Artificial intelligence is reshaping marketing at every level, from audience targeting and personalization to budgeting, forecasting, and creative optimization. Yet for many enterprises, AI progress is constrained by a stubborn underlying problem: fragmented, unreliable, and inflexible data infrastructure.

While AI-powered tools continue to proliferate, most organizations still rely on legacy marketing measurement systems that were never designed for real-time decisioning, generative models, or autonomous agents. Data is siloed across channels, vendors, and teams, making it difficult to govern, unify, or activate intelligence at scale.

Marketing Evolution, long recognized as a pioneer in marketing analytics, is positioning itself at the center of this transformation. The company has announced new funding led by Insight Partners, a global software investor and existing backer. The investment is focused on accelerating product innovation and go-to-market expansion for Marketing Evolution’s AI-ready data infrastructure, purpose-built to unify, govern, and activate enterprise marketing data across AI-driven and agentic systems.

This milestone marks a strategic shift: from analytics provider to foundational data infrastructure platform designed for the next generation of marketing intelligence.

From Analytics Leader to AI-Ready Infrastructure Provider

Founded in 2000, Marketing Evolution built its reputation by helping brands measure and improve marketing ROI through advanced data science. Over time, it became clear that measurement alone was no longer sufficient for enterprises navigating increasingly complex and automated marketing ecosystems.

Customers needed:

• Unified data across channels and platforms

• Reliable, governed inputs for AI systems

• Faster insights and continuous learning

• Explainable intelligence, not black-box outputs

• Infrastructure that could support agentic decision-making

In response, Marketing Evolution began evolving its platform beyond analytics into a domain-specific, AI-ready data infrastructure for marketing.

This latest round of funding accelerates that transformation.

Why Marketing’s AI Transformation Depends on Data Infrastructure

AI adoption in marketing is often framed as a tooling problem. In reality, it is a data architecture problem.

Without adaptable and trustworthy data infrastructure:

• AI models produce inconsistent or biased results

• Automation is limited to narrow use cases

• Insights cannot be operationalized in real time

• Marketing systems fail to learn and improve continuously

Marketing Evolution is addressing what it describes as the most critical barrier in marketing’s AI transformation: building infrastructure that can reliably operationalize AI across the marketing ecosystem.

Rather than focusing solely on performance dashboards or attribution models, the company is building the data backbone and connective tissue required for an always-on, learning-based marketing system.

Insight Partners’ Strategic Support and Board Expansion

The funding round is led by Insight Partners, reinforcing long-standing confidence in Marketing Evolution’s direction.

As part of the investment:

• Rajiv Gihwala, Principal at Insight Partners, joins the Board of Directors

• He will serve alongside George Mathew, Managing Director at Insight Partners and an AI-focused leader

The board also includes experienced industry leaders such as:

• Andy Frawley, CEO of Data Axle and former CEO of Epsilon

• Lindsay Luger, Founding Partner at EIP

• Brett Marchand, CEO of Plus Company

This composition reflects the company’s positioning at the intersection of data, AI, and enterprise marketing transformation.

The Shift From Legacy Measurement to an Agentic Future

Traditional measurement systems were built for retrospective analysis. They explain what happened, but not what to do next, and they rarely improve themselves over time.

Marketing Evolution’s current strategy is designed for a different future:

• AI-driven decision-making

• Predictive and generative intelligence

• Autonomous and semi-autonomous agents

• Continuous learning from outcomes and feedback

This shift requires infrastructure that can ingest, unify, augment, and govern data at scale, while remaining flexible enough to support evolving AI use cases.

Mevo: The Decision-Ready Intelligence Layer for Marketing

At the center of Marketing Evolution’s offering is Mevo, its domain-specific analytics and intelligence platform. Mevo is not just a reporting tool—it functions as a decision-ready intelligence layer for modern marketing organizations.

Core Characteristics of Mevo

• Built on a marketing-specific data model (ontology)

• Designed to unify fragmented data across the enterprise

• Continuously reconstructs customer and media journeys

• Delivers explainable intelligence in real time

• Supports predictive and generative AI use cases

Mevo represents the operational expression of Marketing Evolution’s AI-ready infrastructure vision.

How Mevo Transforms Marketing Data Into Action

Mevo enables marketing organizations to move from fragmented inputs to unified intelligence through three core capabilities.

Unified Data Structure

Mevo delivers:

• A standardized data structure across sources and channels

• Alignment between audiences, tactics, outcomes, and spend

• Consistent definitions across teams and systems

• Trustworthy inputs for analytics and AI models

This unified structure reduces the friction that typically prevents enterprise-scale AI adoption.

Continuous Learning and Intelligence Compounding

Unlike static analytics systems, Mevo is designed to learn continuously.

Key learning capabilities include:

• Reconstructing journeys across complex touchpoints

• Generating synthetic data to fill gaps and improve models

• Feeding predictive and generative AI systems

• Improving accuracy as new outcomes are observed

This approach enables intelligence to compound over time, rather than reset with each analysis cycle.

Real-Time Decisioning and Interaction

Mevo introduces conversational access to intelligence, enabling:

• Simulation of scenarios before decisions are made

• Forecasting of outcomes across channels and budgets

• Real-time recommendations based on live data

• Faster alignment between insights and execution

This moves marketing intelligence closer to operational decision-making rather than post-hoc analysis.

Proven ROI Impact From Marketing Evolution’s Foundation

Marketing Evolution’s infrastructure is not theoretical. It is already delivering measurable benefits to customers.

Organizations using its analytics suite have reported:

• An average 35% increase in marketing ROI

• Improved confidence in data-driven decisions

• Faster insights across fragmented environments

• Stronger alignment between spend and outcomes

These results demonstrate the tangible value of building intelligence on a strong data foundation.

What’s Coming Next: The 2026 Enterprise Data Platform

In Q1 2026, Marketing Evolution plans to launch a next-generation enterprise data platform designed to extend its infrastructure vision further.

Platform Goals

The upcoming platform aims to help brands:

• Unify AI-ready marketing data across their ecosystems

• Govern and control intelligence at the enterprise level

• Activate insights across AI-driven and agentic systems

• Own and compound the value of their data assets

This launch represents the next phase of the company’s evolution from analytics provider to infrastructure leader.

MarTech Implications: Infrastructure as Competitive Advantage

Marketing Evolution’s announcement reflects a broader MarTech trend: competitive advantage is shifting from tools to infrastructure.

Key implications for MarTech leaders include:

• AI success depends more on data readiness than algorithms

• Domain-specific ontologies outperform generic data models

• Continuous learning systems outperform static dashboards

• Enterprises must own and govern their intelligence

• Agentic systems require reliable, explainable data inputs

As marketing becomes increasingly autonomous, infrastructure will define which organizations can scale AI responsibly and effectively.

Executive Perspective on a Generational Platform Shift

Industry leaders see this moment as part of a larger platform transition driven by AI-native companies.

Core themes emphasized include:

• AI is redefining how industries operate, not just tools

• Foundational data platforms will outlast point solutions

• Marketing analytics is evolving into intelligence systems

• Long-term value lies in adaptable infrastructure, not features

Marketing Evolution’s strategy aligns directly with this generational shift.

Conclusion: Building the Intelligence Backbone for Modern Marketing

Marketing Evolution’s latest funding round signals a clear strategic ambition: to become foundational infrastructure for the AI-driven future of marketing.

By moving beyond legacy measurement and investing in AI-ready data infrastructure, the company is addressing the core challenge that blocks meaningful AI adoption across enterprises. With Mevo as its intelligence layer and a next-generation data platform on the horizon, Marketing Evolution is positioning itself to help brands build adaptive marketing systems that learn, explain, and optimize continuously.

As AI transforms marketing from analysis to autonomy, the organizations that succeed will be those that own their data, govern their intelligence, and invest in infrastructure designed for the future. Marketing Evolution is betting that this is where the next era of MarTech leadership will be defined.

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