TL;DR
- Factors.ai, a LinkedIn Marketing Partner, reports that reaching 6+ contacts before a CRM deal exists lifts win rates 17 points, and 3+ more during the active cycle adds 16 points.
- The strongest role mix in the report, internal end users plus influencers plus technical evaluators, is linked to a 22 percentage point win-rate lift.
- Factors.ai found 76% of LinkedIn ad spend targets director-level through owner roles, and pairing LinkedIn Ads with organic activity showed 2.4x higher win rates than ads alone.
- LinkedIn's 24 September 2026 post gives no baseline win rates, controls, time period or country breakdown, so the lifts are vendor-reported correlations.
LinkedIn published research on 24 September 2026 claiming that B2B buyers start researching roughly 124 days before they speak to a seller, and that vendors who reach more of the buying committee early win noticeably more deals. The figures come from a Factors.ai report titled "From Benchmarks to Blueprints: The LinkedIn Revenue Engine for B2B", which LinkedIn says draws on more than 850 B2B companies, 50,000+ closed deals and over $5 billion in deal value. Factors.ai is a LinkedIn Marketing Partner, and the conclusions point toward spending more on LinkedIn, so the numbers are best read as vendor-reported correlations rather than independent proof.
What LinkedIn published and who wrote it
The article ran on the LinkedIn Marketing Blog on 24 September 2026 under the byline of Greg Willis, with the headline "The Biggest B2B Marketing Mistake? Reaching Too Few, Too Late." Willis opens with the questions he says marketing leaders keep asking him: when the buyer journey actually begins, which stakeholders matter most, how early marketers should engage accounts, and how to measure impact when so much of the buying process happens before a lead ever appears in the CRM.
His answers come almost entirely from the Factors.ai report. LinkedIn summarises the report's conclusion this way: winning companies engage buyers earlier, reach more of the buying committee, and combine paid and organic strategies. The post then states that LinkedIn is "uniquely positioned" to help with all three, and it closes by inviting readers to contact a LinkedIn Ads specialist. That framing matters for everything below. This is a platform publishing research from one of its own marketing partners, and the research argues for more investment in the platform.
None of that makes the figures wrong. It does mean the reader should separate three things: what Factors.ai measured, what LinkedIn chose to highlight from it, and what a marketer can actually conclude for their own pipeline.
The headline numbers from the Factors.ai report
The table below lists the main figures LinkedIn attributes to Factors.ai in its 24 September 2026 post and what each one is said to measure.
| Finding reported by LinkedIn | Figure | What it measures |
|---|---|---|
| Research before the first seller conversation | About 124 days | Time buyers spend researching, evaluating and discussing solutions before speaking to a seller |
| 6 or more contacts reached before a CRM deal exists | +17 percentage points | Win-rate lift |
| 3 or more additional contacts engaged during the active cycle | +16 percentage points | Win-rate lift |
| Engaging internal end users, influencers and technical evaluators together | +22 percentage points | Win-rate lift, the strongest role mix in the study |
| LinkedIn Ads paired with organic LinkedIn activity | 2.4x | Win rate compared with paid campaigns alone |
| LinkedIn ad spend aimed at director-level through owner roles | 76% | Concentration of targeting on senior titles |
The post also reports three budget and return figures, covered further down: LinkedIn Ads take 39.8% of B2B display budget share, LinkedIn-sourced deals close at a 34% higher average contract value, and LinkedIn returns 1.6x on ad spend against 1.18x on Google.
The 124-day research window
Most go-to-market teams date the buying cycle from the day an opportunity is created in the CRM. According to Factors.ai, as reported by LinkedIn on 24 September 2026, buyers begin researching, evaluating and discussing solutions around 124 days before they speak to a seller. LinkedIn adds that "much of the activity happens on LinkedIn", which it describes as four months of research, comparison and internal discussion before a sales team knows an opportunity exists.
The argument that follows is about demand capture. Forms, demo requests and lead-scoring models are built to catch buyers once they are ready to act. If preferences are forming four months earlier, LinkedIn argues, a strategy built only on capture is reacting to a decision that is already well underway rather than shaping it.
The reasoning holds up as a general point about long B2B cycles. The specific number needs more context than the post gives. The article does not say whether 124 days is a median or an average, how the start of research was detected for each account, or how much the figure varies by deal size, industry or region. It also does not quantify "much of the activity happens on LinkedIn". A report built on LinkedIn engagement data will, almost by design, see research activity where LinkedIn can observe it, so that sentence is hard to test from the outside.
Buying committee reach and win rates
The finding LinkedIn leans on hardest is about breadth. Factors.ai found that reaching 6 or more contacts before a deal is created in the CRM lifted win rates by 17 percentage points, and engaging 3 or more further contacts during the active sales cycle lifted them by 16 points. The post does not say whether those two effects stack.
LinkedIn connects this to Forrester research, which it quotes as finding that a typical buying decision now involves 13 internal stakeholders and nine external influencers, with the number rising for complex or strategic purchases. The post gives examples of how priorities differ across that group: a CFO wants proof of ROI, an IT leader wants secure integrations, an internal end user wants ease of use, and everyone wants reassurance that peers trust the vendor. The Forrester figure is LinkedIn's citation; the Forrester study itself was not part of the source reviewed for this article.
Against that, Factors.ai found that 76% of LinkedIn ad spend explicitly targets director-level through owner roles. LinkedIn's reading is that concentrating on senior decision-makers may leave other members of the committee under-engaged.
Who you reach matters as much as how many
The post is explicit that headcount alone is not the goal. Engaging six people from the same function, it says, does not deliver the same impact as engaging a mix such as an executive sponsor, an influencer and a technical evaluator. The strongest result in the report came from engaging a combination of internal end users, influencers and technical evaluators, which Factors.ai associates with a 22 percentage point increase in win rates.
For an advertiser, this is the most practical line in the piece. It suggests auditing LinkedIn targeting by role and seniority, not only by company list, and checking whether end users and technical evaluators ever see the brand before a sales conversation starts.
Why the win-rate lifts need careful reading
The lifts are correlations reported by the vendor. The post does not describe controls, and several alternative explanations fit the same pattern. Accounts where a vendor reached more people may simply be larger, better-fit or already more interested. Deals that are going well tend to pull more stakeholders into the conversation, which would push the contact count up as a result of winning rather than a cause of it. The post also does not state the baseline win rate the lifts are measured against, how a contact counted as "reached" or "engaged" (an ad impression, a click, a page follow or a sales touch), or what window of deals was analysed.
The units matter too. A 17 percentage point lift on a 20% baseline would be a very large relative change; on a 50% baseline it is a smaller one. Without the baseline, the reader cannot tell which.
Paid plus organic: the 2.4x figure
According to Factors.ai, companies that pair LinkedIn Ads with organic LinkedIn activity achieve 2.4x higher win rates than those running paid campaigns alone. LinkedIn explains this through what it calls buyability: ads put a brand in front of the right buyers at scale, while organic content such as thought leadership posts, executive commentary and Company Page activity builds credibility over time. Buyers, the post says, do not experience the two separately. They see an ad, then visit the Company Page, or read an executive's post and see a retargeting ad a few days later.
The same caution applies. Companies that run both paid and organic programmes on LinkedIn are likely to have bigger or more mature marketing teams, stronger brands and more budget, any of which could explain part of the gap. The post does not say whether Factors.ai adjusted for company size or spend. It also does not define how much organic activity counted as "pairing".
LinkedIn's share of B2B budgets and returns
LinkedIn reports three further Factors.ai figures. LinkedIn Ads now command 39.8% of B2B display budget share, up 8 percentage points since 2024. LinkedIn-sourced deals close with a 34% higher average contract value than deals sourced from other platforms. And LinkedIn delivers a 1.6x return on ad spend compared with 1.18x on Google.
These are the figures most likely to be quoted in budget meetings, and the ones with the least supporting detail in the post. It does not define "B2B display budget", which platforms sit in the denominator, or which attribution model decides whether a deal was "LinkedIn-sourced". The Google comparison does not say whether it covers search, display, YouTube or all Google inventory, or what attribution window was used. Return on ad spend in B2B is highly sensitive to those choices, because deals close months after the first click. A higher contract value on LinkedIn-sourced deals may also reflect the senior, large-company audience LinkedIn targeting tends to reach rather than the channel itself.
What the source did not say
The following details were not stated in LinkedIn's post and should be treated as unknown until the full report is checked:
- The time period the 50,000+ deals were closed in.
- The industries, company sizes and regions of the 850+ companies, including whether any are in Asia-Pacific or Thailand.
- How contacts were matched to accounts and deals, and what counted as engagement.
- Baseline win rates, sample sizes behind each lift, and any statistical controls.
- The attribution model behind "LinkedIn-sourced" deals and the ROAS comparison with Google.
The post links to a Factors.ai landing page for the full report. This article is based only on LinkedIn's summary; the full report was not part of the source reviewed here.
How to test the claims against your own data
The useful thing about these findings is that most B2B advertisers can check them against their own CRM rather than taking them on trust. As analysis, four checks follow directly from what the post claims:
- For closed-won and closed-lost deals over the past year, count distinct contacts at each account who engaged with marketing before the opportunity was created. See whether the gap looks anything like the 17 point figure.
- Tag those contacts by role (executive, end user, technical evaluator, influencer) and compare the role mix on won deals against lost ones.
- Pull the share of your own LinkedIn spend that targets director level and above, and compare it with the 76% benchmark.
- Measure the gap between an account's first recorded engagement and opportunity creation, and compare it with the 124-day figure.
All four depend on clean tracking: consistent UTM tagging, CRM contact-to-account matching and an agreed attribution model. If that plumbing is weak, analytics and tracking setup is the first job, before any budget shift.
What this means for Thai marketers
Nothing in LinkedIn's post says the Factors.ai data covers Thailand, and the figures should not be presented to Thai stakeholders as local benchmarks. The underlying pattern is still relevant as analysis. Thai B2B firms that sell to multinationals, manufacturers, technology buyers or professional-services clients often face committee decisions and long evaluation periods, and LinkedIn is one of the places those committees can be reached.
Two practical points follow. First, LinkedIn targeting in Thailand that sticks to director and owner titles may miss the engineers, procurement staff and end users who shape a shortlist; testing broader role targeting, measured by pipeline rather than clicks, is a reasonable experiment. Second, paid campaigns that point to an empty Company Page or silent executives leave the "paid plus organic" half of the argument unused, so a steady content marketing programme in Thai and English can support the ads. Neither needs the 2.4x figure to be exactly right to be worth trying.
FAQ
How long do B2B buyers research before contacting sales, according to Factors.ai?
About 124 days, according to Factors.ai research published by LinkedIn on 24 September 2026. The post does not say whether that is a median or an average, or how it varies by industry or deal size.
Does reaching more contacts actually cause higher win rates?
The source does not show that it does. The 17 and 16 percentage point lifts are correlations reported by Factors.ai, and the post does not describe baselines or controls, so larger or already-interested accounts could explain part of the difference.
Is this research independent of LinkedIn?
No. Factors.ai is a LinkedIn Marketing Partner, and LinkedIn published the summary on its own marketing blog with a call to contact a LinkedIn Ads specialist.
Does the Factors.ai data include Thai companies?
The source does not say. LinkedIn's post gives no breakdown of the 850+ companies by country, region or industry.
Should I move budget from Google to LinkedIn because of the 1.6x ROAS figure?
Not on this evidence alone. The post does not state the attribution model or which Google inventory the 1.18x comparison covers, so the safer step is to compare both channels in your own pipeline data first.
The core idea in the report, that B2B deals are shaped by many people well before sales gets involved, is sound and easy to test. The specific multipliers deserve scepticism until the methodology is visible. If you want help building LinkedIn campaigns that reach the wider buying committee and measuring them against real pipeline, see our social ads service.
