Engagement strategy is the practice, not a deliverable.
Engagement is not a deliverable; it is what the strategy should answer.
How the practice shows up
-
The question, before the channel.
Where the audience actually is decides what gets built. The channel mix is the answer, not the brief.
-
The journey, not the campaign.
A touchpoint is only useful when it connects to the ones before and after it. Engagement strategy is the through-line.
-
The constraint, as the case.
The tightest constraints — regulatory, behavioral, attention — are where the practice either stands or collapses. That's where it gets tested.
Work
Case studies are held under client confidentiality. Each card previews a sector and the kind of strategic artifact the work produced — click any card to request access.
About
Engagement strategy for pharmaceutical brand teams — content systems and AI that scale brand engagement under regulatory review.
Over 15+ years across the OHG/IPG network, I've built content systems and engagement properties at single-brand and portfolio scale — the Keytruda modular content system, originally piloted on lung HCP and adopted across indications; the AstraZeneca Imfinzi oncology-portfolio triage site; and the Novartis MS-portfolio triage site. Each shaped engagement strategy across compliance, audience, and outcome tradeoffs. Recent work centers on AI-driven content systems that scale across indications and brand contexts.
My path to engagement strategy came through systems thinking — a BA in international relations and a master's in technical systems management, both from Stony Brook. Before UX, I spent four years in Shenzhen as a business analyst, working cross-border supply-chain problems where production, quality, and cross-cultural negotiation all happened simultaneously. What ties the arc together is a particular fluency with complex systems and a discipline of translating complexity into clarity at the scale required. I came to UX through Stanford's d.school program and HCI coursework in 2013, then built my career across pharma and consumer shops in New York, concentrating in pharma at CDM and Wildtype.
One example: at Wildtype on Merck's Keytruda (2021–2024), I was on the team that designed a modular content system — atomic blocks composed into modules, bundled by communication objective, assembled into templates per channel: branded, unbranded, or third-party. We piloted on lung HCP, then carried it through MLR approval — teaching MLR how the modules and templates fit together, and codifying which modules carried which safety information. We coached other indication teams as adoption spread across the brand. That architecture is what makes AI-driven content systems possible in pharma — the same modular logic that earns regulatory approval is what AI assembly needs to scale without resubmission.
An engineering principle I carry: structure decides what scales. In regulated content, that means the architecture has to clear regulators, work for brand teams, and hold audience trust before AI can do anything useful. With that structure in place, AI becomes leverage. Without it, AI becomes risk dressed up as productivity.
The teams I want to join take the architecture seriously — work that has to clear regulators, earn audience trust, and scale by its own logic.
Contact
- mniola@outlook.com
- linkedin.com/in/marcniola
Usually within 48 hours.