Case Study — Healthcare SaaS

From zero growth insight to a compounding infrastructure that predicts churn, drives experiments, and pays for itself.

Stack

$272K–$505K

Annual revenue impact

$900K–$1.6M

3-year projected impact

90%

Analytics cost reduction

30–60 days

Churn predicted before cancellation

118+

Decision-ready dashboards built

Before.

A B2B SaaS platform in healthcare with ~2,700 customers had built their analytics on an enterprise platform without a proper event taxonomy or compliance review. Events were firing but 0% of properties were being captured — months of data collection that couldn't be segmented or analyzed.

Their analytics weren't answering the questions that mattered: activation rate by practice type, feature adoption by user role, churn signals by customer segment. They had data. They had no decisions.

The CS team was working from a renewal date spreadsheet. No risk scores. No behavioral triggers. No early warning. High-value accounts churned with no prior indication. Meanwhile, analytics was costing $20K–$50K/year for zero growth insight.

The Situation

Analytics collecting data but not connected to any business decision
Analytics costing 10x what they should — $20K-$50K/year for zero growth insight
No churn prediction — CS team reactive, working from a renewal date spreadsheet

What we did.

A full DISCOVER audit across all 6 growth layers, followed by systematic remediation and infrastructure build.

Step 1 — Discovery

DISCOVER audit across all 6 growth layers: competitive intelligence, analytics & measurement, product experimentation, activation, retention & churn, and GTM & positioning.

Step 2 — Compliance

Analytics compliance gaps identified and resolved. Migration to compliant analytics stack completed. 5-layer data governance architecture implemented.

Step 3 — Analytics Rebuild

Full event taxonomy redesigned: 45 events redesigned around business decisions (vs. 12 previously). Migration to compliant analytics stack — $450/month vs. $20,000–$50,000/year for enterprise alternatives.

Step 4 — Decision-First Dashboards

118+ production charts built across 13 dashboards, all question-first. Every chart answers a specific business decision. Activation rate by practice type. Feature adoption by user role. Churn signals by customer segment.

Step 5 — Churn Prediction

85+ behavioral signals analyzed — login patterns, feature adoption trends, support ticket velocity. Churn prediction model trained with a 30-day prediction window. CS team saves accounts 30–60 days before they'd have cancelled — weekly at-risk list delivered every Monday.

Step 6 — Competitive Intelligence

Competitive intelligence database covering 35 competitors. 887+ pages of data analyzed. CS team equipped with competitive positioning guides for the most common competitive scenarios — your sales team knows exactly what to say.

After.

$272K–$505K

Annual revenue impact identified and addressed

90%

Reduction in analytics infrastructure cost

118+

Decision-ready charts built question-first across 13 dashboards

Events redesigned around business decisions (vs. 12 previously)

30–60 days

Churn predicted before cancellation — CS team intervenes, not reacts

$450/mo

Analytics cost (vs. $20K–$50K/yr for enterprise alternatives)

What you can do now.

Your CS team receives a weekly at-risk customer list every Monday — with the top 3 behavioral drivers of churn for each account. Proactive outreach, not reactive damage control.

Your growth team runs experiments against an instrumented funnel where every step is measurable — by persona, by cohort, by traffic source. No more guessing which segment the experiment moved.

Your analytics infrastructure costs a fraction of enterprise solutions — $450/month instead of $20K–$50K/year — while meeting enterprise compliance standards. Full behavioral visibility at a fraction of the cost.

See What This Costs → Book a 15-Minute Call

Jake McMahon

ProductQuant

10 years building analytics and growth systems for B2B SaaS at $1M–$50M ARR. BSc Behavioural Psychology, MSc Data Science. Most healthcare SaaS teams have more data than they know what to do with and fewer answers than they need. The problem is rarely the data — it’s the architecture that sits between the data and the decisions.

What this looks like for your company

The Foundation.

A six-week growth infrastructure build covering analytics, churn prediction, competitive intelligence, and positioning — delivering a ranked opportunity map and the systems your team uses to act on it.

Full analytics audit: every event reviewed, biggest gaps revenue-sized, implementation roadmap
Churn prediction model trained on your data; at-risk accounts surfaced weekly
Competitive intelligence library: 15+ competitors mapped with ongoing monitoring
Decision-ready dashboards built on PostHog at a fraction of enterprise analytics cost
Full handover: documentation, walkthroughs, and independent operation from day one

$15,000–$25,000 · 6 weeks

Right for you if

Analytics data exists but costs $20K–$50K/year and the team still can’t answer basic growth questions
Churn prediction running on spreadsheets and intuition rather than behavioural signals
Need a complete growth operating system, not a point-in-time audit

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