Analyzes 2024 intent data ROI benchmarks from Salesforce and Bombora studies. See how users achieve higher pipeline lift and conversion rates vs. non-users.

Teams using intent data in 2024 see significant ROI, with a Forrester Total Economic Impact study showing one Bombora customer achieving a 342% ROI and a 15% revenue growth from increased conversion and sales velocity. Intent-triggered outreach converts to meetings at 10-14%, a substantial lift over the 2-5% rate for purely cold outreach. Gartner's 2024 research underscores the need for early engagement, finding buyers spend only 17% of their time with vendors, making intent data critical for entering the conversation earlier.

TL;DR

A Forrester TEI study found a Bombora customer realized a 342% ROI over three years, with a net present value of $4.2 million.
Intent-triggered outreach boosts lead-to-meeting conversion rates to 10-14%, compared to just 2-5% for traditional cold calling.
Gartner's 2024 research shows B2B buyers spend only 17% of their purchasing journey in direct contact with vendors.
A financial services client attributed an $800 million pipeline contribution to Bombora-powered insights within three months.
Despite 91% of B2B marketers using intent data, only 24% report exceptional ROI, highlighting an activation gap.

What Is Intent Data and Why Does It Matter in 2024?

Intent data consists of behavioral signals indicating that a company is actively researching a solution, a stark contrast to static firmographic or demographic data. While firmographics describe a company's attributes like industry and size, intent data captures its real-time digital behavior, such as the topics employees are researching, the content they consume, and their engagement with competitor websites. For example, signals can include multiple employees from one company visiting CRM comparison pages, downloading whitepapers on sales automation, or searching for keywords related to a specific business problem. These actions are collected from first-party sources, like a company's own website and email campaigns, and third-party sources, which aggregate data from a wide network of publishers and platforms. Leading providers like Bombora, through its Data Co-op, and 6sense, with its Signalverse™, analyze trillions of these signals to identify which accounts are demonstrating heightened interest in specific topics, allowing revenue teams to focus their efforts on accounts that are genuinely in-market. This intelligence provides a critical layer of prioritization, helping teams understand not just who to target, but when and why.

The modern B2B buying process is overwhelmingly self-directed, making early visibility into an account's research essential for success. According to 2024 research from Gartner, B2B buyers spend only 17% of their total purchasing time in direct contact with all potential vendors combined. This means that for roughly 83% of the buying journey, prospects are forming opinions, defining requirements, and building their shortlist without any input from a sales representative. When a deal involves multiple vendors, an individual sales team may receive as little as 5% of the buyer's total attention. This limited window for influence occurs late in the process, after crucial decisions have already been made. The buyer's independent research phase, which includes consuming online content, consulting peer communities, and using AI-powered research tools, has become the primary arena where preferences are shaped. Without leveraging intent data to detect these early, anonymous activities, sales and marketing teams are effectively blind to the most formative part of the customer's journey, only entering the conversation after the competitive landscape is largely set.

The necessity for early engagement is stark, as buying decisions are often finalized long before a sales team is ever contacted. A global study detailed in the 6sense 2025 Buyer Experience Report, which surveyed over 4,000 B2B buyers, found that 94% of buying groups rank their preferred vendors before initiating any direct contact with sales. Furthermore, the vendor that is ranked as the favorite before this first contact goes on to win the deal 77% of the time. This data underscores a fundamental shift: sales conversations are now more about validating a pre-existing choice than persuading a neutral party. Reflecting the critical importance of gaining this early insight, the B2B buyer intent data market is experiencing explosive growth. According to market analysis from Roots Analysis, the market is valued at $4.49 billion in 2026 and is projected to expand at a compound annual growth rate (CAGR) of 16.62%, reaching $20.89 billion by 2035. This significant investment highlights an industry-wide consensus that understanding and acting on buyer intent is no longer a competitive advantage but a foundational requirement for revenue growth.

Benchmark: How Intent Data Lifts Pipeline Conversion Rates

Teams using intent data see a direct and measurable lift in pipeline conversion, validated by rigorous third-party analysis. A 2022 Forrester Total Economic Impact™ study commissioned by Bombora, for instance, documented how a large financial services firm achieved an 18% higher conversion rate by integrating Bombora Company Surge® data into its sales process. This improvement was not marginal; it contributed to an estimated $3.3 million in profit over a three-year period. The methodology involved prioritizing leads that showed active interest in monitored topics, allowing the sales team to engage prospects at the moment of peak relevance. This contrasts sharply with traditional models that rely on static firmographic or demographic data, which often fail to capture the critical element of timing. By identifying accounts in an active buying cycle, the firm could tailor messaging and allocate resources more effectively, leading to both higher conversion rates and a 30% increase in sales velocity. The study's findings, based on an interview with the firm's senior director of marketing data, underscore a core principle: entering the conversation when the buyer is already thinking about a problem is fundamentally more profitable than trying to create interest from a cold start.

The most dramatic conversion lift from intent data often occurs at the top of the sales funnel, where initial outreach is converted into qualified meetings. Industry benchmarks for 2024-2025 show that purely cold outreach, such as mass emails or untargeted calls, typically yields a lead-to-meeting conversion rate of only 2-5%. However, when outreach is triggered by intent signals, that rate jumps to 10-14%, representing a 2-4x improvement in efficiency. This lift occurs because the outreach is no longer an interruption but a relevant and timely suggestion. Top-performing teams take this a step further, achieving signal-to-meeting conversion rates of 15-22% by focusing on what are known as high-strength signals. These signals are not just single data points, like a lone whitepaper download, but a composite of behaviors: multiple individuals from the same account researching related topics, a surge in research intensity over a short period, or engagement with late-stage content like pricing pages or competitor comparisons. According to a 2026 analysis from OneAway, a well-tuned program should see an average of 10-18% signal-to-meeting conversion across all signals, making it a predictable and scalable source of pipeline.

Beyond initial meetings, intent data provides a significant advantage in later-stage pipeline conversions, particularly in opportunity-to-close win rates. The average B2B win rate for new business hovered around 20-21% in 2024, a figure that reflects the intense competition and cautious buying behaviors prevalent in the market. However, a starkly different picture emerges for expansion and upsell deals within existing customer accounts that are monitored with intent data. For these scenarios, opportunity-to-close win rates can reach 40-60%, more than double the average for new business acquisition. This substantial increase is driven by the ability to proactively identify and act on critical customer signals. For example, Bombora's platform can help identify customers who are researching competitors, signaling churn risk and creating an opportunity for proactive retention efforts. More strategically, it can reveal when a customer is exploring complementary solutions, allowing account managers to initiate a timely and highly relevant upsell or cross-sell conversation. This transforms the role of account management from reactive support to proactive value expansion, directly impacting revenue growth and customer lifetime value.

Outreach Method	Typical Lead-to-Meeting Rate	High-Performance Rate	Primary Success Driver	Data Source (2024-2026)
Cold Outreach (Email/Call)	2-5%	5-8%	Volume and persistence	Lunas Consulting, Martal Group
Standard Intent-Triggered Outreach	10-14%	~18%	Timing and topic relevance	Lunas Consulting, OneAway
High-Strength Signal Outreach	15-22%	>22%	Signal clustering and speed	OneAway
Warm Inbound Lead (Demo Request)	8-12%	>15%	Speed of response	Optifai
Referral/Warm Intro	15-25%	>25%	Trust and relationship transfer	Optifai
Expansion/Upsell (Intent-Based)	40-60% (Opp-to-Close)	>60% (Opp-to-Close)	Existing relationship and proactive timing	Lunas Consulting

Calculating the ROI: The Total Economic Impact of Bombora

A Forrester Total Economic Impact™ (TEI) study, commissioned by Bombora, quantified the significant returns of investing in Bombora's Company Surge® intent data, revealing a 342% return on investment (ROI) and a $4.2 million net present value (NPV) over three years for a representative customer. The TEI methodology involved a detailed financial analysis based on an interview with a key decision-maker at the customer organization. The study aimed to provide a framework for other B2B organizations to evaluate the potential impact of integrating Company Surge® data into their sales and marketing stacks. The subject of the case study was a large financial services organization with annual revenues of $22 billion. This firm's global marketing data team, which generated $295 million in revenue annually, was the initial user of the Bombora data. The impressive ROI calculation stems from benefits totaling $5.4 million over three years, weighed against costs of $1.2 million, with the investment paying for itself in under six months. These results underscore the substantial financial upside for enterprise-level companies that successfully operationalize account-level buying intent signals to drive efficiency and growth.

The financial services firm detailed in the Forrester TEI study achieved a 15% revenue growth by leveraging Bombora's data to enhance both sales conversion rates and velocity. This growth was not an abstract figure; it was the direct result of transforming the company's outbound sales motion. Previously reliant on low-yield cold calling, the sales team used Bombora's Company Surge® data to identify and prioritize accounts that were actively researching relevant topics. This shift allowed for timely, relevant outreach, leading to a conversion rate that improved progressively from 8% in the first year to 18% by the third year. The increased sales velocity, which contributed $1.6 million in profit over the three-year analysis period, was facilitated by automating lead scoring and integrating intent data directly into the sales platform, pushing high-priority leads to sales teams automatically. This strategic change moved the team from struggling for engagement to having highly productive conversations with interested prospects, fundamentally altering their pipeline generation.

A crucial aspect of the Forrester TEI study's 342% ROI calculation is the transparent accounting of the initial investment, which extended beyond Bombora's licensing fees. The financial services organization made a strategic decision to build a new, centralized database and analytical model, investing $2 million with a third-party customer experience firm for its development. The integration of Bombora's data represented 5% of this total development cost, highlighting that while intent data was a critical component, it was part of a broader data infrastructure project. Following the initial build, the organization brought the model management in-house, eliminating ongoing third-party costs. The total costs factored into the three-year NPV calculation amounted to $1.2 million, which included Bombora's fees and internal operational costs. This context is vital for other enterprises, as it demonstrates that the highest returns from intent data are often realized when it is integrated into a well-planned data strategy, rather than used as a standalone tool.

The value of Bombora's data ecosystem extends to publishers, who form the foundation of its consent-based data cooperative. A separate Forrester Total Economic Impact™ study, focused on data publishers, found that providing data to the cooperative could yield a 335% ROI over three years, with a net present value of $3.35 million. This return was driven by several key benefits identified in the study, which was based on the experience of a business news publication. The most significant quantifiable benefit was a 200% increase in cost-per-thousand (CPM) impressions, which was worth $2 million over three years, achieved by using Bombora's insights to prove audience value to advertisers. Furthermore, the publisher saw a 10% improvement in partner and campaign retention, contributing over $2.2 million in profit. These findings, detailed in a study titled “The Total Economic Impact™ of Bombora for Data Publishers”, demonstrate how participation in the data co-op creates a symbiotic relationship, enabling publishers to better monetize their audiences while providing the high-quality signals that B2B marketers use to drive their own growth.

How Different Intent Data Vendors Compare: Bombora vs. ZoomInfo

Bombora's Company Surge® product operates on a fundamentally different data collection model than many alternatives, centered on a proprietary, consent-based Data Cooperative of over 5,000 B2B publisher and brand websites. This co-op provides Bombora with exclusive data from 86% of its members, capturing billions of content consumption events which are then analyzed for intent. The core of its methodology involves establishing a 12-week historical baseline of research activity for every company-topic pair. A "surge" is identified only when an account's research on one of the 25,300+ topics significantly exceeds its own normal behavior over the most recent three weeks, a model designed to surface genuine, unusual interest rather than just high volume. This account-relative scoring, as detailed in a 2026 analysis by Abmatic.ai, allows Bombora to detect meaningful spikes even at companies with historically low research traffic, providing a nuanced view of emerging purchase intent. The entire process is built on a privacy-first framework, using consented first-party data that remains durable against the deprecation of third-party cookies.

ZoomInfo Intent adopts a blended data strategy, bundling its intent signals directly within the SalesOS and MarketingOS platforms rather than offering a standalone data product. Its methodology combines several data streams: third-party signals from publisher networks and bidstream data, first-party signals from activity on ZoomInfo's own platform, and second-party data from a partner network that includes software review sites like G2. This integrated approach is designed to provide a holistic view by layering intent signals on top of ZoomInfo's massive B2B contact and company database, which contains over 500 million business contacts. Unlike Bombora's weekly refresh cadence, ZoomInfo offers daily and even real-time streaming intent alerts, aiming to give sales teams a speed advantage. The platform's WebSights product further enriches this by resolving company IP addresses from website traffic, connecting anonymous visitors to the broader account graph and triggering intent-based workflows. This all-in-one model makes it a compelling choice for teams already invested in the ZoomInfo ecosystem for contact data and prospecting.

The primary distinction in go-to-market application is that Bombora provides account-level surge data without attached contact information, positioning it as a pure data layer that requires a separate execution tool for outreach. A typical workflow involves feeding Bombora's weekly surge reports directly into a CRM or marketing automation platform to prioritize accounts for sales and marketing teams. In contrast, ZoomInfo's value proposition is its unified platform; it provides not only the intent signal but also the verified contact data, direct dials, and organizational charts needed to act on it immediately. This difference is reflected in their pricing and packaging. While both vendors are quote-based and target enterprise clients, third-party analyses from 2026 report Bombora's pricing starts around $25,000-$30,000 annually, whereas ZoomInfo's intent capabilities are bundled into higher-tier subscriptions like Copilot Advanced, with total contract values often starting higher. Consequently, the choice often hinges on whether a team prefers a best-in-class, independent data source to plug into their existing stack or an all-in-one platform that combines intent with a comprehensive contact database.

Feature	Bombora	ZoomInfo	Key Difference
Primary Data Source	Proprietary Data Co-op of 5,000+ B2B publisher sites.	Blended model: co-op data, bidstream, platform signals, and review site partnerships (e.g., G2).	Bombora relies on its exclusive, consent-based co-op; ZoomInfo uses a wider, more varied mix of sources.
Data Scope	Account-level surge scores and topics. No contact data provided.	Account-level intent signals bundled with a large contact database (emails, direct dials).	Bombora tells you which company is interested; ZoomInfo tells you which company is interested and who to call.
Core Methodology	Compares an account's 3-week topic research against its own 12-week historical baseline.	Tracks spikes in content consumption, ad interaction, and platform activity against the market.	Bombora's model is account-relative (vs. self), while ZoomInfo's is more absolute (vs. market).
Execution Model	Data-only layer; requires integration with a CRM, sequencer, or ABM platform for activation.	Integrated platform (SalesOS); intent data and execution tools are in the same system.	Bombora is a data feed for your existing stack; ZoomInfo aims to be the stack.
Pricing Model	Standalone, quote-based annual contract. Reported to start around $25,000-$30,000.	Bundled feature in higher-tier platform subscriptions (e.g., Copilot Advanced).	Bombora is purchased as a distinct data product, while ZoomInfo Intent is an add-on to a larger platform purchase.
Data Refresh Cadence	Weekly surge reports.	Weekly, daily, or real-time streaming options available.	ZoomInfo offers faster, potentially real-time alerts compared to Bombora's weekly cycle.

Salesforce's Perspective: The Role of Data in the 2024 State of Sales

Salesforce's 2024 research underscores that adapting to evolving customer needs and expectations is the single greatest challenge facing sales organizations today. The sixth edition of the "State of Sales" report, which is based on a double-anonymous survey of 5,500 global sales professionals conducted from March to April 2024, found that 57% of respondents see changing customer expectations as more of a challenge than in the previous year. This pressure is compounded by intense market competition, which 57% of sellers also cited as an increasing difficulty. Buyers now demand more than just product information; they expect sales representatives to act as trusted advisors who provide personalized engagement focused on their specific needs. This requires a deep understanding of the customer's context and business challenges, a task made difficult by the fact that reps report spending only about 30% of their time on actual selling activities, with the rest consumed by administrative tasks. The clear message from the market is that to win deals and foster loyalty, sales teams must move beyond transactional relationships and deliver value-driven, consultative experiences at every turn.

The complexity of modern sales is further amplified by the sheer number of communication channels teams must manage. The fifth edition of Salesforce's "State of Sales" report, which surveyed over 7,700 sales professionals, revealed that sales organizations communicate with buyers across an average of ten different channels. This multi-channel environment, spanning from email and social media to virtual meetings, creates significant fragmentation and makes it difficult to maintain a unified view of the customer. While buyers expect sellers to meet them wherever they are, this proliferation of touchpoints risks overwhelming sales teams and diluting the quality of engagement. In fact, a subsequent analysis of the fifth edition data highlighted that over 80% of reps felt overwhelmed by the number of sales tools they had to use. This data highlights a critical operational challenge: without a centralized and intelligent system to consolidate customer interactions and data, sales teams struggle to act as the trusted, well-informed advisors that buyers now expect, leading to disjointed experiences and missed opportunities for meaningful connection.

High-performing sales teams are differentiating themselves by strategically deploying AI and data-driven insights to cut through the noise and enhance productivity. The "State of Sales, 6th Edition (2024)" reveals a strong correlation between success and technology adoption, with 81% of all sales teams now either experimenting with or having fully implemented AI. These high-performing teams are more likely to leverage AI for a range of activities, including personalizing outreach, prioritizing leads, and even providing real-time call coaching. For instance, 70% of teams using AI apply it to generate real-time selling guidance. This move toward intelligent automation is a direct response to the overwhelming administrative burden, as it allows reps to focus more of their limited time on high-value selling activities. The impact is significant, with teams using AI reporting higher revenue growth and increased headcount, debunking fears that the technology would replace jobs and instead showing it as a catalyst for expansion. By embedding data-driven practices into their core workflows, top sales organizations are not just working harder, they are working smarter to meet and exceed modern buyer expectations.

Bridging the gap between insight and action, the native integration of Bombora's Company Surge® data directly within Salesforce provides a powerful, practical solution for sales teams. This integration allows organizations to activate third-party intent data without forcing reps to learn a new platform or disrupt their existing CRM-based workflows. Company Surge® for Salesforce functions as a custom object, enabling administrators to seamlessly embed intent data into dashboards, account list views, and automated workflows. This gives sales representatives clear, actionable signals on which of their target accounts are actively researching specific products or solutions, allowing them to prioritize outreach with unprecedented accuracy. Instead of starting from a cold list, reps can see which accounts are demonstrating in-market behavior and understand the specific topics they are interested in. This context empowers them to tailor their messaging and value propositions to resonate deeply with a prospect's immediate needs, transforming a potentially cold call into a relevant, timely, and highly personalized conversation that drives engagement and accelerates the sales cycle.

The Activation Gap: Why 91% of Users Don't See Exceptional ROI

A significant activation gap prevents most B2B organizations from realizing the full potential of their intent data investments. While adoption is widespread, with a joint study from DemandScience and Autobound showing 91% of B2B marketers use intent data for account prioritization, the results are underwhelming for the majority. The same 2026 research, which surveyed B2B marketing leaders, revealed that only 24% report achieving exceptional ROI from these powerful signals. This disparity highlights a critical distinction between data integration, the technical connection of a signal source, and data activation, the operational workflow that turns a signal into a sales action. The core challenge is not access to data but the failure to embed these time-sensitive insights directly into the daily routines of sales representatives. When signals remain fragmented across platforms or are not presented with context inside the primary CRM, they become noise rather than actionable intelligence, leading to diminished returns and a failure to translate insights into revenue. The data clearly shows that merely purchasing an intent data subscription without re-engineering the response workflow is a recipe for disappointment.

The primary driver of underperformance is the failure to integrate intent signals directly into a representative's core workflow, namely the CRM and sales engagement platforms. When intent data is not seamlessly embedded, it creates friction and delays that erode its value. A 2024 analysis from TalkCMO emphasizes that without proper integration into tools like Salesforce, data remains siloed, leading to slower response times and missed opportunities. This technological hurdle means that even when a salesperson has access to insights about a lead's intent, they may struggle to conveniently use that data during a sales call or outreach sequence. The most successful revenue teams operationalize intent by making it an unmissable part of the existing process, for example, by automatically creating prioritized tasks in the CRM or dynamically populating a sales engagement sequence based on a surge in research from a target account. This contrasts with the far more common and less effective approach of providing access to a separate intent data platform, which requires reps to manually check for signals and cross-reference them with their accounts, adding a layer of work that is often neglected under the pressure of meeting activity quotas.

Compounding the integration challenge is the rapid decay in the predictive value of intent signals, making speed-to-lead a critical factor for ROI. An intent signal is a perishable insight; its value is highest at the moment of capture and diminishes quickly thereafter. Research from Forrester found that for typical B2B purchases, intent signals can lose approximately 50% of their predictive value within just 30 to 45 days. Another analysis suggests that 47% of intent records can become stale within only 14 days of capture. This concept, known as intent decay, means that a signal indicating research on a specific topic today is significantly more valuable than the same signal from a few weeks ago. When a high-intent action occurs, such as a visit to a pricing page, the buyer is already deep into their evaluation. A delay of even a few days in follow-up can mean the difference between entering the conversation while options are being considered and arriving after a competitor has already been shortlisted or a decision has been made. This rapid value destruction underscores why manual, disconnected activation workflows are so detrimental to performance.

Data quality and reliability present another formidable barrier to achieving exceptional ROI, as a large portion of signals fail to translate into tangible pipeline. According to DemandScience's 2026 "State of Performance Marketing" report, a staggering 87% of organizations report that their investments yield unreliable or inflated intent signals. This refers to clicks, downloads, and behavioral scores that appear to signify buying intent but do not accurately reflect a prospect's readiness to engage. The downstream impact is severe, with the same study, which surveyed 750 senior B2B marketing leaders, finding that only 26% of these intent signals ultimately convert into qualified opportunities. This suggests a fundamental misalignment between the data collected and its real-world application. Organizations often act on a high volume of low-quality signals, overwhelming sales teams and diluting focus. Without a rigorous process to vet the source and methodology of intent data providers, from how they capture consent to the recency of the signal, marketing teams risk building their activation strategies on a foundation of inaccurate or misleading information, inevitably leading to poor conversion rates and a frustrating experience for both sellers and buyers.

Frequently Asked Questions

What is the average ROI of using Bombora intent data?

A Forrester Total Economic Impact study of a Bombora customer revealed a 342% return on investment over three years, with a net present value of $4.2 million. This financial impact was driven by a 15% growth in revenue from increased conversion rates and a sales velocity increase of up to 30%. The study, commissioned by Bombora, analyzed a real customer's usage to project the financial benefits, which also included saving 4,500 hours annually through data efficiencies. A separate Forrester study focusing on data publishers using Bombora found a similar 335% ROI.

How does Bombora collect its intent data?

Bombora collects intent data through its proprietary Data Co-op, a consent-based network of over 5,000 B2B publisher and brand websites. A tag placed on these partner sites anonymously tracks content consumption, such as page views and downloads, which are then mapped to a taxonomy of over 21,600 B2B topics. This cooperative model provides a broad view of B2B research activity, with Bombora stating that 86% of its signals are exclusive to its network. The data is aggregated at the company level, not the individual level, to identify which accounts are showing a significant increase in research on specific topics.

What is the difference between Bombora and ZoomInfo intent data?

The primary difference is their data collection methodology and how the data is packaged. Bombora's intent data comes from its exclusive Data Co-op of over 5,000 B2B publisher websites, focusing on tracking content consumption to identify account-level research spikes. In contrast, ZoomInfo blends third-party bidstream data and publisher network signals with its own first-party data from platform usage and its IP-to-company mapping network. Bombora provides only account-level intent signals, requiring a separate tool for contact data, whereas ZoomInfo bundles its intent data with its comprehensive contact database, allowing users to find a named contact alongside an intent signal within the same platform.

How much does Bombora cost in 2024?

Bombora does not publish official pricing, as costs are quote-based and depend on the number of topics tracked, data volume, and integration needs. However, procurement data from 2024-2026 indicates that entry-level contracts start around $25,000 to $40,000 annually for a limited set of topics. Most mid-market companies can expect to pay between $50,000 and $100,000 per year, while enterprise-level deployments with extensive topic coverage and API access can exceed $150,000. These costs are for the intent data license only and do not include the necessary budget for a separate contact data provider, which is required to act on Bombora's account-level signals.

What were the key findings of the Salesforce State of Sales 2024 report?

The sixth edition of the Salesforce State of Sales report highlights a major shift towards using AI to boost productivity and growth. A key finding is that sales reps report spending only 30% of their time on actual selling, bogged down by administrative tasks that could be automated. The 2024 report, which surveyed 5,500 sales professionals, found that 81% of sales teams are already using or experimenting with AI. Notably, teams that have adopted AI are outperforming those that have not, with 68% of AI-powered teams adding headcount in the past year, suggesting AI adoption correlates with business growth rather than job displacement.

Last updated: October 2026

Intent Data ROI: 2024 Benchmarks for Pipeline Lift