Measured has launched new Model Context Protocol (MCP) functionality, which allows marketers at enterprises to gain real-time insight into marketing performance data through well-known AI systems like ChatGPT, Claude, Gemini, among others.
This new integration aims to make it easier for marketers to access performance data across channels through the AI platforms they are familiar with by integrating Measured’s analytics right into those AI systems.
MCP is an open standard that enables AI applications to communicate with other data sources in real time. With this, customers of Measured can gain access to executive summary reports, performance data, and on-the-fly insights on their marketing data all while staying within their chosen AI interfaces.
The move highlights a rising industry trend of incorporating business analytics tools right into AI-based conversational workflows, thus making life easier for businesses in terms of accessing such platforms.
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“Marketing leaders are under constant pressure to move faster and make more confident business decisions that directly impact ROI,” said Trevor Testwuide, CEO of Measured. “By giving companies seamless, real-time access to our marketing performance data within gen AI platforms like ChatGPT and Claude, we’re removing friction and enabling leaders to get the intelligent insights they need instantly, without having to leave the environments where they’re already working.”
Now that the new MCP implementation has been deployed, marketers can easily access information on cross-channel campaigns simply by posing questions in plain English to gain insights immediately. This solution is geared toward fast tracking insights, making decisions quickly, and making performance information more accessible to all concerned parties.
The solution is powered by Measured’s incrementality intelligence framework, which the company says is built on more than 30,000 experiments conducted across over 200 brands. This data foundation enables marketers to access causal performance insights rather than relying solely on correlation-based analytics.
Measured’s MCP capabilities provide access to several core intelligence areas, including:
- Incrementality Intelligence Database featuring causal measurement data across industries, channels, and brands
- Omnichannel performance visibility across major advertising platforms within a unified environment
- Optimization insights that highlight marginal returns and incremental growth opportunities to support budget allocation decisions
The company believes embedding this intelligence into conversational AI tools will help marketing teams engage with data more naturally while improving operational efficiency.
“It’s going to benefit different levels of users,” said Zaw Lin Hteik, Head of Growth Acquisition, Otter.ai. “Our executives don’t live in the platform day to day, so being able to ask questions and get clean answers changes how often they actually engage with the data. And for our analysts, the response comes back already formatted, ready to analyze and make decisions off of. That’s real time saved.”
While the new integration expands accessibility through AI agents and conversational interfaces, Measured emphasized that its underlying methodology remains grounded in incrementality-based measurement principles. According to the company, all insights delivered through MCP continue to follow causal and validated analytical frameworks designed to improve transparency and trust in marketing performance reporting.
The launch also signals Measured’s broader push toward AI-powered enterprise marketing workflows. The company stated that future roadmap developments will include predefined AI skills, advanced optimization tools, benchmarking capabilities, and additional automated workflows to support more intelligent media planning and performance management.
As enterprises increasingly adopt generative AI for business operations, integrations that combine conversational interfaces with real-time analytics are expected to play a larger role in helping organizations improve speed, efficiency, and data-driven decision-making across marketing teams.