Key Takeaways
- Independent measurement gives B2B marketers and CFOs a shared, finance-ready view of performance by tying channel spend to pipeline and closed revenue instead of relying on platform-reported ROAS.
- To make measurement actionable, teams need clean, connected data, clear cross-channel ownership and human oversight on budget decisions even as AI helps with insights, forecasting and scenario planning.
Your CFO wants proof. Your ad platforms want credit. Those two rarely line up. According to Lifesight’s The State of Unified Marketing Measurement Report, based on research from Winterberry Group, 93% of brands rely on platforms that grade their own homework. That means the LinkedIn, Google and programmatic dashboards you report from are run by the same companies selling you more media.
When finance asks what last quarter’s paid social spend actually delivered, platform-reported ROAS won’t hold up in the room. Unified measurement replaces those competing claims with one independent view of what drives revenue, and it gives marketing and finance the same numbers to work from.
The gap is even wider in B2B. Deals take months to close, buying committees spread decisions across the organization, and the touchpoints that move pipeline, like events and sales conversations, often sit outside digital tracking entirely. The report finds that brands use nearly five different measurement approaches with no unifying layer to connect them. For B2B teams, that adds up to more metrics, fewer clean signals and budget conversations that stall before a single dollar moves. Meanwhile, the next planning cycle is already on the calendar.
Jonathan Margulies, managing partner at Winterberry Group, has studied how brands measure, where they fall short and what separates the teams that get real value from measurement. In this Q&A, Margulies shares practical guidance for B2B marketing leaders on building an independent measurement layer that ties every channel to pipeline and closed revenue, closing the cross-channel allocation gap and making your data AI-ready so sales and finance trust the recommendations it produces.
B2BMX Insights: Lifesight’s report finds that 93% of brands rely on platforms that grade their own homework. For B2B marketers whose pipeline depends on LinkedIn, Google and programmatic partners, what does an independent measurement layer look like in practice, and how should CMOs present the case for one to their CFOs?
Jonathan Margulies: An independent measurement layer has to satisfy three requirements. First, it has to ingest spending and campaign data from every channel–LinkedIn, Google, programmatic, events–and incorporate that information into a central database. (Given that 82% of the brands we surveyed already use a data warehouse such as Snowflake or BigQuery, most teams likely already have what they need.) Second, it should support the linking of that spending data to customer and transactional data–records of opportunities, pipeline and closed revenue–so that every channel can be judged on the business results it produced. Third, it should enable analysts to use various methods—marketing mix modeling, holdout tests, etc.—to estimate how much incremental revenue each channel actually powered.
To win over their CFOs, CMOs should start with the shared problem — that neither team can fully trust platform-reported return on ad spend (ROAS) — and present independent measurement as the solution. Propose a common set of metrics tied to incremental revenue and defined in collaboration with finance, then test the approach against a single budget decision, such as next quarter’s paid social spend. If the results give finance a clearer picture of what that investment actually delivered, the CMO has a stronger case for extending independent measurement across the full media plan. Over time, both teams can use the same numbers to guide investment decisions, and budget conversations move faster.
B2BMX Insights: The report states that brands use nearly five different measurement approaches with no unifying layer. In Winterberry Group’s research, is this fragmentation more pronounced in B2B organizations, where long sales cycles and buying committees already complicate attribution?
Margulies: Yes, I’d absolutely expect fragmentation to hit B2B organizations harder. B2B purchases can take months to close, making it difficult to connect what spend drove revenue. Buying committees also spread out decisions across an org. And many of the most consequential touchpoints that move deals forward, like events and sales conversations, fall outside most digital tracking. So B2B teams often get left with a whole variety of methodologies and metrics to reconcile–and fewer clean signals as their output.
How Do B2B Marketing Teams Turn Measurement Into Cross-Channel Budget Decisions?
B2BMX Insights: Cross-channel allocation ranks as the largest capability gap in the report. What’s preventing B2B marketing teams from shifting budget confidently between channels such as events, paid social, ABM programs and content syndication, and which organizational changes close that gap fastest?
Margulies: Without a shared way to compare channels, B2B marketing teams struggle to move budget confidently. Events get judged on leads and meetings, paid social on platform conversions, ABM on account engagement and content syndication on cost per lead. Because none of those metrics translate into one another, a team can’t compare a dollar spent on an event with a dollar spent on LinkedIn ads. The team has no evidence that moving money from one channel to another will pay off. Plus, because channel budgets often belong to different teams, moving money means someone has to give something up. There’s no shared evidence on what is actually driving revenue, so budget conversations stall.
To close the gap, marketing and finance should agree on a shared outcome, ideally incremental pipeline or revenue, so teams can compare channel performance on the same basis. Then, teams should establish a regular budget review with an opportunity to reallocate spend as new evidence emerges. Assigning a single owner with authority over cross-channel budgets helps expedite decision-making and budget allocation.
B2BMX Insights: According to the report, 69% of brands need help translating measurement results into budget decisions. Is this a skills problem, a tooling problem or a governance problem, and who inside a B2B organization should own that translation?
Margulies: I’d actually argue that the problem spans all three. Currently, the skills aren’t there yet. Only 18% of brands say they have all the people and expertise they need to meet their measurement goals. As one retail EVP told us, “For us, technology is not the constraint here. It’s talent. Good measurement people are difficult to find and harder to retain.”
But even with talent, tooling can still be a problem for marketing teams. Many measurement models produce outputs that read like reports. They stop short of recommendations. And without someone with clear authority to act on a model’s recommendations, a strong team with good tools stalls when making risky or experimental budget decisions.
If an organization is going to avoid this, it needs a measurement or marketing analytics leader who reports to the CMO and works closely with finance to assess output and translate results into recommendations. From there, the CMO should own the final budget decision, with finance approving the metrics used to measure success. With those roles clear, outside partners can add capacity where the organization needs it most.
B2BMX Insights: The report finds that 74% of brands need help interpreting results, forecasting outcomes, recommending reallocations and pushing approved changes back to ad platforms. How should marketing leaders decide which of those steps to automate and which to keep under human judgment?
Margulies: Marketing leaders should start automating the steps where the evidence is strongest and the cost of an error is the lowest. Our research found that, of the 79% of brands that use AI in measurement, 85% are using it to generate insights and summarize results, 77% use it for forecasting and scenario planning and 74% use it to prepare data. All three of those are sensible places to automate because every output can be checked, and mistakes are easy to catch before they waste budget. But when it comes to budget recommendations and strategy execution, keep a human involved. People should still own what gets measured, which metrics matter most and what the business should do next.
How Should B2B Marketers Prepare Their Data for AI and Faster Measurement Models?
B2BMX Insights: The report identifies data quality, integration and trust as the barriers holding back AI adoption in measurement. What steps should B2B marketers take in the next 12 months to make their data AI-ready, and how can they build trust in AI-generated recommendations with sales and finance stakeholders?
Margulies: AI recommendations are only useful if the underlying data is reliable, and poor data quality was cited as the most significant barrier (55%). In light of that, B2B marketers should start by fixing any data quality issues and reconciling conflicting numbers across marketing and revenue systems. Causal marketing mix modeling can then help identify which channels drive incremental pipeline and revenue, while incrementality tests provide a way to check those findings against actual results. Connecting the measurement to the systems teams use to plan and buy media puts that evidence within reach when budget decisions come up.
Sales and finance are more likely to trust AI recommendations when they can see the reasoning behind them. Marketers should be able to explain which data and test results support a proposed budget change. Before expecting sales and finance to be on board, test out AI recommendations on smaller decisions and track the impact. As the results come in, teams can expand or limit AI’s role. Executive approval for budget shifts above a set threshold also gives stakeholders a clear say in higher-stakes decisions.
B2BMX Insights: Traditional consultancy marketing mix modeling often arrives months after the fact, while the report argues that unified measurement should deliver causal insights in days. For B2B teams planning annual budgets, how much does speed actually change decision quality, and where does a faster model introduce new risks?
Margulies: Speed improves decision quality when it gives B2B teams a more up-to-date view of channel performance, allowing them to adjust spending before the next annual planning cycle. While annual budgets establish an initial plan, channel performance, costs and market conditions can change significantly throughout the year. More frequent measurement lets teams identify those changes and reallocate spending while there’s still time to influence results. Our research supports this approach: Organizations that get the most from measurement test, learn and reallocate within weeks.
But faster feedback doesn’t always mean better decisions, particularly in B2B, where long sales cycles delay the revenue impact of marketing spend. A model that updates too quickly may favor channels that generate immediate activity over those that contribute to revenue months later. It can also mistake short-term fluctuations for meaningful changes in performance. If the model relies on correlation rather than causal evidence, faster updates only make it easier to act on misleading conclusions.
What Results Can B2B CMOs Expect From Unified Measurement, and What Will It Take?
B2BMX Insights: The report cites an average sales lift of roughly 9.8% for brands using unified measurement and notes that Seidensticker generated 11.8% more revenue on 11.7% less spend after reallocating budget based on causal evidence. What benchmarks should B2B CMOs consider realistic, and how should they set expectations with leadership before results arrive?
Margulies: B2B CMOs should first benchmark against their own baseline and avoid anchoring to the 9.8% average lift cited in the report. Realistic gains depend on how effectively current budgets drive revenue, the company’s channel mix and the length of its sales cycle.
Before results arrive, align leadership on what success looks like, what the timeline will be to measure it and what the findings will inform. It could take time to see results. Given the length of the sales cycle in many B2B companies, incremental pipeline will likely show impact sooner than revenue. Teams may also need to adjust to what they’re seeing and reallocate spend before a revenue lift becomes visible. Agreeing on these milestones up front gives leadership a concrete way to evaluate progress without promising a specific percentage gain.
B2BMX Insights: Modern measurement must meet standards such as GDPR, HIPAA, SOC 2 and ISO 27001, and the report devotes a full chapter to “The People Problem.” Looking ahead to 2027, which matters more for B2B marketers that want to close the unification gap: privacy-first data architecture or the team structure and talent needed to act on the results?
Margulies: Both matter, and they play different roles. Privacy-first data architecture is a requirement. Without it, a measurement program can’t scale, and in regulated categories, it can’t start to make an impact. As a rule of thumb, buyers should look for their measurement partners to meet standards like GDPR, HIPAA, SOC 2 and ISO 27001.
Talent will decide who excels in 2027, though. In our research, 73% of brands say measurement insights drive all or a substantial part of their marketing decisions, yet only 18% have all the people and expertise they need. Another 74% say they need outside help, most often to interpret results and translate them into budget or media recommendations. Marketing teams will increasingly need talent who can understand causal methods and partners who stand outside the walled gardens and add independent capacity. Architecture makes good measurement possible, but good people make it useful.
