Problems › Should We Raise Our Prices? › HealthTech & Digital Health
The question is never "should we raise prices" in general. It is which customers, by how much, and what you expect to lose. This page works through it for digital health companies specifically — including an unedited excerpt from a real analysis of a digital health company.
The question is never "should we raise prices" in general. It is which customers, by how much, and what you expect to lose. The version of this question that applies to digital health companies is not the generic one. 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 — so an answer that ignores at-risk revenue share will be confidently wrong. The analysis has to start from engagement rate and gross margin rather than from revenue.
Price is the fastest lever in any business — it requires no new customers, no hiring and no new product, and it arrives on the next invoice. It is also the one owners are most reluctant to touch, which is why underpricing is far more common than overpricing.
A useful price analysis does not produce one number. It produces a segmentation: which customers are paying below the value they receive, which are already at the ceiling, and where the discount distribution shows price being set by the sales conversation rather than by policy.
The uncomfortable part is that a good price change deliberately loses some customers. If a rise costs you nobody, it was too small.
These three together are the signature. One on its own usually points somewhere else.
✓ Almost every deal closes, and closes quickly
✓ Discounting is common and inconsistently applied
✓ Price has not moved in more than two years while your costs have
The move that usually makes it worse. A uniform percentage rise across the whole book, which overcharges the price-sensitive customers and still undercharges the ones who were never buying on price.
It is for you if you run or finance a digital health company and almost every deal closes, and closes quickly. 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 · Customer Value Architecture · 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 Pricing & Revenue Optimization, 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.
There is no general answer, and the useful analysis is per segment. What can be said is that the loss you fear is usually concentrated in a group whose economics you would improve by losing them.
New first is safer and slower; existing is where the money is. A defensible sequence is to move new-customer pricing, watch win rate for a quarter, then bring existing customers up at renewal with notice.
Then you are selling against them on something other than price, or you are not — and that is the real question. Competing on price without the cost structure to support it is the most reliable way to lose money at increasing volume.
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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