Patrick Diogenia is a marketing, growth, and transformation executive, strategist, and researcher with more than two decades of experience across corporate, consulting, entrepreneurial, and public-sector environments.

He currently serves as Lead Director, Behavior Change Marketing at CVS Health, where he leads an internal agency team primarily supporting Aetna. His work brings together consumer behavior, marketing strategy, analytics, creative, data science, operations, and enterprise stakeholder leadership to influence consequential healthcare decisions.

Across his professional and research work, Patrick focuses on translating customer insight, evidence, technology, and market understanding into decisions about where organizations should compete, what capabilities they should build, how they should allocate resources, and how those choices can produce measurable results.

Patrick serves as Lead Director, Behavior Change Marketing at CVS Health, leading an internal agency team whose work primarily supports Aetna.

The team develops marketing and engagement strategies designed to help members make healthier and more efficient healthcare decisions. Its work can include encouraging preventive care and annual checkups, connecting members with appropriate mental and behavioral health programs, improving engagement with health services, and helping reduce avoidable hospital readmissions.

The role combines agency leadership, marketing strategy, operations, analytics, creative, data science, campaign execution, and enterprise stakeholder management. It reflects Patrick’s broader interest in how organizations translate insight about people into interventions that can improve both customer outcomes and business performance.

Patrick typically works on problems that sit between strategy and execution. These include deciding which customer opportunities merit investment, determining how an organization should segment and prioritize markets, designing lifecycle and loyalty strategies, evaluating marketing technology capabilities, improving customer experience, establishing performance measures, and creating the operating structures needed to turn strategic priorities into sustained execution.

His work often begins where the answer is not yet obvious: the organization has data, resources, and competing opportunities, but needs a clearer framework for deciding what to do next.

Patrick views growth strategy primarily as a problem of choice and resource allocation. Rather than beginning with a predetermined channel, technology, or tactic, he starts by identifying where an organization has a credible opportunity to create differentiated value.

From there, he considers the customers to prioritize, the capabilities required to serve them, the investments those capabilities justify, and the measures that will indicate whether the strategy is working. His approach places particular emphasis on connecting strategic ambition to operating decisions, accountability, and measurable outcomes.

Patrick believes customer segmentation should begin with the business decision the segmentation is intended to improve, rather than with the statistical technique used to create the segments.

A technically sophisticated model has limited value if an organization cannot identify, reach, understand, or meaningfully treat the resulting segments differently. His work therefore considers not only model quality, but also actionability, stability, data availability, operational complexity, customer context, and the economics of differentiated treatment.

This perspective also informs his work on AI-assisted customer segmentation and the selection of appropriate segmentation methods for different business problems.

Patrick approaches artificial intelligence as a decision-support capability rather than an end in itself. He is particularly interested in where AI can improve customer understanding, segmentation, targeting, experimentation, decision speed, and organizational learning.

At the same time, his work examines the limits of optimization without context. A model can become more technically precise while becoming less useful to the people responsible for acting on its recommendations. Patrick therefore emphasizes the interaction between AI, managerial judgment, organizational capability, and the real-world conditions in which decisions are made.

Patrick’s marketing technology experience includes customer communications, lifecycle marketing, personalization, segmentation, measurement, vendor strategy, marketing platforms, and cross-functional capability development.

He has worked on decisions involving multimillion-dollar technology and services portfolios, directly managed significant vendor and project responsibilities, and advised on larger investments controlled at higher organizational levels. His work has also included vendor negotiation, business-case development, KPI design, executive reporting, governance, and translating technical capabilities into customer and commercial outcomes.

Patrick’s leadership philosophy emphasizes clarity, evidence, ownership, and the development of people.

He believes teams perform better when they understand not only what they are expected to deliver, but why the work matters, how priorities relate to one another, and how success will be measured. His approach therefore combines strategic direction with operating cadence: clear objectives, useful metrics, candid discussion of tradeoffs, and accountability for follow-through.

He also places particular value on teaching and knowledge transfer. Throughout his career, he has used research, graduate study, and practical experience to help colleagues understand the reasoning behind decisions rather than simply directing them toward an answer.

Patrick frequently uses academic and applied research as an input to business decision-making. Rather than treating scholarship and management practice as separate activities, he looks for ways to translate concepts from marketing, organizational behavior, analytics, communication, and strategy into usable frameworks for practitioners.

During his MBA studies, for example, he regularly applied ideas from coursework to active business problems, using research to inform strategic recommendations, customer initiatives, vendor decisions, measurement approaches, and operating practices.

His broader interest is in making rigorous ideas usable without stripping away the context and limitations that make them meaningful.

Patrick has studied Net Promoter Score as both a customer metric and a managerial innovation.

His research asks why NPS became extraordinarily widespread despite longstanding debate about its scientific and predictive advantages. Rather than treating adoption purely as evidence of measurement superiority, his work examines characteristics such as simplicity, portability, managerial visibility, ease of communication, and institutional diffusion.

This perspective places NPS within a larger question Patrick studies frequently: why organizations adopt certain management practices, how those practices spread, and what happens when tools designed for one purpose acquire broader organizational meaning.

Patrick’s experience spans sectors including healthcare, media and telecommunications, hospitality and travel, retail, financial services, gaming, technology, business services, economic development, and consulting.

He sees cross-industry experience as useful because it makes assumptions more visible. Practices that appear inevitable within one industry often look very different when compared with how another sector organizes customer relationships, measures value, deploys technology, or structures decision-making.

Rather than assuming that a practice should be copied from one industry to another, Patrick focuses on identifying which underlying principles are transferable and which depend on industry-specific economics, customer behavior, regulation, or organizational structure.

Patrick holds MBAs from Indiana University’s Kelley School of Business and Alliance Manchester Business School and graduated summa cum laude from the University of Pennsylvania.

His graduate education has complemented rather than replaced his professional work. He has used formal study to deepen his understanding of strategy, marketing, analytics, organizational behavior, leadership, and decision-making while continuing to examine how those disciplines operate in real organizations.

His current academic interests extend into organizational communication, applied artificial intelligence, and machine learning.

Patrick’s current work is centered on the intersection of customers, organizations, technology, and managerial decision-making.

Topics include AI-enabled customer segmentation, customer metrics and measurement, the diffusion of management practices, organizational behavior, leadership, marketing strategy, and the practical adoption of artificial intelligence.

A recurring question across this work is why technically attractive ideas sometimes succeed, fail, or produce unexpected consequences once they enter complex organizations.

Patrick treats strategy less as a presentation or planning exercise and more as a system for making consequential choices.

A useful strategy should clarify what deserves investment, what does not, which customers or opportunities matter most, what capabilities must exist, who owns the resulting decisions, and how the organization will know whether those choices were correct.

For Patrick, the test of strategy is therefore not how sophisticated it sounds. It is whether it helps an organization make better decisions, mobilize people and resources, and produce results that can be observed and evaluated.