LinkedIn published a guide on June 3, 2026 arguing that B2B marketing measurement has reached a structural breaking point - one where the tools exist but organizational trust in the data they produce does not.

The guide, titled The Future of B2B Marketing Measurement, draws on interviews with senior marketing leaders at Microsoft, ServiceNow, Xero, PwC Germany, Dassault Systemes, Personio, Plaid, Cegid, and Alma. It organizes their observations around five trends that, according to LinkedIn, are reshaping how B2B marketers connect campaign activity to revenue.

The backdrop is a data point from Forrester: about 64% of B2B marketing leaders say their organizations do not trust the measurement methods currently in use for decision-making. That figure, cited by LinkedIn in a June 3 blog post accompanying the guide, frames the rest of the document's argument. The problem is not a shortage of data. It is a gap between what the data says and what leadership is willing to act on.

The shift from cost metrics to revenue metrics

The most consistent theme running through the guide is the inadequacy of cost-based metrics as a language for communicating marketing's value to the rest of a business. Impressions, clicks, cost per click, cost per lead - these are the vocabulary of media buying, not of revenue strategy. According to LinkedIn, marketing leaders are increasingly frustrated by this gap.

Vivek Khandelwal, Director of Digital Acquisition, Strategy and Operations in Asia Pacific and Japan at ServiceNow, put it directly in the guide: "In general, our philosophy is, 'let's go beyond media metrics'. You can talk about click-through rate, cost per click and cost per impression all day long, but what eventually matters to the business are the revenue metrics. It's all about how many customers we're winning, how many opportunities we're creating for the business and the ROI that we're generating on marketing investments."

This orientation toward revenue is not simply philosophical. It has practical implications for which KPIs marketing teams track, how they communicate with finance and sales, and how budgets get defended. The guide describes a structural shift: reporting on KPIs that correlate with revenue in a clear and consistent way, at a rate that both sales and finance departments can treat as credible.

The role of Marketing Qualified Leads in this framework is contested. Alex Venus, Performance Marketing Senior Lead at Personio, noted in the guide that the MQL definition has become diluted to the point where conversion rates vary from 4% to 20% or more within the same organization. According to Venus, Personio's north star metric is qualified pipeline - specifically, opportunities that sales teams care about and that convert at a rate of 25% or higher. That is a markedly different standard than an MQL, and the difference matters when presenting to a Chief Revenue Officer.

Alex Young of Plaid, the financial data network, added a longer-term dimension: the ratio of customer lifetime value (LTV) to customer acquisition costs (CAC). "We work really closely with our analytics team to get the full picture of the revenue we're getting from specific customers over time, because the number can change quite drastically between Day One and two or three years down the line." That kind of long-range view is exactly what cost-per-click reporting cannot provide.

Separating brand from performance measurement

The second trend the guide identifies is the growing demand from senior leadership - including CFOs - for financial visibility into brand marketing, not just performance campaigns. This is a harder problem than it sounds. Brand investment operates on a different timescale than direct response, and traditional metrics like ROAS (Return on Advertising Spend) and CPA (Cost Per Acquisition) are poorly suited to capturing it.

Lucas Riedberger, Digital and Media Director for the 3DEXPERIENCE innovation platform at Dassault Systemes, described the tension with precision: "The value of a brand is very important to any Chief Financial Officer. As a marketer, I can explain to them that the money we put into these campaigns has direct value in terms of the capitalization of the brand - the amount that we'll receive if we sell a brand to another company. The challenge is that it's difficult to put numbers behind that."

Valerie Kile, Performance Marketing Manager at Alma - a therapist support network - described the practical solution her team has adopted: "A big move for us has been separating out the measurement approaches for brand awareness and lead generation. You can't make a case for brand in terms of return on advertising spend and cost per acquisition. The impact is seen in different ways. Separating the two means that we're able to focus on optimizing our lead budget for ROAS, whether that's finessing messaging or adjusting where the budget gets spent."

Guillermo Novillo, Director of Integrated Marketing for LATAM at Microsoft, framed it as a problem without a current industry standard: "Part of the reason why people have questioned the value of brand marketing is that we haven't found a way to standardize the way that we assess impact. I would love to see more of a framework emerging for how you connect branding to business outcomes, and I think that's something that will start to happen."

Alex Long at Plaid raised the technical limit: building account-level awareness metrics that can be tied back to deal activity, rather than trying to force brand investment into a performance measurement model it was never designed to support.

The attribution problem and the end of last-touch

Attribution - assigning credit for a sale to the campaigns and channels that contributed to it - has always been complicated in B2B. According to the guide, proliferating digital channels and longer buying cycles are making it more so. The specific failure mode the guide focuses on is last-touch attribution: the habit of crediting whichever campaign interaction happened just before a conversion, regardless of the full sequence of touchpoints that preceded it.

Julien Harazi, Head of Lead Generation at Cegid, described the contemporary B2B buyer journey as a tangle: "As B2B marketers, our world has become a lot more complicated. All of the touchpoints are intertwined and it can be difficult to understand the buyer journey and identify where the value comes from in terms of your marketing. As a business, we've prioritized investing in an attribution model so that we can build this type of understanding."

ServiceNow's Khandelwal described using machine learning models to distribute credit across all relevant touchpoints, rather than concentrating it on the last one. That approach has practical consequences: it changes which channels appear to be contributing to revenue, and therefore how budgets get allocated between brand awareness and direct response.

The complexity goes further still. The guide notes that in B2B contexts, the person a campaign influences is frequently not the same person who shows up as the buyer. A junior employee might compile a vendor shortlist; a manager narrows it; a CFO signs off. Each step represents a marketing influence that standard attribution models will miss entirely. According to the guide, "the impact of any piece of marketing will always be bigger than what you can measure."

Julian Sappelt, Senior Manager at PwC Germany, described his team's response: doubling the sales pipeline value attributable to marketing for four consecutive years, while simultaneously acknowledging that untracked business exists above that figure. PwC Germany is exploring AI algorithms to identify and account for that untracked value - a long-term measurement project rather than a solved problem.

Measuring across three timeframes simultaneously

The guide's fourth trend addresses what is perhaps the most operationally demanding shift: running three different measurement models in parallel, each calibrated to a different timescale.

According to LinkedIn, the practical framework looks like this. Immediate metrics - cost per click, engagement rates - are used for real-time in-flight optimization. Short-term metrics, covering three to twelve weeks, track ROAS at the campaign or channel level and their impact on pipeline. Long-term metrics, running twelve months or more, use customer lifetime value as the primary variable and incorporate all forms of marketing investment, including salaries and overhead.

Khandelwal described the operational version at ServiceNow: "The first question is how do we measure and optimize campaigns, and for that we look at things like cost per qualified lead, which can operate in near real-time. In the medium term, we look at pipeline created over three to 12 weeks, and we divide that by the total marketing investment. Then, over a longer-term timeframe, we look at closed-won deals and make long-term investment decisions."

The distinction between ROAS and ROI matters here. According to LinkedIn's guide, ROAS isolates the impact of specific campaigns or channels, while ROI aggregates total marketing investment - including people costs - against total returns. In practice, the guide argues, blurring this distinction is often useful, particularly when understanding how campaigns work together rather than in isolation. Kile at Alma described calculating both individual platform ROAS and blended ROAS across all channels simultaneously, treating them as complementary rather than competing views.

Alex Venus at Personio offered a framing that cuts through the complexity: "The sophisticated approach is to look at measurement as a coverage model rather than a calendar. You want to make sure that you're not just generating pipeline and opportunities but you have a really healthy funnel - that you are generating new opportunities all the time, and that your opportunities are ultimately converting. I look at it as a rolling model and I think that's a really effective way of having actionable conversations with sales leaders."

Real-time data integration: the 360-degree problem

The fifth and final trend is data integration. According to the guide, marketers have more data sources than ever - platform dashboards, CRM systems, marketing automation tools, business intelligence platforms. The challenge is not the volume of data but the coherence of what it says when combined.

Sveta Freidman, Global General Manager of Data and Analytics at Xero, described the ideal that most organizations are still trying to reach: "What we really need is a tool that can provide a single, 360-degree view of the customer. To achieve that, you need to be able to connect your first-party data with behavioral and offline data, in order to create a better customer experience and more effective acquisition. We're working with platforms like LinkedIn to help us achieve that integration."

Harazi at Cegid described a technical architecture that gets closer to that goal: "There's a magic triangle between marketing automation, CRM and business intelligence, and connecting those things together is the key to measuring effectively. Our marketing automation and CRM have about 300 fields in common, and so updates on one can be automatically made to another."

Alex Venus at Personio described the practical tools his team is using: Dreamdata, a third-party attribution platform that imports conversion data and stitches it together with anonymized LinkedIn data. The goal, according to Venus, is a single platform covering both the top and bottom of the funnel - though he acknowledged that the industry is not there yet. According to Alexandra Long at Plaid, real-time dashboards provide an internal view but they "only tell us half the story," because GDPR constraints mean not all relevant signals can be pulled into a single dashboard.

Why this matters for marketing teams

The broader context here is one that PPC Land has tracked closely across several recent reporting cycles. Dreamdata's March 2026 benchmarks, covering more than 3.5 million complete customer journeys, found that B2B buying cycles now average 272 days. LinkedIn accounts for 41% of total B2B paid media budgets in those data sets. That combination - long buying cycles, heavy platform concentration - is precisely the environment where the measurement failures this guide describes become most expensive. A 272-day sales cycle cannot be evaluated against a 30-day reporting window without losing the majority of what actually happened.

LinkedIn's Revenue Attribution Report, first introduced in September 2024, was designed to address part of this gap. The platform enhanced it in July 2025 with company-level attribution, allowing marketers to track how entire organizations engage with campaigns across paid and organic touchpoints - not just individual leads. In September 2025, LinkedIn launched its Company Intelligence API, extending those company-level capabilities to third-party attribution platforms. Early beta data showed a 287% increase in companies reached when combining organic and paid touchpoints, and a 96% increase in pipeline attributed to marketing.

The Forrester finding that 64% of B2B marketing leaders distrust their measurement methods is, in that context, not primarily a technology gap. It is a credibility gap - one between what marketers know their campaigns are doing and what they can demonstrate to a CFO or a Chief Revenue Officer. The five trends the guide describes are, at root, five different attempts to close that gap.

Timeline

Summary

Who: LinkedIn, with contributions from senior marketing leaders at Microsoft, ServiceNow, Xero, PwC Germany, Dassault Systemes, Personio, Plaid, Cegid, and Alma.

What: A 26-page guide titled "The Future of B2B Marketing Measurement," identifying five trends reshaping how B2B organizations connect marketing activity to revenue: connecting all measurement to revenue, developing ROI frameworks for brand marketing, moving beyond last-touch attribution, measuring simultaneously across multiple timeframes, and integrating data sources into a real-time 360-degree view of the buyer journey.

When: Published June 3, 2026, supported by Forrester research and interviews with B2B marketing leaders across multiple industries and regions.

Where: Published on LinkedIn's marketing blog and distributed as a downloadable guide through LinkedIn Ads channels. Contributors are based across Asia Pacific, LATAM, EMEA, and North America.

Why: According to Forrester research cited by LinkedIn, 64% of B2B marketing leaders report their organizations do not trust the measurement methods currently used for decision-making. The guide argues that the credibility gap between what marketers can demonstrate and what finance and sales leadership will accept is the central constraint on marketing's influence inside organizations - and that closing it requires moving away from cost-based metrics toward revenue-based ones, supported by more sophisticated attribution technology and integrated data infrastructure.