate dashboard they have to remember to check. Cursive delivers your weekly audience straight to a Google Sheet that syncs across 200+ tools.

Phase 3: Workflow setup

Define what happens at each intent level. High-intent accounts (surging on your category, visiting your site, engaging competitors) trigger immediate outreach and targeted ads. Medium-intent accounts enter nurture and ABM programs. Low-intent accounts are monitored until signals strengthen. Automating these paths ensures consistent follow-through and maximum ROI. Pair intent with a fresh weekly Custom Audience so your team always has new in-market contacts to action.

ProviderComparison

How the leading options compare across the criteria that matter most in 2026.

Provider	Intent Types	Visitor ID	Pricing Model	Best For
Cursive	First + third-party	Yes (40–60% deterministic)	Self-serve, $197/mo	Lean B2B GTM teams
Bombora	Third-party (co-op)	No	Annual data feed	Enterprise data teams
6sense	First + third-party	Limited	Enterprise license	Large ABM programs
G2	Second-party (review site)	No	Per-category subscription	Competitive intelligence
TrustRadius	Second-party (review site)	No	Per-category subscription	Enterprise tech buyers

For a detailed look at how Cursive stacks up against 6sense, see our 6sense vs. Cursive comparison, or explore how intent data feeds the Custom Audience.

Frequently AskedQuestions

What is B2B intent data?

B2B intent data is information that reveals when companies or individuals are actively researching products, services, or topics related to a potential purchase. It is derived from online behavioral signals such as web searches, content consumption, review site visits, and competitor research. Intent data helps sales and marketing teams identify prospects who are in an active buying cycle.

What is the difference between first-party and third-party intent data?

First-party intent data comes from your own digital properties, such as your website, app, or email campaigns. Third-party intent data is collected from external sources across the broader web, including content publishers, review sites, and ad networks. First-party data is more accurate but limited in scope, while third-party data provides broader coverage but may have lower precision.

How accurate is B2B intent data?

Accuracy varies by source and methodology. First-party intent data from your own website is highly accurate because you directly observe the behavior. Third-party intent data ranges from 60-85% accuracy depending on the provider and validation methods used. The best results come from combining multiple intent data sources and validating signals against your CRM data.

How do you use intent data for sales prospecting?

Sales teams use intent data to prioritize outreach by focusing on accounts showing active buying signals. When a target account surges on topics related to your solution, reps can reach out with timely, relevant messaging. This approach increases connect rates by 2-3x compared to cold outreach because you are contacting prospects when they are actively evaluating solutions.

What are intent data signals?

Intent data signals are specific behavioral actions that indicate purchase interest. Common signals include searching for solution-related keywords, reading product comparison articles, visiting competitor websites, downloading industry reports, engaging with review sites like G2 or TrustRadius, and repeatedly visiting your pricing page. Each signal type carries a different weight in predicting buying intent.

How much does B2B intent data cost?

B2B intent data pricing varies widely. Standalone intent data feeds from legacy providers like Bombora typically cost between $25,000 and $100,000 per year. Cursive takes a different approach: intent data powers our Custom Audience, a fresh weekly list of in-market buyers built to your ICP, for a flat $197/month. It is self-serve and month-to-month, with no annual contract or enterprise minimum.

Can intent data predict when a company will buy?

Intent data cannot predict the exact timing of a purchase, but it reliably indicates when a company is in an active research or evaluation phase. Companies showing intent signals are statistically 2-3x more likely to enter a buying process within 90 days compared to companies without intent signals. The more signals a company triggers, the closer they tend to be to a purchase decision.

How do you integrate intent data with your CRM?

Most intent data platforms offer native CRM integrations with Salesforce, HubSpot, and other major platforms. With Cursive, your weekly Custom Audience is delivered straight to a Google Sheet and syncs to 200+ tools, so in-market contacts land in your existing stack with no engineering work. Once connected, reps can prioritize their pipeline based on real-time buying signals.

RelatedResources

The technologies and strategies that work alongside B2B intent data.

Website Visitor Identification Intent Audiences Custom Audiences Cursive Platform Intent Data for B2B Software Intent Data for Technology

Put intent datato work

Cursive's Custom Audience turns intent signals into a fresh weekly list of in-market buyers built to your ICP — delivered to your sheet for a flat $197/mo, month-to-month, cancel anytime.