Problems › A Competitor Is Taking Our Customers › HealthTech & Digital Health
Losing to a competitor is a positioning question far more often than a price one, and the two need opposite responses. This page works through it for digital health companies specifically — including an unedited excerpt from a real analysis of a digital health company.
Losing to a competitor is a positioning question far more often than a price one, and the two need opposite responses. What makes this harder for digital health companies is structural: 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. Any credible answer therefore has to hold at-risk revenue share and engagement rate in the same view, which is exactly where most internal analysis stops because the two live in different systems.
When a competitor starts winning, the first explanation offered inside the business is always price. It is occasionally true. More often the competitor has picked a narrower promise and is beating you inside it, which looks like price to a sales team because price is the last thing discussed before a loss.
The distinction matters because the responses are incompatible. If it is genuinely price, you either match it and reprice the whole book or you accept the loss of that segment. If it is positioning, matching price funds their advantage while destroying your margin.
The way to tell is unglamorous: the reasons recorded on the last twenty losses, segmented. A price problem shows up everywhere. A positioning problem clusters.
These three together are the signature. One on its own usually points somewhere else.
✓ Losses concentrate in one segment or one use case rather than spreading evenly
✓ The sales team asks for discount authority rather than for different proof
✓ The competitor is smaller and more specific than you
The move that usually makes it worse. Meeting the price and keeping the positioning, which loses the margin and the argument at the same time.
It is for you if you run or finance a digital health company and losses concentrate in one segment or one use case rather than spreading evenly. 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. Reduce downside exposure from $7.1M outcomes shortfall to $4.2M while maintaining upside participation in 34 health-plan contracts.
The leak it closes. $2.9M gross profit protected annually through downside cap (difference between $7.1M shortfall at 38% vs $4.2M shortfall at 25%)
The assumption it rests on. Health plans accept 25% downside cap without demanding 15-20% PMPM reduction to compensate — the engine put the probability at 0.7.
| Investment required | $0 incremental — policy change executed by existing legal, finance, and account management teams within current $14M annual burn |
| Expected return | 5.2× on zero incremental investment — derived from $4.2M FY2026 bookings protected relative to status-quo downside exposure |
| Revenue, year 1 | $57.8M ARR (25% at-risk share = $15.5M at-risk revenue vs $23.6M status quo) |
| Revenue, year 2 | $61.4M ARR (assuming 80% contract renewal at 25% cap) |
| Revenue, year 3 | $68.2M ARR (assuming 85% renewal and 10% PMPM stabilization) |
| Exit criteria | Abandon this move if >3 of 8 Q4 2026 contract renewals demand >15% PMPM reduction to accept 25% cap, OR if outcome-prediction accuracy falls below 70% on 10k cohort by Month 9; pivot to fixed-fee PMPM model with optional 15% upside sharing only |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Competitive Benchmarking & Positioning, 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.
Only if you can serve that segment at their price and still make money, and only if you are willing to reprice the customers who already pay you more. A selective match is usually a promise you cannot keep once the market notices.
On specificity, not on breadth. A better-funded competitor can outspend you everywhere and cannot out-focus you in one place, which is why narrowing the promise usually beats broadening the feature set.
Then the honest answer is a product decision with a timeline and a cost, not a marketing response. The damaging outcome is spending a year on messaging for a gap that messaging cannot close.
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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