DemandScience has recently unveiled a report that shows the extent that misleading marketing campaign metrics and over-complicated MarTech stacks are affecting businesses’ bottom lines.
In their The 2026 State of Performance Marketing: Exposing the Marketing Data Mirage, B2B marketing teams today are reporting strong campaign performance, rising engagement, and increasingly sophisticated measurement. The issue: is any of this translating into revenue.
The degree to which marketing teams invest in campaigns that yield promising intent signals, but fail to convert to revenue, is staggering. The marketing leaders surveyed in this research report estimated that an average of 25% of their marketing budget is spent on campaigns that look productive based on campaign metrics but do not drive revenue.
Report Overview
Conducted by an independent research firm, the report features an analysis of survey responses from 750 senior B2B marketing leaders of companies with revenues from $100 million to more than $5 billion. That pattern that has emerged is strong marketing performance is often a marketing data mirage, driven by misleading metrics, unreliable intent signals, and over-complicated MarTech stacks that obscure rather than clarify what is actually working.
“Marketers are working harder than ever, yet their campaigns are dragged down by signals, AI-generated content, and metrics that look promising on the surface but fail to translate into real outcomes,” said Bill Hobbib, CMO at DemandScience. “Too often, marketers see dashboards glow green, impressions scale, and lead goals exceeded, yet these “qualified” leads convert to customers at a low rate. The Mirage makes tactical execution look successful while masking the very issues that prevent revenue.”
The Impact of AI
Respondents reported that in the more than 85% of cases where sales teams acted on positive marketing intent signals, conversion rates remained “stubbornly low,” a significant challenge that CMOs and CFOs must overcome when it comes to measuring performance metrics that have a high probability of translating into sales.
The rise of AI in the last year contributed to a huge increase in the quantity of content marketing— 72% reported AI generated content hurt brand distinctiveness and 76% reported creating content that is not tied back to a data-driven strategy.
Marketers will continue to use AI for content generation, but as they do so, marketers need to ensure that the subject and quality of the content is helping rather than hurting, according to Demand Science officials.
Focus on MarTech Stacks
Two other findings from the report stand out:
- 85% of respondents reported spending more than half their time fixing problems than creating campaigns. The “problems” include cleaning data, reconciling disconnected systems, and troubleshooting underperforming campaigns.
- 79% stated MarTech costs are rising without any clear ROI improvement. Additionally, 66% reported using 11 or more marketing tools. Together, these stats show the extent to which martech bloat is having a negative effect on marketing teams’ performance.
In the coming year, marketing teams that want to perform better must work towards streamlining their tech stacks, with a focus on only implementing tools that are clearly delivering value in the form of leads that convert to revenue, according to DemandScience officials.
“While 25% of budget leaks away, respondents estimate they could unlock an additional 32% in annual revenue if their data, signals, content, and orchestration were more effective and connected,” said Derek Schoettle, CEO and chairman of DemandScience. “These potential gains are effectively hiding in plain sight. For organizations doing hundreds of millions or billions of dollars in revenue, the gains are extraordinary.”
