Should We Raise Our Prices?
in HealthTech & Digital Health

The short answer

The question is never whether to increase at-risk revenue share in general. It is which contracts, by how much, and what logo churn you expect in return. 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.

Adjusting at-risk revenue share is the fastest lever in any digital health business. It requires no new enrolled members, no hiring and no new product, and it arrives on the next PMPM invoice. It is also the one operators are most reluctant to touch, which is why underpricing on outcomes risk is far more common than overpricing.

A useful price analysis does not produce one number. It produces a segmentation: which contracts show engagement rates that can support a higher at-risk share, which are already at the ceiling given attributed outcomes, and where the distribution of at-risk shares shows terms being set by the sales conversation rather than by policy.

The uncomfortable part is that a good adjustment deliberately increases logo churn. If the change costs you no contracts, the increase in at-risk share was too small.

How to tell this is actually your problem

These three together are the signature. One on its own usually points somewhere else.

✓ Most contracts close at the offered at-risk share with little or no negotiation.
✓ At-risk shares differ widely across similar contracts and are set during individual sales discussions rather than by a consistent rule.
✓ At-risk share has remained unchanged while gross margin has declined over repeated 12-month measurement windows.

The move that usually makes it worse. A uniform increase in at-risk share across the entire contract book, which triggers churn among lower-engagement contracts and still leaves margin on the table with contracts that could support higher terms.

Who this is for — and who it is not

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.

What this looks like when the analysis is actually run

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.

This is one move out of a full analysis. Read a complete report — every page, no email required.

What the engine does with this question

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.

Questions people ask about this

How much can I raise prices without losing customers?

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.

Should I raise prices for existing customers or only new ones?

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.

What if my competitors are cheaper?

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.

Is this different in healthtech & digital health than in other industries?

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.

What data do I need before this analysis is worth running for a digital health company?

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.

When is Percision the wrong tool?

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.

Does Percision replace a lawyer, tax advisor, auditor, or AI implementation team?

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.