Problems › Our Marketing Spend Is Not Working › HealthTech & Digital Health
Most marketing that "does not work" is spend on a channel that cannot reach the buyer, measured in a way that cannot tell. This page works through it for digital health companies specifically — including an unedited excerpt from a real analysis of a digital health company.
Most marketing that "does not work" is spend on a channel that cannot reach the buyer, measured in a way that cannot tell. For digital health companies, this shows up in a particular place. The numbers that carry the answer are at-risk revenue share and engagement rate, and the complication specific to this industry is that outcomes risk is being signed faster than the company can learn whether it can carry it — a 12-month measurement window against an 11-month sales cycle. The general version of this problem and the one you are actually in have different first moves.
Two different failures produce the same complaint. The channel genuinely does not reach your buyer, in which case more budget makes it worse. Or it does and you cannot see it, in which case the spend is being judged by a measurement system that does not track the path your buyer actually takes.
Separating them is a measurement question first. If cost per acquisition cannot be computed by channel, no amount of creative or targeting work will settle the argument, and the budget will be allocated by whoever is most confident.
The second question is payback rather than volume. A channel that acquires expensively but pays back inside a quarter is fundable; one that acquires cheaply and pays back in three years is not, whatever the cost per lead says.
These three together are the signature. One on its own usually points somewhere else.
✓ Cost per acquisition cannot be stated by channel
✓ Spend is defended by impressions, clicks or leads rather than by customers
✓ The best-performing channel changes depending on who reports it
The move that usually makes it worse. Optimising creative and targeting before fixing measurement, which produces a year of confident decisions on unreliable numbers.
It is for you if you run or finance a digital health company and cost per acquisition cannot be stated by channel. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.
It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
Below is an excerpt from a real run of this analysis on a digital health company. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.
The subject is Vantabridge Health, a sample company profile used for testing rather than a customer — $62M ARR, 340,000 enrolled members.
Excerpt from a real Percision run · Cost Reduction & Efficiency · sample company profile
The move. Convert 180 existing employer relationships into $11.7M incremental outcomes-contingent revenue by Month 24 without new-plan procurement.
The leak it closes. $6.5M device leakage reduced by shifting kit cost to employer opt-in, improving gross margin 7 points on employer cohort
The assumption it rests on. 180 employers accept outcomes-contingent terms at 45% at-risk share — the engine put the probability at 0.7.
| Investment required | $0.6–0.9M total (2 FTE employer specialists @ $180K fully loaded each × 18 months + $120K enablement tools) |
| Expected return | 13.0× on $0.9M investment ($11.7M incremental revenue by Month 24) |
| Revenue, year 1 | $3.9M incremental employer outcomes revenue |
| Revenue, year 2 | $11.7M cumulative incremental employer outcomes revenue |
| Revenue, year 3 | $18.5M cumulative if employer cohort grows 15% YoY |
| Exit criteria | Terminate move if employer conversion rate <25% by Month 12 OR if employer at-risk share demanded exceeds 50% OR if device-kit leakage reduction <10 points by Month 18. |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Go-to-Market & Commercial Strategy, one of 29 engagements the platform runs. For digital health companies it works through at-risk revenue share, engagement rate, gross margin and logo churn, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.
You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.
The only meaningful test is against lifetime value and payback period, both of which are business-specific. A cost that is excellent in one model is ruinous in another with the same revenue.
Long enough to cover your sales cycle plus one payback period, and no longer. Judging early kills channels that work slowly; judging late funds channels that never will.
Cut the channels you cannot measure first — that is where the risk is concentrated. Cutting uniformly removes the channel that was working alongside the ones that were not.
Materially, yes. Outcomes risk is being signed faster than the company can learn whether it can carry it — a 12-month measurement window against an 11-month sales cycle — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are at-risk revenue share, engagement rate, gross margin, and an answer built on industry-general benchmarks will usually point at the wrong one first.
Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on at-risk revenue share and engagement rate. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.
Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
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