AI in Healthcare: Transforming Personalisation in Digital Health Platforms

The Evolution of Personalisation in Digital Healthcare

In today's digital healthcare landscape, personalisation is no longer a luxury but a necessity expected by consumers. According to a Mckinsey study, 71% of consumers anticipate receiving personalised interactions from health services. The strategies have thus shifted from broad segmentation to heightened individualisation, which can be broken down into four distinct phases:

Phase 1: Broad Business Unit Segmentations

• Initially, health-tech companies employed broad segmentation corresponding to main business lines, treating different services like e-pharmacy and lab tests separately.
• This approach led to generic promotions without great customer resonance.

Phase 2: Omnichannel Personalisation

• With the rise of digital, there emerged a need for a cohesive omni-channel experience.
• Marketing efforts combined platforms like apps and websites with offline touchpoints to convey uniform messages.

Phase 3: Micro-segmentation by Condition or Need

• Healthcare providers began analysing specific health conditions and customer needs for a more nuanced segmentation.
• Personalised content tailored to conditions like diabetes or asthma became pivotal.

Phase 4: Individualised Personalisation Driven by AI

Today, AI facilitates a segment of one approach, analysing purchase histories and user behaviours to create uniquely tailored interactions. For instance, if a user frequently orders allergy medications, AI can proactively offer timely coupons or act as a health coach. This level of personalisation is essential for fostering long-term trust with consumers, enabling better healthcare outcomes.

Ultimately, the future of health tech marketing hinges on delivering genuine value to the customer journey while enhancing patient care, thus moving beyond mere promotional efforts.