Cardiometabolic buyers are won by trust, not novelty, and your claims face regulatory review. We create an experimentation program that ships weekly, stays within clinical guardrails, and shows you what truly drives enrollment and adherence.
The Challenge
Your testing backlog has become a graveyard of unfinished ideas
Diabetes and cardiometabolic teams collect experiment ideas the way they collect Jira tickets – fast, then never again. Without an owner and a resolution cadence, tests sit at 40 percent traffic for six weeks and nobody calls them. The cost is not the failed test, it is the eight winning ideas that never got run because the pipeline was clogged. When enrollment is your growth lever, a stalled test program is lost revenue every single week.
Every claim on a landing page sets off a legal and clinical review
You cannot A/B test 'reverse your diabetes' the way a DTC apparel brand tests 'free shipping.' Cardiometabolic outcomes are regulated territory, and a careless variant can pull medical, legal, and regulatory into the room and freeze your roadmap for a month. Most growth teams respond by testing nothing meaningful – only button colors. That is why their experimentation program produces no lift: they are optimizing the parts that do not matter because the parts that do feel too risky to touch.
You track signups, not the outcomes that payers and members actually value
A cardiometabolic company that optimizes top-of-funnel signups will happily buy enrollments that never activate a CGM, never log a meal, and churn before the first A1C reading. The metric that matters – enrolled-to-engaged, or first-90-day adherence – sits three steps downstream of where most teams run their tests. Optimize the wrong metric and you scale a leak.
With small sample sizes, every result becomes a coin toss
Unlike a consumer app with millions of sessions, a Series A diabetes company may enroll a few thousand members a quarter through a clinical or employer channel. Run a naive A/B test on that traffic and you will call winners that are noise. Teams either wait months for significance and lose momentum, or ship on 60-percent-confidence reads and wonder why the aggregate never improves.
How We Can Help
We begin by auditing what you have actually shipped over the past two quarters, not what appears on the roadmap. We compile the tests that ran, how long they lingered, who resolved them, and what changed downstream. Nine times out of ten, the conclusion is the same: velocity is low, resolution discipline is absent, and the tests that ran affected surfaces incapable of moving the outcome metric. That audit builds the case for change.
Next, we reconstruct the backlog around a hypothesis format that connects every experiment to a specific funnel metric – not 'signups' but 'enrolled-to-first-CGM-scan' or 'employer-eligible-to-activated.' Every idea receives a size estimate, an effort estimate, and a clinical-risk flag, allowing regulated variants to enter review early rather than die late. The backlog becomes a prioritized queue with a weekly shipping target instead of a wishlist.
To address clinical claims, we create a pre-cleared variant library alongside your medical and regulatory partners. Rather than starting a new review for every test, we establish approved claim structures and evidence hierarchies that can be freely recombined. That separates an experimentation program testing meaningful messaging from one that only ever changes a button's color.
For limited sample sizes, we apply the statistical rigor that most growth teams overlook. We size tests for your real traffic, use sequential testing where appropriate so clear winners can stop early, and clearly identify surfaces that lack enough volume to test – those decisions rely on judgment, not an underpowered test masquerading as data.
Our difference is that we embed as operators. We do not deliver a framework deck and disappear. We join your standups, lead the experiment review meeting, prepare the analysis, and make ship-or-kill decisions with you until your team owns the muscle. This growth experimentation engagement is led by people who have shipped tests in regulated health, not consultants who merely read about it.
We also tie the program into your wider growth strategy and measurement stack, ensuring experiment insights compound into channel and product decisions instead of remaining in an unopened spreadsheet.
What we deliver
- Experiment audit – what shipped, what stalled, and where velocity leaks (usually the first eye-opener)
- Prioritized test backlog scored by impact, effort, and clinical-review risk
- Pre-cleared claim variant library built with your medical and regulatory partners
- Weekly experiment review cadence with owned resolution and ship/kill decisions
- Right-sized test design and analysis for low-volume clinical and employer traffic
In cardiometabolic health, experimentation is never constrained by idea generation – the real limits are resolution velocity and clinical-claim clearance. Solve those two, and your current backlog becomes worth 10x more overnight.
Our Methodology
We operate experimentation as a 90-day sprint. Days 1-30 focus on diagnosis and setup: we review shipped tests, reconstruct the backlog using a true hypothesis format, and establish the pre-cleared claim library with your medical and regulatory partners so review no longer creates the bottleneck. During days 31-60, we ship – running a weekly experiment review, setting a shipping target, and delivering honest analysis for every resolved test, with clinical guardrails included from day one. Days 61-90 are about compounding: winners move into production, insights inform your channel and product roadmap, and we begin transferring the review meeting to your team.
Unlike a traditional agency or CRO consultancy, we do not optimize individual surfaces in isolation. A generic CRO firm may test checkout while avoiding the clinical-claim hierarchy because it intimidates them. We designed this for regulated environments: the goal is to test risky, high-leverage messaging safely, not run 40 button tests and claim a 2 percent lift.
The program is built to make itself unnecessary. By day 90, your team owns the cadence, backlog discipline, and claim library. We prefer to create your engine rather than sell you an ongoing dependency.
Our Working Model
The first 30 days require intensive work from us – we dig into your data, join your standups and review meetings, reconstruct what truly shipped, and establish the backlog and claim library. By week three, you will notice tangible change as the first properly designed test goes live.
Our side provides a growth operator who leads the experimentation program from end to end, along with an analyst who designs and interprets the tests. From you, we need a product or engineering partner who can implement variants, plus access to your medical and regulatory reviewer – that relationship is everything in cardiometabolic.
We work on a weekly cadence: a standing experiment review in which every live test receives a resolution decision, each new idea is scored into the backlog, and nothing remains at partial traffic without cause. Each month, we consolidate learnings into a growth read connecting experiment outcomes with enrollment, activation, and retention trends.
Most engagements last three to six months. At the end, you have a self-sustaining program – including a scored backlog, shipping cadence, claim library, and team that can lead the review without us. Some clients continue the engagement to add experimentation across new channels or within the product itself.
- Experiment velocity increase
- Enrolled-to-activated conversion lift
- Faster clinical-claim clearance cycle
- Reduced wasted spend on underpowered tests
If your diabetes & cardiometabolic health company needs growth experimentation leadership, we should talk.
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Frequently asked questions
What does a growth experimentation engagement cost for a diabetes or cardiometabolic company?
Most engagements cost about what you would spend on one senior growth hire, billed monthly over a three-to-six-month build. That is substantially less than the alternative stack of a full-time VP of Growth, an analyst, and a CRO agency retainer.
How soon will we see results from an experimentation program?
The first properly designed test will ship within three weeks, with the review cadence operating by week four. Meaningful improvement in a downstream metric such as activation generally appears during the second month, after enough tests have resolved to distinguish signal from noise.
How does your experimentation team work with our current product and marketing staff?
We embed with your team instead of operating externally. We attend your standups, lead the weekly experiment review, and produce the analysis while partnering directly with your product or engineering counterpart to implement variants.
How do you A/B test clinical claims without creating regulatory issues?
We do not improvise with claims. At the start of the engagement, we work with your medical, legal, and regulatory partners to create a library of pre-cleared claim structures and evidence hierarchies that you can recombine freely.
What distinguishes Winston Francois from a conventional CRO or experimentation agency?
Traditional CRO agencies optimize the safest surfaces and report minor gains from button tests because high-leverage clinical messaging intimidates them. We designed this engagement for the regulated case – safely testing risky, high-value messaging is the whole purpose. We also work as embedded operators and transfer the program to your team, rather than maintaining a permanent retainer where the knowledge stays with us.
How can you run valid experiments when our enrollment volume is limited?
We size each test around your real traffic rather than acting as though a consumer-scale playbook will fit. When volume allows, we apply sequential testing so clear winners can be stopped early; when a surface cannot achieve significance, we acknowledge it and use judgment rather than presenting noise as data. Honest clarity about what your traffic can and cannot answer is fundamental to the discipline.
What kind of cardiometabolic company is the best fit for this service?
This service best fits a Series A through growth-stage diabetes or cardiometabolic company with roughly $5M to $100M in revenue, an existing product and enrollment volume, but no disciplined experimentation capability. If you are pre-product-market-fit or receive almost no traffic, experimentation is too early, and we will say so. We start with a brief call to review what you have actually shipped and determine whether investing in an engine makes sense now.
