Intent Data Showdown: Company Surge vs. Topic Signals
A data-driven comparison of Bombora's Company Surge® and general topic-level intent signals for B2B marketing, updated for 2024 methodologies.
In 2024, the primary difference between Bombora's Company Surge® and topic-level signals is the baseline methodology. Company Surge® identifies intent by comparing a company's recent research activity on a topic against its own 12-week historical baseline, flagging statistically significant increases. This differs from generic topic-level data, which often just notes content consumption without historical context. Bombora's model uses a Data Co-op of over 5,000 B2B publisher sites to power its analysis.
TL;DR
- Bombora's Company Surge® score is calculated by comparing an account's topic research over the last 3 weeks to its historical 12-week baseline.
- A Surge Score of 60 or higher is considered a significant spike, indicating an account is actively in-market.
- Bombora's Data Co-op consists of over 5,000 publisher and brand sites, with 86% of the data being exclusive.
- The most popular use case for B2B intent data is digital advertising (67%), followed by market intelligence (62%) and lead generation (57%).
- The B2B intent data market is projected to grow from $4.49 billion in 2026 to $20.89 billion by 2035.
Defining the Signals: Company Surge® vs. Topic-Level Intent
Bombora's Company Surge® provides a nuanced view of B2B buying intent by measuring a company's research activity against its own historical behavior, not against an industry average. This model identifies statistically significant increases in content consumption, flagging accounts that are abnormally interested in a specific topic. The signal is generated by comparing the most recent three weeks of research activity to a 12-week historical baseline for that specific company. A Company Surge® Score of 60 or higher indicates that an organization is demonstrating a meaningful spike in research, suggesting it has moved from passive interest to active evaluation. This patented methodology, which powers products like Bombora Company Surge® Q3 2024, is designed to filter out the noise of everyday content consumption and pinpoint accounts that are genuinely in-market. The data is sourced from a cooperative of nearly 6,000 B2B publisher and brand websites, where anonymized, consent-based behavioral data is shared and analyzed. This baseline-centric approach allows marketing and sales teams to prioritize accounts with precision, focusing on organizations showing a recent and unusual change in their research patterns rather than just a high volume of activity.
Topic-level intent signals, in their more generic form, operate on a fundamentally different and broader principle than the baseline-driven model of Company Surge®. This type of intent data typically indicates that an account has engaged with content related to a specific subject, such as 'cloud security' or 'account-based marketing,' without the crucial context of historical behavior. For example, a large enterprise might always have a baseline level of research on cybersecurity, and a simple topic-level signal might flag this consistent activity, creating a false positive. It answers the question of whether a company is active on a topic, but not whether that activity is unusual or new. This approach often relies on aggregating data from publisher networks, ad-bid streams, and other third-party sources to note content consumption. While valuable for broad market analysis, it lacks the diagnostic power to distinguish between passive education and an active buying journey. Without a historical baseline for comparison, sales and marketing teams may receive a list of accounts showing interest, but they lack the critical insight to know which of those accounts are truly accelerating their research and are therefore more likely to be entering a purchasing cycle.
The foundation of Bombora's analytical power is its proprietary Data Co-op, a unique asset comprising nearly 6,000 B2B publisher and brand websites that share anonymized, consent-based behavioral data. This cooperative model, which Forrester has called 'the gold standard for account-level intent data feeds,' provides the massive dataset required to establish reliable research baselines for millions of companies. Members of the co-op contribute data on content consumption, and in return, they gain insights into their own audiences. This symbiotic relationship ensures a steady flow of high-quality, privacy-compliant data; in fact, 86% of the signals are shared exclusively with Bombora for the purpose of deriving intent. The data collected includes page views, downloads, and engagement metrics like scroll velocity and dwell time, which are then mapped to a taxonomy of over 25,300 B2B topics. This process allows Bombora to identify which company is showing interest without relying on personal information, making the data stream compliant with regulations like GDPR and CCPA. The health and diversity of this co-op are critical, with traffic from specialty publishers remaining steady even as broadscale news sites see declines, ensuring the signals remain robust and representative of the B2B ecosystem.
| Feature | Bombora Company Surge® | Generic Topic-Level Intent | Business Implication |
|---|---|---|---|
| Core Methodology | Compares recent (3-week) topic research against a company's own historical (12-week) baseline. | Flags any content consumption on a topic, without historical comparison. | Surge® identifies abnormal interest, reducing false positives and focusing teams on accounts with changing behavior. |
| Signal Nuance | A 'Surge' indicates a statistically significant increase in research intensity. | Indicates general interest or engagement with a topic. | Provides a clear trigger for sales outreach, separating active evaluation from passive research. |
| Scoring Model | A score of 0-100, where 60+ signifies a meaningful spike over the baseline. | Often lacks a standardized scoring model or may use simple volume metrics. | Enables quantitative prioritization; teams can focus on accounts with scores of 60, 70, or higher. |
| Data Source | Exclusive B2B Data Co-op of nearly 6,000 consent-based publisher and brand sites. | Varies widely; can include publisher networks, ad bidstreams, or scraped data. | Co-op data is generally higher quality, privacy-compliant (GDPR/CCPA), and more defensible. |
| Primary Use Case | Prioritizing a known list of target accounts for sales and marketing activation. | Broad audience discovery and general market analysis. | Ideal for account-based marketing (ABM) where the goal is to find in-market buyers within a target account list. |
| Data Output | Account-level surge data, identifying which company is surging on which topics. | Account-level topic interest, often without intensity or historical context. | Focuses outreach on the right company, with the specific topics providing context for messaging. |
Bombora's Data Cooperative: The Engine Behind Company Surge®
The engine driving Bombora Company Surge® in 2024 is its vast Data Cooperative, a collective of nearly 6,000 B2B publisher and brand websites. This extensive network processes billions of content consumption events monthly, creating a detailed tapestry of B2B research behavior. The sheer scale of this operation, built over a decade through direct, consent-based relationships with media partners, allows Bombora to capture signals across a wide spectrum of industries and company sizes. Unlike data sourced from bidstream ad placements, which can lack context, the co-op model provides a holistic view of engagement, tracking interactions with gated content, paywalled articles, and event registrations. This direct access to publisher data, as detailed in Bombora's 2024 Data Cooperative analysis, is foundational to establishing the historical baselines that make Company Surge®'s anomaly detection possible, moving beyond simple keyword tracking to measure true research engagement. The cooperative's structure, which includes thousands of influential B2B publishers, provides a granular view of the buyer's journey from initial awareness to late-stage solution comparison.
A critical differentiator for Bombora's Data Cooperative is the exclusivity of its data; 86% of the signals processed are shared exclusively with Bombora for the purpose of deriving intent. This high percentage of proprietary data, a figure consistently highlighted in Bombora's 2024 documentation, means that competing intent providers do not have access to the same raw material, giving Bombora a unique vantage point on market-wide research trends. This exclusivity prevents the signal degradation and noise common in more commoditized data sources, such as those relying heavily on public bidstream data. The result is a more reliable and distinct dataset that powers the Company Surge® algorithm, which compares recent research activity to a historical 12-week baseline to identify statistically significant interest. This methodology, outlined in resources like the Bombora Co-op Resource Center, ensures that an identified "surge" represents a genuine change in a company's research intensity, rather than just a fleeting interaction with a keyword. This protected, high-fidelity data environment is what allows sales and marketing teams to trust the signals for prioritizing accounts and personalizing outreach with confidence.
Bombora's analytical precision is further enhanced by a sophisticated taxonomy that has grown to include over 25,300 topics as of the 'Quay' taxonomy release. This classification system moves far beyond simplistic keyword matching by employing Natural Language Processing (NLP) and machine learning models that have been trained for over a decade. These advanced AI models analyze the context of content, allowing them to differentiate between homonyms, such as 'Apple' the company versus 'apple' the fruit, and understand the true subject matter of a webpage. This contextual understanding is crucial for accurately mapping billions of monthly research events to specific business interests and buying journeys. As detailed in Bombora's methodology, this AI-driven classification filters out irrelevant noise and ensures that the intent signals captured are genuinely related to B2B products, services, and challenges, providing a much clearer picture of a company's needs than keyword scraping ever could. The taxonomy is continuously updated to reflect new market trends and technologies, ensuring its ongoing relevance.
Despite industry-wide shifts driven by AI search trends, the signal quality from Bombora's Data Cooperative has proven remarkably durable, particularly within niche B2B sectors. According to Bombora's analysis of its publisher network, traffic from specialty B2B publishers within a static control set grew 9% in the second half of 2025 compared to the same period in 2024 (H2 2024). This resilience indicates that for complex, specialized topics, B2B buyers continue to rely on in-depth content from trusted, expert publishers rather than high-level AI-generated summaries. While broader news sites have seen traffic declines, the stability and growth in these specialty areas underscore the enduring value of the co-op's data sources for uncovering deep-funnel purchase intent. This finding, published in a 2026 report titled 'Our view across the Bombora Data Co-op', suggests that the cooperative's diverse and specialized publisher base provides a future-proofed foundation for intent signal collection, ensuring that Company Surge® continues to identify meaningful research behavior even as content discovery patterns evolve.
Use Case Comparison: When to Use Surge vs. Broad Topic Data
Broad, topic-level intent data is most effective for top-of-funnel (TOFU) activities where the goal is casting a wide net for market intelligence and audience discovery. This type of data, which tracks general content consumption across the web, allows marketers to identify a large universe of potentially interested accounts without the immediate need for signs of active buying behavior. It helps teams understand market trends, segment audiences, and create targeted awareness campaigns based on the topics potential customers are researching. For example, a company can use broad topic signals to discover new market segments or previously unknown accounts showing baseline interest in a category. According to Forrester's Q1 2023 Global B2B Intent Data Survey, one of the most common benefits users report is increased response rates from outbound marketing, a classic TOFU activity. This approach powers initial engagement by aligning content and advertising with early-stage research themes, effectively warming up a large audience before they demonstrate the specific, spiking behavior that solutions like Bombora's Company Surge® are designed to detect.
For mid-funnel (MOFU) account-based marketing (ABM) execution, Bombora's Company Surge® provides the necessary precision to prioritize accounts that have moved from passive interest to active research. Unlike broad data, Company Surge® establishes a 12-week historical baseline of content consumption for each company and flags statistically significant increases, or 'surges,' in research intensity. A Company Surge® score of 60 or higher indicates an account is actively consuming content on a topic at a much higher rate than its norm, signaling it is genuinely in-market. This methodology is crucial for ABM, where the goal is to focus resources on a select list of high-value accounts. As noted in The Forrester Wave™: B2B Intent Data Providers, Q2 2023, leading providers excel at identifying these active buying signals, which are essential for prioritizing outreach. By leveraging the patented models of a solution like Bombora Company Surge® Q4 2024, marketing and sales teams can confidently build target lists for campaigns, ensuring they engage accounts that are demonstrating quantifiable buying intent, not just ambient interest.
At the bottom of the funnel (BOFU), sustained, high Company Surge® scores signal that a buying decision is imminent and can trigger direct sales outreach. When an account shows a high Surge Score across multiple related topics for several consecutive weeks, it indicates a buying committee is conducting its final evaluation. This pattern, often tracked as 'Weeks Surging,' is a powerful indicator for sales teams to prioritize follow-up and personalize their final pitch based on the specific topics being researched, such as competitor comparisons or pricing pages. This same mechanism is highly effective for customer marketing and churn prevention. According to a survey by Ascend2, only 32% of B2B marketers currently use intent data to prevent churn, highlighting a significant opportunity. By monitoring an existing customer's Surge data, a company can receive an early warning if that account begins actively researching competitor solutions. This allows customer success teams to intervene proactively, address potential dissatisfaction, and reinforce value before the account is lost, turning intent data into a critical tool for both acquisition and retention.
| Funnel Stage | Primary Use Case | Recommended Data Type | Key Metric / Signal | Example GTM Action |
|---|---|---|---|---|
| Top-of-Funnel (TOFU) | Market intelligence & audience discovery | Broad Topic-Level Data | General topic consumption, audience-level trends | Launch broad awareness campaigns and segment new potential markets. |
| Mid-Funnel (MOFU) | ABM campaign prioritization | Bombora Company Surge® | Company Surge® Score > 60, number of surging topics | Prioritize accounts for a targeted, multi-channel ABM campaign. |
| Bottom-of-Funnel (BOFU) | Sales opportunity acceleration | Bombora Company Surge® | Sustained high Surge Score, 'Weeks Surging' > 1, competitor topic surge | Trigger direct sales outreach with personalized messaging about pricing or comparisons. |
| Customer Marketing | Churn risk identification | Bombora Company Surge® | Existing customer surging on competitor or problem-related topics | Proactive outreach from customer success to reinforce value and address issues. |
| Post-Sale / Expansion | Upsell & cross-sell opportunities | Bombora Company Surge® | Existing customer surging on topics related to adjacent products/services | Introduce new features or complementary solutions that align with research behavior. |
The Limits of Intent: Why Signals Are Not Proof of Purchase
Intent data's primary function is prioritization, not as definitive proof of an impending purchase. A surge in research activity indicates exploration, not a confirmed commitment to buy. Most intent signals reflect early- to mid-stage research as buying groups validate their options, a phase that precedes direct vendor engagement. In fact, most intent marketing focuses on this early research activity, which signals exploration rather than confirmed B2B buying intent. This distinction is critical; treating a research spike as a bottom-of-funnel lead often leads to premature outreach that creates friction rather than accelerating a deal. According to Forrester's 2024 State of Business Buying report, which surveyed over 16,000 global business buyers, 86% of B2B purchases stall during the process. This high percentage underscores that even accounts showing strong signals face internal hurdles, budget constraints, and complex decision processes that can halt momentum. Effective teams use intent signals to inform their account-based marketing strategies, deciding which accounts to monitor and what content to develop, rather than triggering an immediate sales call.
The utility of intent data is further constrained by its typical scope, which is at the account level, not the contact level. An alert from a system like Bombora Company Surge Q4 2024 might indicate that a specific corporation is researching “cloud computing,” but it cannot specify if the research is driven by a junior analyst for a report or the Chief Technology Officer for an imminent migration. This ambiguity forces sales teams into a guessing game, potentially misaligning their messaging by sending technical documents to a procurement officer or pricing to an engineer. This limitation is significant when considering that, on average, 13 people across multiple departments are involved in a buying decision, according to Forrester's 2024 research. Without knowing the specific individuals driving the research, outreach becomes inefficient. While account-level data helps narrow the field of target companies, it leaves sales development representatives to guess which of the many contacts within that account to engage, a process that often yields low reply rates.
First-party intent data, gathered from activity on a company's own website and marketing channels, provides the most accurate signal of interest but captures only a fraction of the buyer's journey. According to Gartner research from 2024, B2B buyers spend only 17% of their total purchase journey meeting with potential suppliers, meaning the vast majority of their research happens on third-party sites. This independent research phase, which includes engaging with peer review platforms, professional communities, and AI-assisted tools, is where buyers often form their vendor preferences before ever making direct contact. Relying solely on first-party data means missing the crucial early stages of consideration. This is the gap that third-party intent data from providers like Bombora, sourced from a cooperative of thousands of B2B publisher sites, is designed to fill, offering a window into the 80% of the journey that happens off-site.
The challenge of demonstrating clear returns on marketing investments is a persistent issue, a problem that data-driven signals aim to address. For instance, the B2B events industry has historically struggled with attribution. A 2026 survey of 841 professionals for the State of B2B Event Marketing report by Outcomes Rocket found that 68.9% have reported an event ROI figure they did not fully trust, highlighting systemic weaknesses in connecting event activity to sales outcomes. This difficulty in proving ROI, where only 39.2% of respondents could say they tag every conference lead to its source, mirrors the broader marketing challenge that intent data seeks to solve. While a 2026 Bizzabo report noted that the number of organizers struggling to prove event ROI fell from 70% to 40% year-over-year, the improvement was linked to better data integration, not a fundamental change in the events themselves. Intent data offers a scalable way to link pre-purchase activity to outcomes, providing a quantifiable signal that, while not perfect, is often more reliable than traditional metrics for justifying marketing spend and directing sales focus.
Activating Intent Data in 2024: From Report to Revenue
Activating intent data in 2024 begins with seamless platform integration, which is rapidly lowering the barrier to entry for many B2B organizations. A pivotal development in this space is HubSpot's native inclusion of Bombora Company Surge® data within its Buyer Intent product as of August 2026. At no additional cost, HubSpot users in Marketing Hub and Sales Hub can now access signals based on up to 12 auto-selected Bombora topics, which are configured based on the user's website and existing research settings. While this is a capped tier compared to a direct Bombora contract, it provides a powerful, genuinely free starting point for identifying which target accounts are intensifying their research. This democratization of high-quality intent data means that even teams without dedicated data budgets can begin to prioritize outreach and segment accounts based on active buying signals. The integration works by updating the HubSpot database weekly, allowing teams to incorporate Company Surge® data directly into account scoring, workflows, and audience segmentation to focus on accounts most likely to convert. This shift from siloed data tools to embedded platform capabilities marks a significant step in making intent-driven strategies accessible to the broader market.
The availability of high-fidelity intent signals necessitates a fundamental overhaul of traditional sales playbooks, moving organizations from generic MQL-based criteria to dynamic, intent-based lead handoffs. Relying solely on standard lead scores is no longer sufficient; instead, a spike in Company Surge® activity for a target account should trigger a distinct and immediate engagement plan. According to Forrester's Q1 2023 Global B2B Intent Data Survey, over 85% of companies using intent data have achieved business benefits, with the most common being increased response rates from outbound marketing and more successful sales prospecting. A successful playbook differentiates engagement based on signal intensity and context. For example, an account surging on broad, top-of-funnel topics might be routed to a marketing nurture stream with relevant content, whereas an account showing intent for bottom-of-funnel keywords like competitor comparisons or pricing should trigger an immediate alert for sales development representatives (SDRs) to initiate personalized outreach. This approach ensures that sales teams are not just chasing noise but are engaging accounts at the precise moment their research indicates a readiness to buy, transforming sales from a reactive process into a proactive, data-driven science.
Beyond sales prioritization, Company Surge® data provides a powerful engine for precision advertising and competitive intelligence, allowing teams to allocate budget with greater accuracy. The direct integration between Bombora and platforms like LinkedIn Campaign Manager enables marketers to push intent-based account lists directly into their advertising workflows as Matched Audiences. These audience lists can be set to refresh automatically each week, ensuring that ad spend is consistently focused on accounts that are actively in-market. This allows for highly personalized ad creative and messaging tailored to the specific topics an account is surging on, leading to better response rates. Simultaneously, this data serves as a critical competitive intelligence tool. By monitoring for surges on competitor brand names or product categories, organizations can identify accounts that are in an active evaluation cycle. This insight allows sales and marketing teams to tailor counter-messaging, highlighting specific differentiators and potentially displacing an incumbent or a competitor being considered. Using intent signals this way, as noted by software company Kibo, can identify prospects who are three times more likely to close.
Related reading
- see our 11 tactics for abm success at every funnel stage analysis
- see our 12 tips for selling to the c suite analysis
- see our 2024 b2b intent data benchmarks analysis
- see our account based marketing target list sizing how many accounts is too many analysis
Frequently Asked Questions
What is the difference between Bombora and 6sense?
The primary difference is that Bombora is a specialized intent data provider, whereas 6sense is a comprehensive account-based marketing (ABM) platform that includes intent data as one of its features. Bombora focuses on providing high-quality Company Surge® data that can be integrated into various existing marketing and sales stacks. In contrast, 6sense offers a full-funnel platform with predictive analytics, account identification, and advertising orchestration, often using Bombora's data as one of several inputs. Therefore, companies choose Bombora for its standalone, high-fidelity signals, while they choose 6sense for an all-in-one, orchestrated ABM solution.
How is a Bombora Company Surge® score calculated?
A Bombora Company Surge® score is calculated by comparing a company's recent content consumption on a specific topic against its own historical baseline. Bombora establishes a normal research pattern for every company on more than 13,000 topics by observing behavior across its Data Co-op. A score of 60 or higher indicates a statistically significant increase in research activity compared to this baseline, signaling a 'surge' in interest. This score, which ranges from 0 to 100, is determined by factors like the number of unique users from the company researching the topic and the intensity of their engagement.
Is Bombora data GDPR and CCPA compliant?
Yes, Bombora's data is designed to be compliant with major privacy regulations like GDPR and the CCPA. The data is collected through a consent-based Data Co-operative of over 5,000 B2B publisher websites, where members are responsible for obtaining user consent before data is collected. Although the process involves tracking behavior from devices, the data is aggregated and anonymized at the company domain level, not tied to personally identifiable information (PII). For regulations like CCPA, Bombora's data collection can be considered a 'sale' or 'sharing' of personal information, requiring publishers to provide opt-out mechanisms.
What are the top use cases for B2B intent data?
The top use case for B2B intent data is to identify and prioritize in-market accounts for sales and marketing outreach. According to a 2024 survey, the most popular applications include digital advertising (67%), market and competitive intelligence (62%), and lead generation (57%). Other common uses are to inform account-based marketing (ABM) strategies, personalize messaging, and support customer expansion or prevent churn. Ultimately, these use cases help align sales and marketing teams by focusing their efforts on accounts that are actively demonstrating buying signals.
How much does Bombora cost in 2024?
In 2024, Bombora's pricing typically starts around $30,000 per year for an entry-level Company Surge® package. Most mid-market companies can expect to pay between $40,000 and $80,000 annually, while enterprise-level deployments with extensive topic tracking and API access can exceed $100,000. Pricing is quote-based and depends on factors like the number of topics tracked, data volume, and integration complexity. It is important to budget for additional tools, as Bombora provides account-level signals and requires a separate contact data provider to identify specific individuals for outreach.
Last updated: October 2026