A few projects where strategy had to survive contact with the real world.
Most of my work sits somewhere between understanding what patients or customers actually need and figuring out how a healthcare organization can respond. These are a few examples.
A $50M+ payer opportunity that was really a people problem
“Marketing to the payer” was not a particularly useful idea. There were too many people involved, and they cared about very different things. I mapped who actually had influence, what was getting in the way for each group, and built the GTM approach around that.
What was going on
The account was large enough that treating it as one audience stopped making sense. Contracting, clinical, network, member-experience and operational stakeholders all had different reasons to care — or not care.
What I worked on
I mapped decision-makers by influence, need and adoption barrier, then used that segmentation to shape targeting, messaging and channel choices across sales outreach, email, web, events and other touchpoints.
I worked with commercial, legal, medical and operations teams to turn the strategy into material people could actually use.
What changed
We connected campaign execution back to performance data so we could see which audiences and messages were creating useful engagement rather than simply generating activity.
The broader program contributed to more than $2M in attributable expansions and more than $26M in influenced expansions.
What happens when a patient journey suddenly gets insurance added to it
On paper, moving from self-pay toward insurance sounds like a payment change. For a patient or physician, it can change the whole experience.
What was going on
Invitae's integration into Labcorp introduced a shift from a largely self-pay experience toward insurance. That created new questions, steps and information needs for physicians and patients.
What I worked on
I mapped the physician and patient journeys through the ordering experience and looked for places where the new model introduced confusion, additional work or a reason not to adopt.
Some issues were interface problems. Others were really workflow problems underneath the interface.
What changed
The work informed design changes in the ordering experience intended to make the transition easier for patients and physicians to understand and navigate.
Turning clinical workflow insight into health-system adoption
We had technology that could identify patients who might qualify for clinical trials. I worked on making that capability useful to the sponsors, sites and investigators who would actually have to incorporate it into their workflows.
The ecosystem
Recruitment involves sponsors, health systems, research sites, investigators, clinical staff and eventually patients. Each group encounters a different part of the process and values something different.
What I worked on
I interviewed sponsors, site leaders and investigators to understand where recruitment was slowing down across the lifecycle.
The research shaped audience-specific positioning, product priorities and commercialization planning.
Where it landed
The GTM work contributed to adoption by three additional health systems.
It also gave us a clearer view of the different people whose behavior had to change for the product to become part of everyday clinical research workflows.
Building the measurement system behind DTC healthcare growth
I connected acquisition, conversion, retention and customer value across channels so we could understand performance as one customer lifecycle instead of a collection of separate campaign reports.
The setup
Paid search, social, display, EHR channels and retention data each captured a different part of customer behavior. Looking across them together gave us a much better view of what growth actually looked like.
What I built
I created an always-on performance dashboard combining more than 12 data sources and connecting acquisition activity with conversion, retention and customer value.
How we used it
The combined view helped us evaluate which channels were creating valuable customers and informed ongoing decisions about audience strategy, acquisition efficiency and channel investment.
Designing the handoff from automated to human patient support
One of my favorite school projects looked at a very specific moment in patient support: how an automated conversation should transition into live human help.
The moment
We focused on the point where an automated patient conversation reaches the limits of what it can appropriately resolve and live support takes over.
What we designed
We mapped what the bot should try to resolve, when a human should step in, what context should travel with the patient and how to avoid making someone explain everything again.
The output
The work included conversation flows, content and escalation logic across the automated-to-human support experience.
The common thread is less about any one method. I like figuring out where an experience or strategy is getting stuck — and what has to change for someone to actually use it.