Table of Contents
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Quick-Read Summary
Marketers have now grasped that B2B buyers hunt in packs of nearly 10 as they pursue business solutions for their organizations.
Marketers are also getting better at recognizing these buying groups when they come knocking – 72% already recognize and prioritize accounts that present with multiple leads. This is outstanding.
But these packs of buyers roam the B2B internet for nearly a year in their quest for solutions, riddling the landscape with thousands upon thousands of digital footprints – footprints that could act as a crystal ball to reveal which will knock if invited, and which may need a more persuasive nudge to step forward.
Yet, instead of harvesting the bounty of signals at their disposal, many still prefer to pick at the meager selection they’ve been presented for nearly two decades. When asked about 23 different types of signals, most cling to just a handful.
Our study shows that this reluctance owes more to skepticism than to external barriers such as budget, process, skill, or technology – and it’s smothering the creativity that marketers must summon to break through the artificial limits to revenue productivity imposed by outdated practices.
The report also offers a silver lining: when companies invest more in marketing, that investment pays off. Higher marketing budgets were associated with improved overall financial performance.
Summary of Findings
- Group-Based B2B Purchasing: Typical B2B purchases are made by groups of 10 individuals, with larger deals involving bigger teams. Marketers understand this but still underestimate buying group sizes for lower-cost solutions.
- Research and Anonymity: All buying team members conduct online research, but most remain anonymous. The average form-fill rate is 3.7%, indicating that most buyers do not disclose their identities.
- High Reliance on Form-Fills: Despite form-fill rates being low, form-fills are the signal marketers rely on most, suggesting a disconnect between how buyers buy and how marketers identify them.
- Go-To-Market Strategies: Forty-three percent of marketers use Account-Based Marketing (ABM) alone or with Inbound, Outbound, or both. Another 22% use a mix of Inbound and Outbound, 21% solely focus on Inbound, and the remaining 15% only use Outbound strategies.
- Buying Group Visibility: Seventy-two percent of marketers prioritize accounts where multiple buying group members complete forms on their websites, an 11% improvement from 2022.
- Tools & Data Sources: Marketers use including CRM systems, marketing automation platforms (MAP), and third-party intent data to find potential buyers. Surprisingly, they underutilize CRM and MAP systems for account data.
- Buying Signal Utilization: Large buying teams generate a sea of signals across nearly two dozen channels. However, most marketers access fewer than 7 of these channels.
- Buying Signal Dissatisfaction: Marketers are not satisfied with the buying signals they use (usefulness rating below 40%), with many marketers finding them less useful than desired.
- Challenges in Signal Mix Optimization: Time, technology, process, skill, and budget score as equivalent challenges to using a better mix of buying signals.
- Budgeting Insights: Organizations allocate 13.4% of their annual revenue to marketing, varying by industry and target audience. Demand and ABM strategies occupy 40% or less of the overall marketing budget. Higher marketing budgets correlate with better financial performance.
Author’s Note
As we engineered data collection and analysis for this research, we grappled with what to name it.
We considered calling it the State of ABM and Demand study, and the contents of this report would justify that name. For a similar report last year, we opted for “Buying Signals Study.” Then, our focus was on raising awareness of the need to utilize the full array of signals to identify buyers. That work remains to be done.
But that still missed the mark. What truly matters are the last two words of the prior paragraph:
identify buyers.
That is the first hurdle marketers must surmount. As marketers, we obsess over “engage and convert.” But, if we pursue the wrong accounts or look the other way as potential buyers file through your digital doorways, we will waste time and budget.
In this report, we first map the terrain of B2B buyer journeys. Buyers have detailed their journeys for us. We know what those journeys are like. Then, we catalogue the steps and strategies B2B marketers use to engage with them. Spoiler alert: the steps and strategies don’t always intersect with the journeys they are meant to track.
Whatever you are doing to identify your next best customers today, it almost certainly isn’t what you will be doing by the time your employer refreshes your laptop. We invite you to stay with us throughout the coming year as we guide you through the landscape of B2B’s best and worst practices and the recommendations that follow from them.
Introduction
Our recent report, Buyer Experience Study, revealed that just one in three individuals who will go on to become your customer will fill out a form to see your content. If you put content behind a gate, you are ensuring that two-thirds of your most devoted audience will not see it.
We also know that serious buyers do not speak with vendors until they are 70% through their buying journeys.
In other words, most buyers won’t fill out your forms or talk to you while they are researching your solutions.
But it is what buyers accomplish while shopping undercover that should alarm B2B organizations the most: they decide what they are going to buy and from whom.
The buyers in our recent Buyer Experience Study told us that they do not simply respond when sellers reach out. Instead, they bide their time, waiting to engage until they are ready as a buying group. When they are ready, they initiate that first contact 83% of the time.
What does ready mean? Your buyers told us that their first direct interaction – which they initiated – was with the vendor that ultimately won the business 84% of the time.
Because this first direct interaction happens more than two-thirds of the way through the journey, there can be only one conclusion: buyers know who they are going to buy from when they begin engaging with sellers directly. Buyers decline conversations with sellers until 70% through their journeys, because they want to decide what to buy before talking to sellers, and it takes that long to get there.
That is the context for this report.
Our 2022 Buying Signals Study revealed that B2B organizations relied primarily on the old-familiar – form-fill leads. Knowing that sales must be made prior to the first buyer-seller interaction, we surveyed 546 marketers in late 2023 to see if this had changed.
Findings
The B2B Buyer
B2B Purchases Are Made in Groups, Leaving A Wealth of Signals for Marketers
Recent studies, including our own, consistently highlight the collaborative nature of B2B purchases. Our 2022 Buying Signals Study and the 2023 Buying Experience Study together surveyed more than 1,000 B2B practitioners and buyers and found the average buying group size to be 10 members. The current research buttresses this understanding, revealing that as solutions get more expensive, the teams that buy them get larger. In fact, nearly 40% of the reason one buying team is bigger than other is down to average selling price (ASP).
Source: 6sense
Figure 1 shows that marketers know that buying groups expand with solution costs. Results from our recent Buying Experience Study validate this understanding. In that study, we asked buyers to tell us how large their buying groups were and compared that data to the data collected on buying group sizes from the current study.
Marketers’ View of the Buying Group Largely Tracks with What Buyers Report
As Figure 2 below illustrates, buying group sizes that marketers report align closely with those reported by their buyers (the correlation coefficient for the two responses was r = .94, an exceptionally strong correspondence). Marketers clearly understand the sizes of the buying groups they target. It is notable, however, that marketers tend to underestimate the size of buying groups for lower cost solutions. As in prior years, we also found that Director-level responders had more accurate – which in most instances means slightly higher – estimates of buying group size.
Source: 6sense
In summary, our findings underscore that B2B buying is a team effort, with group sizes averaging just under 10 members, a number that increases with the size of the deal. This reaffirms our previous research and emphasizes the collective decision-making process in B2B purchases.
Why Large Buying Teams Are the Key to Understanding and Identifying Buyers
In our 2023 Buying Experience Study, we found that a typical 10-member B2B buying team had 160 digital and human-mediated (e.g., calls, direct emails, in-person meetings) over the course of their buying journey, and more than 4,000 across all channels.
The most effective B2B revenue teams exploit these signals to know which accounts are in-market and require marketing or sales attention. Finally, it is not just a designated scout or two from each buying team that visits vendor websites. Buying team members from corner offices to the smallest cubicles told us that they have double-digit interactions with each vendor being evaluated.
Source: 6sense
All Buying Groups Conduct Online Research, But Most Remain Anonymous
Consistent with all prior research both by 6sense and others, marketers once again told us that approximately 3.7% of their web visitors fill out forms to view content. The Interactive Table below shows form-fill rates by factors such as industry, average selling price and more. While you’ll see slight variations in form-fill rates with these filters, most are not statistically reliable. We’ll soon see that the only meaningful difference in form-fill rate is between organizations that practice account-based marketing and those who do not.
There is critical context to add from other research, which indicates that when visitors come from accounts that can be identified through de-anonymization techniques, just 15% to 20% of these visitors fill out forms (PathFactory). Further, in our recent Buying Experience Report, buyers reported that only 30% filled out forms on the websites of vendors they brought from.
Source: 6sense
While individuals from identifiable accounts clearly complete forms at a higher rate than others do, 70% to 80% of these visitors remain anonymous, even to the companies they eventually buy from.
We will discuss the use of strategies such as outbound, inbound, and Account-Based Marketing (ABM), below. Here, however, it is worth noting that marketers that employ an account-based strategy earned a higher form-fill rate. This might be due to the focused account targeting and messaging inherent in ABM strategies.
As shown in the chart below, ABM marketers report an average form-fill rate of 4%, roughly half a percentage point higher than those who do not (3.4%). This difference is statistically reliable. It is not, however, likely to make a meaningful difference in pipeline and revenue creation for those doing ABM compared to others.
Source: 6sense
How B2B Organizations Attract Buyers: Go-To-Market Strategies
In our research, we queried marketers about their use of three specific go-to-market (GTM) strategies.
- Inbound Marketing: An approach aimed to attract and engage potential customers to reveal themselves to vendor organizations by offering valuable content and experiences.
- Outbound Marketing: Methods that involve proactively reaching out to an audience through channels such as email, direct mail, and outbound prospecting to promote products or services.
- Account-Based Marketing (ABM): A targeted strategy that aligns marketing and sales on highly targeted engagement with high-value accounts, tailoring inbound and outbound tactics to address the target accounts.
In our sample, 43% of marketers practice ABM, whether on its own or combined with inbound, outbound, or both.
Because many respondents reported a mix of strategies, we classified participants into five categories based on whether they exclusively employed a single go-to-market strategy or combined it with others.
- ABM Only: The marketing organization exclusively practices Account-Based Marketing (ABM/X).
- Inbound Only: The marketing organization exclusively practices inbound marketing.
- Outbound Only: The marketing organization exclusively practices outbound marketing.
- ABM Blend: The marketing organization practices ABM along with either inbound marketing, outbound marketing, or both.
- Traditional Blend: The marketing organization practices both inbound and outbound marketing.
As figure 6 shows, the most common strategy involved ABM plus either inbound, outbound, or both (ABM Blend). Together, the two categories of blended strategies accounted for 51% of respondents. Despite ABM Blend being the most common strategy, ABM-only practices were the least common.
These results suggest that ABM strategies have been widely adopted but are rarely the only way an organization goes to market. Later, we will explore the conditions, tactics, and outcomes associated with the adoption of ABM.
Source: 6sense
Marketers Are Equally Satisfied with Inbound, Outbound, and ABM
To begin, we asked marketers to rate their level of satisfaction with each of the three main GTM strategies. These results are given in Figure 7 below. Despite variation in how organizations combine the three major approaches, B2B practitioners reported statistically identical, high levels of satisfaction with each.
Source: 6sense
Account-Based Marketing (ABM) Adoption
Across the board, approximately 40% of organizations have an ABM practice. We looked across industries, company funding (private-equity, venture capital, public, etc.), annual revenue, solution prices, and buyer company size (small, medium, large), but found no meaningful patterns that predict which types of organizations employ Account-Based Marketing (ABM).
The Types of Account-Based Marketing (ABM) that Marketers Employ
As we’ve seen, 43% of B2B organizations use an Account-Based Marketing (ABM) strategy, whether on its own or combined with inbound marketing, outbound marketing, or both. Of these, we wanted to understand the type of ABM approach they use (see descriptions below).
Although the current study did not yield sufficient data to address this question, insights into the types of ABM practiced by marketers today can be gleaned from the responses of 650 B2B marketers in another survey we conducted in January 2024 (for more information on this study please see the Methods section).
- One-to-one ABM: Revenue teams target individual high-value accounts with customized strategies tailored to each account’s unique needs and characteristics.
- One-to-few ABM: Marketers target a larger set of similar accounts, employing personalized strategies for tailored marketing efforts.
- One-to-many ABM: Revenue teams target clusters or segments of accounts with shared characteristics, such as their industry, region, or size. Messaging and tactics are customized to the segment, but not to the specific account level.
Figure 8 below represents the proportion of marketers with an ABM practice that engage in each type of ABM. For example, the most common type of ABM practice is one-to-few.
Source: 6sense
A Strong Majority of Organizations See and Respond to Buying Groups, Not Just Leads
In B2B transactions, relying on a single form-fill to identify in-market prospects is ineffective. It fails to differentiate between casual browsers and active buying team members. When multiple individuals from the same group research similar solutions concurrently, that is a more reliable indicator of potential buyers lies in recognizing. The likelihood of a buying opportunity increases with each additional visitor from the same account engaging in this behavior.
To understand if organizations see and act on this indicator, we asked whether they prioritize accounts from which they have received multiple leads. A promising 74% of organizations indicated they do prioritize accounts with multiple leads, a notable rise from 61% found in our 2022 study. This indicates a growing awareness of active buying processes.
Source: 6sense
Prioritizing Buying Groups Is Associated with Better Financial Performance
Bolstering the case for prioritizing buying groups, we found that marketers who prioritize buying groups report 4% better financial performance compared to those who don’t. These findings indicate that simply knowing when buying groups are present without acting does not yield any benefits.
Source: 6sense
Data and Tools Used to Identify Accounts & Contacts
Organizations have a variety of data sources, both internal and external, to draw from when identifying accounts and contacts to target as prospects. In addition, numerous tools exist to help organizations refine their selection of accounts and contacts. These tools range from spreadsheets that can be filtered to tools that use predictive analytics/artificial intelligence (AI) to identify ideal customer profiles.
Marketers Use Many Data Sources, But None Are Universally Adopted
Figure 11 below reveals that just over half of marketers use each of the data sources listed for account acquisition, but none are used by more than 43% for contact acquisition. While most sources are used by at least half of the participants for account identification, they are less likely to be used for contact data. For instance, less than 38% use MAP for contact data, and under 30% use CRM. CDPs and 3rd party data providers are more common for contact data, but their usage doesn’t exceed 43%.
Typical marketers use three to four different sources for account and contact information.
The reliance on external sources suggests that marketers find the quality and/or quantity of their internal sources to be inadequate.
Source: 6sense
Marketers Use Many Tools for Selecting Contacts and Accounts, But None Are Universal
In addition to these data sources, marketers utilize tools offering sophisticated analytics and filtering to select the best accounts and contacts. These tools are distinct from pure data sources. Often, data will be sourced elsewhere and loaded into the tools discussed below for further processing.
Stronger Performing Organizations Utilize More Data Tools
We found that marketers with ABM practices generally use three tools, whereas others use two. Notably, companies with better financial performance use between four and five tools. Lower-performing companies tend to use only two to three tools. This indicates a correlation between a company’s investment in buyer identification tools and their financial performance.
Source: 6sense
Identifying In-market Buyers: Buying Signal Usage and Utility
As we have seen, marketers have a variety of tools available to identify potential prospect accounts and contacts. However, as our prior research has demonstrated, only a small fraction of accounts – even those that are targeted to be a good fit – will be in-market for a solution at any given time. To optimize efficiency, marketers need to identify the small subset of good-fit accounts that are actually in-market.
Fortunately, the intelligence about which accounts are in-market is available to be harvested. As B2B buying teams comb the internet in search of solutions to their business problems, they have thousands of digital interactions. These interactions are catalogued, matched to the accounts from which they come, and are made available to B2B vendors in the form of 3rd-party intent data. Combined with traditional signals such as email and ad clicks, this offers mountains of information to help B2B providers identify in-market buyers. We explored if revenue teams are leveraging this abundance and their perception of its usefulness, using a list of 23 distinct buying signals.
B2B Marketers Don’t Agree on Much, But Still Rely Heavily on Form-fills
Website form-fills remain the most utilized signal. As described earlier in this report, we know that most web visitors – even those that will make a purchase — don’t fill out forms. More importantly, buying team members don’t engage directly with sellers until 70% of their buying journey is complete, and only after they have formed strong opinions and even chosen a winner.
To influence buyers earlier, revenue teams need to identify interest before form-fills occur. This involves two underutilized methods: de-anonymized web traffic and 3rd party intent (for more information on these topics, see “Moving on from Lead-Centricity”).
B2B’s Underutilized Early Warning Systems: De-anonymized Web Traffic & 3rd-party Intent
With technology readily available today, typical B2B companies can identify the accounts from which half or more of their (non-bot) anonymous traffic emanates. Doing so dramatically increases a marketer’s understanding of which accounts are showing interest.
However, our survey found that only 31% of marketers de-anonymize their web traffic, with a mere 11% finding it useful. This indicates a profound gap in marketers’ understanding of the value of unmasking anonymous web visitors.
The second early warning system for marketers comes from 3rd-party sources such as intent data, product reviews, and social media. While over 40% of marketers use leads from product review sites and social media, less than 25% find them useful. Despite being a rich intelligence source, only 30% of marketers use third-party intent data, with only 12% of users finding it useful.
Readers may browse the table below to examine how the characteristics of provider organizations, such as the cost of their solutions, their industries, and many others influence their use of buying signals.
Overall Signal Utilization Is Low Across B2B
The data show that most organizations use only a fraction of the signal types available to help the identify buyers. Most organizations use between five and six signal types out of the 23 we asked about. Worse yet, as presaged above, marketers do not find the signals they do collect particularly useful. None of the signals were found to be useful by more than 35% of users, and most signals were found to be useful by 20% or fewer of marketers.
Below, we examine how critical factors such as go-to-market strategy, annual revenue, company funding type (private, public, etc.), and buyer segment impact or do not impact the variety of signals that marketing organizations collect.
Blended GTM Strategies Drive More Buying Signal Usage
Not surprisingly, the strategies a company employs to identify buyers influence their use of buying signals. Companies with multiple strategies employ more signals than those with just a single strategy.
Source: 6sense
Private Equity-Backed Firms Tend to Use More Signal Types
Private equity-backed (PE-backed) firms tend to gather more signals compared to their counterparts in companies with alternative funding structures. Marketers at private, public, and venture capital firms, on the other hand, use a statistically equivalent number of signal types.
Source: 6sense
Small to Mid-Size Enterprises Collect More Signal Types
Surprisingly, small to mid-size organizations report using more types of signals than larger companies do. Those with revenue between $50M and $250M gather 8 to 9 types while those above $250M collect around 5 to 7 types.
Source: 6sense
Classifying Signals to Understand What Marketers Want From Them
With most signal types in use by 40% or fewer of marketers, and most marketers using between just 5 and 6 types of signals in total, we were not able to identify any clear combinations of signals that marketers tended to employ as a group. There are no canonical “signal stacks.”
However, many signals share characteristics. For example, some signal types (e.g., form-fills) point to the activity of individuals who are identified by name. Others (e.g., de-anonymized web traffic) can only point to an account that is demonstrating interest. Likewise, some signals point to actions by groups from the same account (e.g., 3rd party intent), while others indicate the behavior of individuals (e.g., syndicated content leads).
By categorizing each of the 23 signals along four dimensions, we were able to gain a better understanding of what marketers value in buying signals. Whereas analyzing the list of 23 specific signals yielded relatively few insights into what marketers value, this new perspective allowed us to identify clear patterns in marketer preferences.
Below in Figure 16 are definitions of the four dimensions, along with utilization and utility ratings for each.
| Signal Dimension | Raw | Derived |
| Definition | Signals acquired and used in the form they are received (e.g., form-fill lead). | Signals in which an operation to either one signal or a combination of two or more signals to produce a new signal (e.g., a form-fill to which a score has been applied to enable prioritization). |
| Average Collected | 5.3 signals | 1.7 signals |
| Percent Considered Useful | 49% | 45% |
| Signal Dimension | Anonymous | Identified |
| Definition | Signals used to identify anonymous behavior (e.g., third-party anonymous intent, anonymous visitors to a website). | Signals for which the identity of the individual is known (e.g., webinar registrations). |
| Average Collected | 2.1 signals | 5.0 signals |
| Percent Considered Useful | 46% | 50% |
| Signal Dimension | Individual | Group |
| Definition | Signals that reveal the presence or actions of a single person (e.g., form-fill, email open). | Signals that are telling of group behavior (e.g., third-party intent, software review site account-level report). |
| Average Collected | 5.4 signals | 1.5 signals |
| Percent Considered Useful | 50% | 46% |
| Signal Dimension | Received | Acquired |
| Definition | Signals that are received directly from provider systems (e.g., freemium downloads, form-fills). | Signals that are acquired from another party, which originally received or created the signal (e.g., syndicated content leads, third-party intent). |
| Average Collected | 4.1 signals | 2.9 signals |
| Percent Considered Useful | 44% | 52% |
No Surprise: Marketers Like Signals Where Individuals are Named and Received Directly into Their Systems
Marketers clearly depend on signals that identify individuals, are received in their own systems, and used in the form they receive them. In other words, marketers still want form-fill leads or other signals, such as syndicated content leads, and product review website leads that point to specific people.
What marketers want varies depending on a variety of factors. Those factors can be used as filters in the interactive table below. We encourage readers to explore the interactive table below to understand how various go-to-market (GTM) strategies impact reliance on each signal category.
Account-Based Marketers Use More Anonymous and Computed Signals
In the interactive table above, the account-based marketing (ABM) filter shows that marketers who practice ABM are more likely to use signals that indicate buying group activity than those without an ABM practice. ABM practitioners are also more likely to collect anonymous signals and signals that are computed, such as account or intent activity scores. These findings indicate that ABM marketers are more likely to understand the value of signals that identify buying group activity.
Inbound Marketers Take a Surprisingly Broad Approach, But Still Favor Form-fills
In the interactive table above, filtering for marketers who practice Inbound marketing shows that these marketers are more inclined to use signals that identify individuals, whether received in their own systems or acquired from external sources (e.g., syndicated content leads). Inbound marketers also utilize both raw signals (e.g., a form fill) and computed signals (e.g., lead scores) more than peers that do not practice Inbound marketing.
Outbound Marketers Rely on Raw signals, Hampering Their Ability to See In-market Accounts
In the interactive table above, the Outbound filter shows that marketers who practice Outbound marketing are less likely to use computed signals (e.g., account scores, intent scores). This finding is troubling, because it indicates that organizations with an outbound marketing practice are not utilizing the resources available to them to identify accounts that are in-market. Because outbound prospecting is such an expensive activity, it behooves organizations to invest in acquiring signals that would narrow the focus on prospectors to those that are more likely, not just to be a good fit, but to be in-market. Our findings indicate that organizations are not doing this.
Challenges Marketers Face Are Consistent, No Matter the GTM Strategy
Having noted above that marketers are underutilizing available signals, we were interested to see if there were particular challenges that prevented marketers from utilizing a greater range of signal types.
Our findings indicate that about half of marketers face each of the five challenges mentioned. These challenges were equally common across industries, companies of different funding types (private, public, venture-capital, etc.), and target buyer segments. They were also reported equally by marketers across seniority levels (explore the interactive table below).
It is notable that Budget is no more of a challenge than time, technology, process, or skill. This suggests that the low usage rate of signal types is more due to a lack of belief in or understanding of their value, rather than in the budget, time, technology, process, or skill required to utilize them.
Marketing Budgets
In our survey this year, we explored how organizations budget for marketing. Across our sample of marketers from a wide array of industries, company sizes and funding sources, marketers reported that their organizations budgeted 13.4% of their companies’ annual revenues for marketing.
This figure is higher than the oft-cited benchmark of 5% to 10% of revenue for B2B marketing. There are notable studies that have found quite similar results, however. Most notably, in a 2023 report by Deloitte, CMO’s reported that their budgets were 13.6% of their companies’ annual budgets2. Lending further credence to the value we found, all industries surveyed reported statistically equivalent values, with Tech & Software being the exception at just 11.0% of revenue (see Figure 19 below).
Source: 6sense
Target Audience Influences Budget Allocation
We also explored whether other factors influenced how much was budgeted for marketing. We found that organizations that sell to accounting and finance departments enjoy substantially larger budgets (16.8%) compared to the overall average of 13.4%. In contrast, those selling to Operations/Engineering (9.1%) and Supply Chain (8.7%) departments were budgeted at a substantially lower level than their peers.
Source: 6sense
More Marketing Budget Yields Better Company Financial Performance
In our survey, we asked marketers to rate how their organizations performed financially over the past 12 months. Later in the survey, we asked about their budgets. A correlation analysis revealed that organizations that allocate more of their company revenues to marketing also report better financial performance (r=.259, p<.001). Not surprisingly, marketers in organizations that allocate more of their company revenues to Marketing also report higher satisfaction with their GTM strategies (r=.267, p <.001).
Inbound, Outbound, and ABM programs are Equally Budgeted
The marketers we surveyed indicated that Inbound, Outbound, and Account-Based Marketing (ABM) strategies each receive equivalent shares of organizations’ marketing budgets. According to our survey respondents, around 40% of the total marketing budget is allocated to these strategies, whether individually or in combination. This distribution is consistent with the observation that not all organizations adopt all three approaches; in fact, only 15% of the 546 respondents we surveyed utilize Inbound, Outbound, and ABM simultaneously.
Implications
This research shows that B2B marketers increasingly recognize interest from buying groups — not just individuals. This shift enhances the effectiveness and efficiency of B2B revenue teams. An additional benefit is that focusing on interested buying groups allows non-active individual form-fillers to engage with vendor content in peace.
We know that buyers don’t engage directly until they are 70% through their buying process, and when they do, they have already decided which vendor they want to buy from 84% of the time. To operate effectively in this reality, marketers must proactively identify and engage potential buyers long before that 70% mark.
To maximize visibility into active buying groups, marketers must invest in intent data and website traffic de-anonymization. There simply is no other way to see and influence early stage buying processes.
Marketers might very well object that they operate under constraints, primarily of budget and time, and so cannot take advantage of the available signals. However, while roughly half of the marketers we surveyed cited budget as a challenge to doing more, that leaves half of B2B marketers with budget to acquire more signals. These organizations need to move quickly to remove other barriers to productivity, whether those barriers be internal processes, skills, or re-prioritizing staff time.
Finally, the link between higher marketing budgets and improved financial performance underscores the need for adequate marketing funding. Marketers that are budget-constrained should use reports like this one and others cited in this report to advocate for more robust budgets, highlighting their impact on financial results and marketing effectiveness.
Methods
6sense Research surveyed B2B professionals to understand how they identify their target accounts and buying groups. The 2023 study expanded its scope from 169 respondents in 2022 to 546 B2B professionals and incorporating additional survey questions to explore how organizations allocate their budgets and the go-to-market strategies they employ to engage potential buyers. Conducting this survey annually enables us to track trends in B2B practices, providing a longitudinal perspective on changes over time.
The following charts provide a breakdown of our survey participants, highlighting demographic and firmographic information such as their industry, company size, and more.
Survey Respondents
A Note on Additional Survey Data Used
As noted earlier, there were limited responses to a specific question in our survey regarding the types of account-based marketing (ABM) strategies employed by marketers. However, we asked the same question to 650 marketers in another survey conducted early 2024. Thus, we used the data from that survey to provide insight into which types of ABM marketers are practicing today (one-to-many, etc.). About 20% of these marketers work in Technology, 15% in Manufacturing, 10% in Financial Services, 16% in Professional Services, 27% in Business Services, while the rest were spread across industries such as Education, Construction, Legal Services and more.
Appendix
Signal Types and Their Characteristics
| Signal Type | Individual or Group | Identified or Anonymous | Received or Acquired | Raw or Derived |
|---|---|---|---|---|
| Display Ad Clicks | Individual | Anonymous | Received | Raw |
| Display Ad Views | Group | Anonymous | Acquired | Raw |
| Scored Form-Fill Leads (MQLs) | Individual | Identified | Received | Derived |
| Form-Fill Leads | Individual | Identified | Acquired | Raw |
| Anonymous traffic, deanonymized | Group | Anonymous | Received | Derived |
| Syndicated Content Leads | Individual | Identified | Acquired | Raw |
| Social Leads | Individual | Identified | Received | Raw |
| Partner Referrals | Individual | Identified | Acquired | Raw |
| 3rd Party Anonymous Intent | Group | Anonymous | Acquired | Derived |
| Product Review Site Leads | Individual | Identified | Acquired | Raw |
| Product Review Site Company Level Intent | Individual | Anonymous | Acquired | Derived |
| Email Opens/Clicks | Individual | Identified | Received | Raw |
| Demo Requests, Downloads | Individual | Identified | Received | Raw |
| Demo Usage (# users, product telemetry) | Individual | Identified | Received | Derived |
| Freemium Downloads | Individual | Identified | Received | Derived |
| Freemium Usage | Individual | Identified | Received | Derived |
| Virtual Event Registrations | Individual | Identified | Received | Raw |
| Live Event Registrations | Individual | Identified | Received | Raw |
| Contact Me Requests | Individual | Identified | Received | Raw |
| Cold Calling | Individual | Identified | Received | Raw |
| Direct Mail | Individual | Identified | Received | Raw |
| SEO Clicks | Group | Anonymous | Acquired | Raw |
| Web Chat (Live or Bots) | Individual | Anonymous | Received | Raw |
Statistical Reporting
| Finding | Statistical Test | Statistic | Significance Level | Effect Size | Sample Size |
|---|---|---|---|---|---|
| The average buying group size is 10 members. | Average | N/A | N/A | N/A | 616 |
| Larger deals involve more buying team members. | Correlation | R=.620 | P<.001 | Fisher’s z= .726 | 616 |
| Average Selling Price (ASP) accounts for nearly 40% of what drives buying team size. | Linear Regression | R=.601 | P<.001 | R2=.36 | 573 |
| Marketers report buying group sizes that closely match those reported by their buyers, with a correlation coefficient of r = .94, indicating exceptionally strong agreement. | Correlation | R=.94 | P<.001 | Strong | 616 |
| Director-level respondents provided more accurate – which in most instances means slightly higher – estimates of buying group size. | ANOVA | F=5.290 | P<.001 | N2=.041 | 616 |
| The average form-fill rate is 3.7%. | Average | n/a | n/a | n/a | 574 |
| Marketers using account-based strategies saw form-fill rates increase to 4%, about 0.6% higher than non-ABM users at 3.4% | T-test | T=2.17 | P=.004 | Cohen’s d=.085 | 573 |
| 43% of marketers reported practicing ABM, either independently or in conjunction with inbound, outbound, or both. | Frequency | n/a | n/a | n/a | 574 |
| 51% of marketers use multiple Go-To-Market Strategies. | Frequency | n/a | n/a | n/a | 573 |
| Marketers rated their satisfaction with Inbound, Outbound, and Account-Based Marketing (ABM) equally. | Repeated Measures ANOVA | F=.436 | P=.647 | N2=.005 | 92 |
| We found no meaningful patterns in the types of marketing organizations that employ Account-Based Marketing (ABM) based on industry. | Chi-Squared | X2=9.37 | P=.095 | n/a | 573 |
| We found no meaningful patterns in the types of marketing organizations that employ Account-Based Marketing (ABM) based on company funding. | Chi-Squared | X2=2.385 | P=.496 | n/a | 573 |
| We found no meaningful patterns in the types of marketing organizations that employ Account-Based Marketing (ABM) based on annual revenue. | T-Test | T=-1.023 | P=.307 | Cohen’s d=-.088 | 550 |
| We found no meaningful patterns in the types of marketing organizations that employ Account-Based Marketing (ABM) based on solution prices. | T-Test | T=-.751 | P=.453 | Cohen’s d=-.063 | 573 |
| We found no meaningful patterns in the types of marketing organizations that employ Account-Based Marketing (ABM) based on buyer company size (small, medium, large). | Chi-Squared | X2=3.441 | P=.179 | n/a | 573 |
| 74% of organizations indicated that they prioritize accounts with multiple leads. | Frequency | n/a | n/a | n/a | 552 |
| Most marketers, even those not using Account-Based Marketing (ABM) practices, seem to recognize and give priority to buying groups, although the difference wasn’t statistically reliable enough to allow us to infer that trend exists among marketers outside of our sample. | Chi-squared | X2=14.23 | P=.07 | X2=14.23 | 552 |
| We found that marketers who prioritize buying groups report a 4% better financial performance compared to those who don’t. | ANOVA | ANOVA | P=.021 | N2=.014 | 552 |
| On average, marketers use three to four different sources for account and contact information. | Average | n/a | n/a | n/a | 539 |
| Our survey found that only 31% of marketers de-anonymize their web traffic, with a mere 11% finding it useful. | Frequency | n/a | n/a | n/a | 546 |
| While product review site leads and social media leads are used by over 40% of marketers, they’re deemed useful by only 25% or fewer. | Frequency | n/a | n/a | n/a | 546 |
| Third-party intent data, despite being a rich intelligence source, is employed by just 29% of marketers, with only 12% finding it useful. | Frequency | n/a | n/a | n/a | 546 |
| Most organizations only use between five and six signal types out of the 23 we asked about. | Frequency | n/a | n/a | n/a | 574 |
| Companies with multiple go-to-market strategies employ more signals than those with just a single strategy. | ANOVA | F=22.118 | P<.001 | N2=.135 | 573 |
| Private equity-backed (PE-backed) firms tend to gather more signals compared to their counterparts in companies with alternative funding structures. Marketers at private, public, and venture capital firms, on the other hand, gather statistically equivalent numbers of signals. | ANOVA | F=2.623 | P=.05 | N2=.014 | 574 |
| Small to mid-size organizations report using more types of signals than larger companies do. Those with revenue between $50M and $250M report collecting 8 to 9 types while those above $250M report collecting around 5 to 7 types. | ANOVA | F=16.425 | P<.001 | N2=.108 | 550 |
| ABM practitioners are more likely to collect signals that are computed, such as account or intent activity scores, than those who do not practice ABM. | T-test | T=4.770 | P<.001 | Cohen’s d=.413 | 558 |
| ABM practitioners are more likely to collect more anonymous signals than those who don’t practice ABM. | T-test | T=4.484 | P<.001 | Cohen’s d=.390 | 558 |
| Marketers who practice Inbound marketing are more inclined to use signals that indicate the activity of identified individuals than those who don’t practice inbound. | T-test | T=3.46 | P<.001 | Cohen’s d=.312 | 558 |
| Inbound marketers utilize raw signals (e.g., a form fill) more than peers that do not practice Inbound marketing. | T-test | T=2.98 | P=.003 | Cohen’s d=.269 | 558 |
| Inbound marketers utilize computed signals (e.g., lead scores) more than peers that do not practice Inbound marketing. | T-test | T=2.37 | P=.018 | Cohen’s d=.213 | 558 |
| The go-to-market strategy associated with the highest level of budgeting was those practicing ABM only, followed by those practicing Inbound and those practicing Outbound only. | ANOVA | F=12.815 | P<.001 | N2=.086 | 549 |
| Organizations that allocate more of their company revenues to marketing also report better financial performance. | Correlation | r=.259 | p<.001 | Fisher’s z=.263 | 549 |
| Organizations that allocated more of their company revenues to marketing also report higher satisfaction with ABM. | Correlation | r=.357 | p<.001 | Fisher’s z=.374 | 232 |
| Organizations that allocated more of their company revenues to marketing also report higher satisfaction with Inbound Marketing. | Correlation | r=.235 | p<.001 | Fisher’s z=.240 | 369 |
| Organizations that allocated more of their company revenues to marketing also report higher satisfaction with Outbound Marketing. | Correlation | r=.256 | p<.001 | Fisher’s z=.262 | 321 |
| According to our survey respondents, around 40% of the total marketing budget is allocated to these strategies, whether individually or in combination. | Average | n/a | n/a | n/a | 574 |
