A data-backed comparison of surge vs. active intent for B2B pipeline, citing Bombora's 2024 framework and data on conversion rate lift.

According to Bombora's 2024 framework, using surge intent data can increase marketing conversion rates by up to 70%. Surge intent identifies early, account-level research spikes across a cooperative of over 5,000 B2B websites, signaling top-of-funnel interest. Active intent, by contrast, captures explicit, bottom-of-funnel buying signals like pricing page visits or demo requests from your own properties, indicating immediate purchase consideration. While surge data provides scale, active data provides high-precision signals from prospects ready to engage.

TL;DR

Bombora reports that marketing teams using surge intent data see up to 70% higher conversion rates.
6sense research from their 2025 Buyer Experience Report shows 80% of B2B deals are won by the vendor the buyer favored before contacting sales.
Platforms like 6sense and Demandbase that operationalize intent data typically cost between $50,000 and $150,000 per year.
Active intent signals, like a demo request, can have lead-to-opportunity conversion rates exceeding 10-15%, far higher than top-of-funnel surge signals.
Surge data coverage from providers like Bombora is weakest for SMB and local businesses, as the co-op data is primarily from enterprise-focused B2B publishers.

How Does Bombora Define and Measure 'Surge' Intent?

Bombora's Company Surge® methodology is built upon a vast, proprietary data cooperative that monitors content consumption across a network of over 5,000 B2B publisher and brand websites. [10] This cooperative structure provides a comprehensive view of the B2B web, capturing billions of content consumption events each month. [6] Unlike first-party data, which is limited to activity on a company's own digital properties, Bombora's approach aggregates consented research behaviors from a diverse ecosystem, with 86% of these signals being shared exclusively with Bombora for intent derivation. [5] The system uses natural language processing and AI-driven models to analyze this activity, mapping it against a continuously updated taxonomy of more than 25,300 business topics. [5, 7] This allows Bombora to understand the context and relevance of the content being consumed, moving beyond simple keyword matching to identify genuine research interest at the account level. The entire process is designed with privacy at its core, operating on a consent-driven basis that is compliant with GDPR and CCPA regulations. [5, 17]

A 'surge' is identified when a company demonstrates a statistically significant increase in research activity on a specific topic compared to its own historical baseline. Bombora's models establish this baseline by analyzing an account's content consumption over a 12-week period, creating a benchmark of its normal research behavior. [5, 9, 11] A surge event is triggered when the activity in the most recent three weeks shows a notable spike against this 12-week history. [5, 9] This change in behavior is quantified into a Company Surge® Score, which ranges from 0 to 100. According to the Bombora Company Surge® User Guide from January 2023, a score of 60 or higher indicates that a company is actively 'spiking' and is considered to be in-market for that topic. [4] This score is calculated using factors such as the number of interactions with a topic, the number of unique users from the company engaging with the content, topic relevancy, and the depth of content engagement, such as scroll velocity and dwell time. [4]

To ensure a strong and actionable intent signal, Bombora's best practices recommend requiring a surge on multiple related topics. A common threshold is to identify accounts that are spiking on at least three relevant topics, a filter that can be applied within the Company Surge® reporting tools. [4, 8] This multi-topic approach provides greater confidence that an account is engaged in a serious buying journey rather than casual research. The resulting intent data is delivered at the account level, not the individual contact level, which aligns with account-based marketing (ABM) strategies and respects privacy by not tracking personally identifiable information. [10, 17] This data is typically delivered to platforms like Salesforce or HubSpot on a weekly cadence, often refreshing over the weekend to provide sales and marketing teams with the most current signals for the week ahead. [11, 15, 17] This regular update cycle ensures that go-to-market teams can prioritize outreach and tailor messaging to accounts that are actively demonstrating purchase intent across the B2B web.

What Signals Constitute 'Active Intent' and Where Are They Found?

Active intent signals are definitive, high-value behavioral data captured directly from a company's own digital properties, such as its website, CRM, and product analytics. These first-party signals are the most reliable indicators of late-stage buying interest because they represent explicit actions taken by a prospect. For example, when a visitor repeatedly views a pricing page, they are actively evaluating the solution against their budget, signaling a shift from casual research to serious consideration. Similarly, actions like signing up for a product trial, requesting a demonstration, or downloading a technical case study indicate a user is moving down the funnel and investing time to understand how the product solves their specific problem. Unlike broader, top-of-funnel surge data, these interactions are not just about topical interest; they are concrete steps in a self-directed evaluation process. Analyzing this first-party data, such as tracking which features are most used during a trial or which pages are visited before a demo request, provides an un-filtered view of a prospect's priorities and pain points, making it an invaluable resource for sales and marketing teams to tailor their engagement.

Beyond a company's owned properties, second-party active intent signals are found on independent B2B software and service review platforms. Marketplaces like G2 and TrustRadius generate what is often called "downstream intent" data, which captures high-fidelity buying signals from prospects who are actively comparing vendors and solutions. When a buyer uses these platforms to read reviews, view product comparisons, or research alternatives to a specific competitor, they are demonstrating clear, lower-funnel intent. According to a 2021 guide from TrustRadius, this data is particularly valuable because it comes from an audience of in-market buyers, and some platforms can even provide insights into which competitors a prospect is evaluating. For instance, the G2 Buyer Intent product provides data on which accounts are viewing a company's profile, its competitors, and relevant product categories. This type of second-party data offers a crucial window into a buyer's evaluation process at the very moment they are making their selection, providing a highly qualified signal that is often second only to a company's own first-party data in terms of its predictive power.

A defining characteristic of active intent is that it is often tied to a known individual or a de-anonymized company, standing in stark contrast to the anonymous nature of most surge data. While a prospect may begin their research anonymously, active intent signals are frequently captured after a user has identified themselves by filling out a form, signing into a trial, or through the use of website visitor identification tools. Platforms like Leadfeeder (now part of Dealfront), 6sense, and Common Room specialize in this de-anonymization process, using techniques like reverse IP lookup and cookie matching to connect anonymous website traffic to specific company profiles. According to a 2026 analysis from Factors.ai, these tools can realistically match 30-75% of B2B website traffic to named accounts, turning a significant portion of the previously invisible "dark funnel" into actionable leads. This allows revenue teams to move beyond account-level guesswork and engage specific people. For example, a platform like Common Room's Buyer Intelligence aims to resolve every signal back to a real person, transforming a generic alert like "a company visited your pricing page" into a specific insight, such as "the VP of Revenue at Acme Corp, who recently joined from a current customer, just viewed your pricing page for the third time."

Crucially, by the time a prospect generates these explicit active intent signals, they have already completed a substantial portion of their buying journey independently. Research from 6sense's 2025 "Buyer Experience Report," which surveyed B2B buyers, indicates that buyers complete roughly 60% of their evaluation and research before ever engaging a vendor for the first time. A similar 2024 study from 6sense, based on a survey of 2,509 B2B buyers, found this figure to be closer to 70%, with 81% of buyers having already chosen a preferred vendor before speaking with any sales representative. This extensive, self-directed research phase means that when a buyer finally raises their hand by requesting a demo or starting a trial, they are not at the beginning of their journey; they are often in the final stages of validating a decision they have already mostly made. This reality underscores the importance of capturing and acting on active intent signals with speed and precision. The prospect is not looking for an introduction to the market, but for confirmation that your solution is the right choice to solve a problem they have already thoroughly defined.

Surge vs. Active Intent: A Side-by-Side Data Comparison

Surge data provides the broad, top-of-funnel coverage necessary to identify in-market accounts early in their buying journey, while active intent offers narrow, high-precision signals for converting prospects at the bottom of the funnel. Surge data, exemplified by products like Bombora's Company Surge®, is sourced from a vast cooperative of over 5,000 B2B websites, tracking anonymized content consumption to spot when a company's research on specific topics spikes above its historical baseline. [3, 4] This method provides a wide-angle lens on the market, flagging accounts that are just beginning to research a problem or solution category, often before they have engaged with any vendors directly. In contrast, active intent data is generated from first-party signals on a company's own digital properties, such as pricing page visits or demo requests, or from high-value third-party sites like G2. [2, 19] These actions signify explicit interest and a readiness to engage with sales, representing a much smaller, but more qualified, segment of buyers who have moved from anonymous research to active evaluation.

A foundational claim from Bombora is that marketing teams activating surge data can achieve up to a 70% increase in conversion rates compared to static account lists. [22] This performance lift is attributed to the data's ability to dynamically prioritize accounts based on real-time behavior. Instead of targeting a fixed list of ideal customers, sales and marketing teams can focus their budget and outreach efforts on organizations that are demonstrating active research interest right now. [4] The methodology behind Bombora's Company Surge® involves monitoring research activity across more than 25,300 topics and comparing an account's recent engagement over three weeks to a 12-week baseline to identify a statistically significant 'surge'. [1] This allows teams to engage accounts with relevant messaging while they are still in the early stages of defining their needs, resulting in higher engagement than campaigns targeting accounts with no verified, current interest. [22] This data-driven prioritization ensures that resources are allocated to accounts with the highest propensity to buy, fundamentally shifting teams from speculative outreach to informed engagement.

The strategic value of influencing buyers during the anonymous surge phase is underscored by findings in the 6sense 2025 B2B Buyer Experience Report, which surveyed nearly 4,000 B2B buyers. [13] The report found that 95% of winning vendors are already present on the buyer's 'Day One shortlist', which is formed well before the buyer makes direct contact with a sales team. [9, 11] This critical insight reveals that the majority of the decision-making process occurs during the top-of-funnel research phase that surge data is designed to illuminate. By the time a prospect generates an active intent signal, such as filling out a contact form, they have often already narrowed the field considerably. According to the same 6sense research, buyers delay direct contact with sellers until they are, on average, 61% of the way through their journey. [9] This makes early visibility through surge data essential; if a vendor is not part of the initial consideration set built during this independent research phase, their chances of winning the deal are drastically reduced.

Conversely, active intent data, while representing a smaller fraction of the total addressable market at any given time, delivers highly qualified leads that are primed for immediate sales engagement. Signals from sources like G2, a B2B software marketplace, capture high-value, bottom-of-funnel actions such as viewing competitor comparison pages or product pricing. According to an analysis by Dreamdata in October 2024, deals influenced by G2 signals were twice as valuable as those without, and 12% of all closed-won deals contained a G2 signal in the buying journey. [8] These signals are powerful because they represent explicit purchase consideration. For example, the same Dreamdata study found that a G2 'Comparison' signal, where a buyer directly compares two products, is 5.7 times more influential than a broader 'Category' signal, indicating a prospect moving from general research to vendor selection. [8] While surge data fills the top of the funnel, this high-precision active intent data is what allows sales teams to focus their efforts on accounts that are not just in-market, but are actively evaluating a purchase now, leading to more efficient pipeline conversion.

Attribute	Surge Intent (e.g., Bombora)	Active Intent (e.g., G2, Website Forms)	Primary Business Use Case
Signal Source	Aggregated, anonymized research across a cooperative of 5,000+ B2B publisher websites. [3]	Direct actions on owned properties (website, emails) or third-party review sites. [5, 19]	Identifying new in-market accounts and influencing early-stage research.
Funnel Stage	Top-of-Funnel (Awareness, Research)	Bottom-of-Funnel (Consideration, Decision)	Prioritizing accounts for demand capture and sales outreach.
Data Type	Account-level topic interest spikes measured against a historical baseline. [1]	Known contact-level actions (form fills) or account-level explicit actions (G2 comparisons). [19]	Timing marketing campaigns and personalizing sales conversations.
Audience Scale	Broad; covers the ~83% of the buying journey that happens before vendor contact. [24]	Narrow; covers the final ~17% of the journey when buyers engage vendors directly. [24]	Scaling ABM programs vs. converting hand-raisers.
Signal Implication	An account is beginning to research a problem or solution category.	A specific person or account is ready to evaluate vendors and make a purchase decision.	Building brand preference vs. closing near-term opportunities.
Lead Quality	Predictive; identifies potential future buyers based on research trends.	High-quality; signals explicit interest and readiness to engage with sales. [8]	Informing content strategy vs. generating Marketing Qualified Leads (MQLs).

How Do Platforms Like ZoomInfo and 6sense Operationalize Intent Data?

Revenue intelligence platforms like 6sense operationalize intent data by unifying multiple signal types into a predictive engine that scores account-level purchase readiness. The platform's 6AI engine processes trillions of daily data points from its Signalverse network, which includes first-party data from a client's own web properties, third-party surge data from partners like Bombora, and second-party review site data from G2 and TrustRadius. This multi-source approach allows 6sense to capture signals across what it calls the "Dark Funnel," which is the anonymous research activity that occurs before a prospect formally engages with a vendor. The platform's proprietary machine learning models then analyze these combined signals to classify accounts into distinct predictive buying stages, such as Awareness, Consideration, or Decision. This classification moves beyond simple lead scoring; it assesses the collective behavior of the entire buying group within an account to determine where they are in the purchasing journey. By integrating directly with CRM and marketing automation systems, 6sense uses these buying stage predictions to trigger orchestrated campaigns, alert sales teams to in-market accounts, and personalize messaging with high relevance.

ZoomInfo operationalizes intent data by layering its proprietary Streaming Intent signals on top of one of the industry's largest B2B contact and company databases. The platform collects intent from multiple sources, including its own network of publisher sites, third-party partnerships with review sites like G2, and, notably, from bidstream data. This bidstream data is captured from ad exchanges and reflects which companies are interacting with specific types of online advertisements, although some critics note this can lead to false positives from accidental clicks. ZoomInfo's core value proposition is combining these diverse signals with its massive, verified contact database, allowing teams to move directly from identifying an in-market account to engaging specific individuals. Its Streaming Intent feature, introduced to provide real-time alerts, notifies users the moment an account's research activity on a tracked topic spikes above its historical baseline. This is designed to give sales teams a critical timing advantage. According to a February 2025 analysis, while 52% of sales professionals have reported false positives with intent data generally, teams that validate ZoomInfo's signals against their own first-party CRM data see the best results. The platform also offers workflow automation that can trigger sales plays or update CRM records based on these intent signals.

The accessibility of intent data has broadened significantly, with platforms like HubSpot and Apollo.io embedding it directly into existing workflows for a wider user base. As of August 2026, HubSpot natively integrates Bombora's Company Surge® data, allowing users to track up to 12 intent topics without a separate Bombora contract. This integration surfaces account-level research spikes directly on company records within HubSpot's Marketing Hub and Sales Hub, enabling users to trigger automated workflows, segment audiences, and adjust lead scoring based on this third-party signal. For small and mid-sized businesses (SMBs), Apollo.io provides an even more accessible entry point by bundling intent data with its sales intelligence and engagement platform. Sourcing its signals from partners including Bombora and LeadSift, Apollo offers a limited number of intent topics based on subscription tier, with plans ranging from approximately $49 to $119 per user per month. The Basic plan ($49/mo) typically includes around three intent topics, while the Professional and Organization plans ($79-$119/mo) offer up to six. While not as deep as dedicated enterprise platforms, this model allows resource-constrained teams to leverage intent-informed prospecting within a single, cost-effective tool.

What Are the Documented Limitations and Costs of Intent Data?

The financial investment required to access high-quality intent data represents a significant barrier, with costs varying widely based on the platform's scope and data depth. For a standalone third-party data feed like Bombora Company Surge, median contract values begin around $25,000 to $30,000 per year for a basic package. [23, 26] However, this entry point often covers a limited number of research topics, and because Bombora provides only account-level signals, companies must budget an additional $15,000 to $40,000 for a separate contact data provider like ZoomInfo or Apollo to make the signals actionable. [16] More comprehensive Account-Based Marketing (ABM) platforms, which bundle intent data with predictive analytics and advertising orchestration, command a much higher price. According to 2026 data from procurement platform Vendr, the median annual cost for 6sense is approximately $62,440, while Demandbase's median is slightly higher at $68,591. [7] Enterprise-level contracts for these platforms frequently exceed $150,000, with some deals reaching $300,000 annually, not including mandatory implementation fees that can add another $10,000 to $50,000. [13, 15, 22]

A primary limitation of third-party surge data is its probabilistic and account-centric nature; it signals that a company is showing interest, not which specific individual is responsible. This is a structural aspect of how data co-ops like Bombora's work, which aggregate anonymized browsing behavior from a network of over 5,000 publisher websites. [9, 37] The resulting signal, often called a "Surge," indicates an abnormal spike in content consumption on a certain topic from a specific company, but it cannot pinpoint the buyer or buying committee. [37] This leads to a common frustration for sales development representatives (SDRs), who receive a notification that an account is researching "cloud security" but have no guidance on whether it was the CTO, a procurement officer, or an intern conducting a literature review. [9, 30] This ambiguity often results in what sales reps call "chasing ghosts," where outreach is directed at the wrong contacts or the prospect denies any active research, leading to wasted effort and low conversion rates from the raw signal. [28]

Accuracy and coverage remain persistent challenges for intent data providers, exacerbated by modern work trends and the inherent structure of data collection. The widespread shift to remote work has degraded the reliability of IP-based identification, a core mechanism for mapping anonymous web traffic to a specific company's office network. [33, 34] While some providers claim to have mitigated this, independent studies show IP-to-household linkage accuracy can be as low as 13%, creating a high potential for false positives. [39] Furthermore, the data co-op model, which powers providers like Bombora, is structurally biased toward large enterprises. The publisher network consists mainly of B2B media sites focused on enterprise-grade problems, resulting in poor signal coverage for small and mid-sized businesses (SMBs) or companies in niche local markets. [4] This means that if your ideal customers are not large corporations, the available universe of intent signals may be sparse, making it difficult to justify the significant financial investment. [23]

Vendor	Primary Data Type	Median Annual Cost (2024-2026 Est.)	Key Limitation	Ideal Customer Profile
Bombora	Third-Party (Co-op)	$25,000 - $60,000	Account-level signals only; requires separate contact data tool. [9, 16]	Marketing teams needing a raw topic-intent feed for a broader ABM stack.
6sense	Multi-Source (Predictive AI)	$62,440 - $100,000+	High cost and complexity; requires dedicated ops resources to manage. [15, 22]	Enterprise ABM teams with large budgets needing predictive account scoring.
Demandbase	Multi-Source (ABM Orchestration)	$68,591 - $150,000+	Expensive, with significant add-on costs for advertising and user seats. [1, 7]	Large B2B organizations focused on integrating intent with advertising and sales plays.
G2 Marketing Solutions	Second-Party (Review Site)	$22,000 - $32,000	Signal is limited to users researching on G2.com; less useful for non-SaaS. [6, 19]	B2B SaaS companies with an active presence on the G2 review platform.
ZoomInfo	Hybrid (Contact Database + Intent)	$33,500 - $50,000	Intent data is an add-on to a large contact database; signal quality can be secondary. [11, 16]	Sales teams that need a single platform for both contact data and basic intent signals.
Leadfeeder (by Dealfront)	First-Party (Website Visitors)	$1,188 - $4,788	Only identifies companies already on your website; no visibility into broader market research. [17]	SMB teams wanting an affordable way to identify and act on their own website traffic.

Frequently Asked Questions

What is the main difference between surge and active intent data?

The main difference is where the signal is captured and what it implies about the buyer's journey. Surge data, or third-party intent, tracks an account's research activity across a wide network of publisher websites, identifying an increase over their baseline to signal early-stage, top-of-funnel interest. [19, 29] Active intent, or first-party intent, is behavior captured on your own website, such as visiting the pricing page or requesting a demo, which signals late-stage purchase consideration. [6, 31] While surge data provides broad coverage to find new in-market accounts, active data offers high-precision signals from prospects ready to engage. [19]

Is Bombora the only provider of surge intent data?

No, Bombora is not the only provider, but it is a foundational source whose data is resold by many other platforms. [18, 19] Bombora operates the largest B2B data cooperative with over 5,000 websites, making its Company Surge® data a category leader. [7, 30] However, companies like 6sense, Demandbase, and ZoomInfo offer their own aggregated third-party intent data solutions, often combining Bombora's feed with other sources like ad bidstreams or their own publisher networks. [5, 9, 18] Other notable providers that offer various forms of third-party intent include TechTarget, Intentsify, and DemandScience. [1, 7]

How much does B2B intent data cost?

B2B intent data pricing varies widely, from free entry points to over $150,000 annually for enterprise platforms. [2] Standalone surge data from a provider like Bombora typically starts around $25,000 to $30,000 per year, with mid-market contracts often landing between $50,000 and $100,000. [3, 4] All-in-one platforms that bundle intent with contact data and other features, such as 6sense or Demandbase, have a median annual cost of over $60,000. [12, 13] For smaller businesses, providers like Apollo.io and Dealfront offer more accessible entry points, including free tiers or plans starting under $100 per month. [1]

How accurate is surge intent data?

Surge intent data is probabilistic, meaning it indicates elevated research activity rather than a guaranteed intent to buy. [6] One independent analysis measured Bombora's precision at 81%, suggesting about one in five surging accounts may not have genuine purchase intent. [17] The accuracy is limited because signals are tied to an account (a company's IP address), not a specific person, and research can happen for many reasons besides a new purchase. [10, 26] To improve reliability, experts recommend validating surge signals by layering them with other data points, such as first-party website engagement or public trigger events, before acting on them. [16, 32]

Can I get intent data for small businesses?

Yes, several providers offer intent data solutions suitable for small businesses, though coverage can be a limitation. All-in-one platforms like Apollo.io and Lusha are often recommended for SMBs because they bundle Bombora-powered intent signals with contact data at an affordable price point. [5, 6] Dealfront also offers a free plan to identify companies visiting your website, which is a strong starting point for smaller teams. [1] However, the effectiveness of third-party surge data can be weaker for niche industries or smaller companies that do not generate enough research signals across publisher networks to register a reliable surge. [15, 30]

Last updated: October 2026

Surge vs. Active Intent: A Data-Backed B2B Comparison