From Fragmented Marketing Insights to AI-Driven Patient Growth

Achieving 19% More Patients Without Increasing Spend

Client Overview

A leading U.S. healthcare network with a strong regional presence and diverse specialty care, the client is driven by a mission to elevate patient experiences through innovation and compassion. Focused on measurable growth and smarter care delivery, the organization set out to modernize its marketing analytics—transforming fragmented data into actionable intelligence that drives patient acquisition, optimizes spend, and strengthens lifetime value.

Challenges

The healthcare provider faced increasing complexity in understanding marketing’s real impact on patient acquisition and engagement.

Limited ROI Visibility: Traditional MMM models failed to quantify marketing’s true contribution to patient appointments.
Fragmented Data Sources: Disconnected systems made it difficult to unify insights across service lines, media channels, and time periods.
Static Reporting: Existing models offered backward-looking analysis with no actionable guidance for optimization.
Lack of Specialty Clarity: Media responsiveness across specialties like Cancer, Neuroscience, and Cardiology remained unclear.
No Link to Lifetime Value: The team lacked visibility into how marketing influenced long-term patient engagement and overall value.

Solution

The organization partnered with Market Fusion Analytics to deploy its Growth Drivers platform, powered by AI and machine learning. The platform delivered an intelligent, dynamic measurement framework that continuously linked marketing activity to business outcomes.

AI/ML-Based Attribution: Quantified each marketing channel’s real impact while accounting for macroeconomic and seasonal variations.
Specialty-Level Sensitivity Analysis: Identified which service lines responded most effectively to media spend.
Dynamic, Real-Time Modeling: Machine learning models continuously ingested new data, ensuring up-to-date, actionable insights.
ROI & CLV Measurement: Connected marketing investments directly to new patient acquisition and long-term value generation.

Delivery Approach

Assessment:

Analyzed multi-year patient appointment data across service lines and media channels.

Evaluated gaps in existing measurement models and identified influencing external factors such as seasonality and operations.

Planning:

Designed a specialty-sensitive performance framework using AI/ML-driven models.

Established automated data pipelines for continuous model learning and updates.

Defined unified KPIs to track acquisition, lifetime value, and ROI impact.

Implementation:

Deployed Growth Drivers™ models to isolate and measure the effectiveness of every marketing tactic.

Integrated specialty-level insights to fine-tune media mix and allocation strategies.

Enabled marketing and strategy teams to access real-time insights via conversational AI.

Optimization & Hypercare:

Continuously refreshed models with live data for evolving recommendations.

Fine-tuned media mix across time, channels, and specialties for peak efficiency.

Provided ongoing support and scenario planning to guide future campaigns.

Business Outcome

19% increase in new patient acquisition — achieved without increasing marketing spend.

14% of new patients directly attributed to marketing-driven initiatives.

Top-performing channels: TV, OOH, and Paid Search delivered the highest ROI.

Most responsive specialties: Neuroscience, Cancer, and Cardiovascular.

Continuous optimization loop: AI-driven insights enabled ongoing improvement and scenario-based planning.

Conclusion

By transitioning from static, manual measurement models to an AI-powered, dynamic analytics platform, the healthcare provider unlocked a new level of marketing accountability and performance. The transformation empowered teams to make data-backed decisions, maximize media ROI, and deliver measurable growth, turning marketing from a cost center into a strategic driver of patient engagement and value.

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