Case Study: Healthcare Customer Segmentation
A New Perspective on Target Groups in Healthcare Marketing
In healthcare, vast amounts of valuable data are generated every day. Yet CRM systems, digital interactions and field force activities often remain disconnected. For engaging health care professionals (HCPs), this means target groups are only partially visible, campaigns do not reach their full potential and resources are not used to their best effect.
Together with a leading healthcare company, we demonstrated how Analytical CRM can change this. A data-driven segmentation model consolidates information, uncovers behavioral patterns and creates clear target group profiles.
The result: more relevant communication, more efficient steering of activities and resources and a reliable foundation for future-oriented HCP marketing.
The Challenge: Fragmented Data and Missing Alignment
The situation was typical for many healthcare organizations: While large amounts of data and analyses were already available, their integration into operational processes was not consistently established. CRM data was fragmented, digital signals were not centrally accessible and cross-channel coordination was not possible. As a result, marketing and sales lacked a consistent segmentation logic.
The key challenge was to prepare segmentation insights in a way that made them directly actionable for measures such as campaign planning or field force management. The goal was to build a stable data foundation enabling differentiated and behavior-based engagement of health care professionals.
Our Approach: Consolidating Data and Showing Behavior
At the core of the project was the creation of a modern marketing data stack with Snowflake as the central hub. Relevant data sources were integrated, cleansed and harmonized.
Based on this foundation, we developed an extended RFM model (Recency, Frequency, Monetary). It combined traditional KPIs with digital behavioral data such as click patterns, interaction frequency and channel preferences. Machine learning techniques were used to identify patterns and create meaningful clusters.
Segmentation data was regularly fed back into the CRM through the loop system, enabling the field force to use it directly. Trainings, pilot projects and practice-oriented Power BI dashboards supported adoption in daily operations. This made data-driven decisions transparent and embedded them across teams. The result was an integrated approach that connects technology, methodology and organization.
The Result: A Model that Works in Daily Business
The segments were visualized in interactive Power BI dashboards. As a result, marketing, sales and CRM teams have continuous access to:
- Target group profiles with clearly defined characteristics, taking into account data protection and regulatory requirements
- Preferred channels and behavioral patterns
- Interaction frequency and potential scoring
This allows marketing campaigns and field force activities to be planned and managed with greater precision.
Benefits for Marketing and Sales
As in other industries, budgets in healthcare are limited, regulatory requirements are strict and the target audience is highly demanding. A data-driven customer segmentation enables organizations to engage health care professionals more effectively and use resources more efficiently.
This case study shows that siloed data can be turned into a true decision-making tool when technology, methodology and organization are aligned.
The advantages are clear:
- Structured foundation: Transparency about relevant target groups and preferences
- Efficient use of existing data: Fragmented information is consolidated
- Targeted campaign management: Content, channels and budgets can be planned more effectively
- Scalability: The model serves as a basis for additional use cases such as Next Best Action, churn prediction or CRM automation
Benefits for Marketing and Sales
Healthcare customer segmentation means grouping health care professionals (HCPs) based on their behavior, preferences and interactions – while taking data protection and regulatory requirements into account. This enables organizations to communicate in a targeted and personalized way.
A behavior-based model combines Analytical CRM data with digital signals such as clicks and channel preferences. This creates precise profiles that marketing and sales teams can use for more relevant engagement.
Teams gain transparency on target groups, can better plan field visits, design more effective campaigns and events and allocate budgets more efficiently.
An HCP segmentation model enables, for example, data-driven use cases such as Next Best Action, churn prediction, personalized campaigns and CRM automation.
The duration depends on the data landscape as well as the company’s specific goals and project objectives. First results, such as segmented dashboards, are often possible within a few weeks once data has been consolidated and a base model has been created.