A new LinkedIn report shows how businesses are changing their approach to measuring marketing success.
The report, based on insights from leaders at Microsoft, ServiceNow, PwC, and other global firms, identifies five key trends reshaping measurement strategies.
1. Revenue-Centric Metrics
Marketers are now focusing more on revenue-related metrics instead of traditional cost-per-lead measures.
Leaders are adopting tools that sync CRM data with campaign engagement. These tools bridge the gap between marketing activity and business outcomes and show how specific efforts drive deals.
Other critical shifts include:
Marketing Qualified Leads (MQLs) are no longer the primary metric because their conversion rates are inconsistent.
There is a greater emphasis on “sourced pipeline,” which refers to deals generated by marketing, and “influenced pipeline,” which measures the effect of multiple touchpoints in marketing.
ServiceNow’s Vivek Khandelwal noted:
“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, and the ROI we’re generating on marketing investments.”
Personio’s Alex Venus emphasized:
“Our North Star metric is qualified pipeline, which means an opportunity that your salespeople care about, which should be converting at a rate of 25% or more.”
2. ROI Frameworks for Brand Marketing
CFOs now need proof that brand-building works financially. This means marketers must show how their awareness efforts lead to sales results.
The report reads:
“The emphasis is shifting from the cost of marketing outcomes to the value of those outcomes. For marketers, that means reporting on KPIs that correlate with revenue in a clear and consistent way – at a rate that both sales and finance can believe in.”
To justify brand spend, teams are:
Separating brand and demand budgets to optimize spending.
Running campaigns focused on specific high-value accounts, then tracking deal timelines for correlation.
Balancing engagement (e.g., branded search growth) with pipeline influence.
3. AI-Powered Attribution Models
B2B buying groups are getting larger, often including 6 to 10 members.
As a result, marketers are now using machine learning models instead of outdated last-touch attribution methods.