How AI and ML are transforming healthcare marketing

Authored by Indusekhar Chandrasekhar, Senior Vice President and Head - Brand, Marketing & Strategy, Thryve Digital Health LLP.

“The art of marketing is the art of brand building. If you are not a brand, you are a commodity” – Philip Kotler.

The pioneer of marketing was spot on in his assessment of the impact of brand marketing. In today’s digitally-driven landscape, the need to remain connected to the audience has only become greater, and people expect key services such as healthcare to deliver the desired support and outcomes. This dynamically evolving landscape requires the integration of top-of-the-line AI and machine learning capabilities into the marketing framework. The impact of AI and ML on healthcare delivery is well documented, and now let us look at their role in healthcare marketing.

Greater personalization – Healthcare services have a significant social angle, and that’s where personalization plays a critical role. With the help of AI and ML algorithms, healthcare marketers can deeply analyse patient data, preferences, and behaviours to craft highly personalized as well as relatable marketing campaigns. The key to building trust is to deliver relevant information and services which are customized for the individual needs. This ability can help establish a stronger patient-provider relationship and drive engagement for the brand.

Predictive analytics – It is possible to analyse historical data of disease prevalence through AI-driven predictive analytics techniques. This can help predict patient behaviour related to services such as appointment cancellations or the possibility of medication adherence etc. This data can help healthcare marketers to optimize resource allocation and design campaigns that better engage the audience, effectively retain them, and drive awareness about the importance of issues like medication adherence.

Chatbots and virtual assistants – During the pandemic, we saw how AI-powered chatbots and virtual assistants played a key role in spreading mass awareness and handling the flood of general queries. This experience has clearly demonstrated how these systems are capable of instantly responding to a large number of patient queries, from anywhere and anytime. These can also be used to schedule appointments, explain processes, or to guide people through the potential course of treatment for their conditions. This is helping improve the overall experience of engaging with a healthcare brand and making care more accessible.

Targeted marketing – ML algorithms have proved to be highly beneficial for health marketers when it comes to patient engagement. These can create precise segmentation based on demographics, health conditions, and preferences. This insight enables the marketers to create targeted advertising campaigns that can reach the right audiences with relevant content, drive engagement and achieve higher conversion rates.

Capitalizing on context – With healthcare red flags constantly emerging, the need for healthcare marketers to seek relevance in these red flags and prepare for market opportunities is critical. The pandemic for instance induced a collateral market for products across the spectrum. Smart marketers will look at use-patterns (preference and frequency in use) and need-extensions (new demand for allied products or services)  tocreate effective marketing strategies.Like for instance the rise in the market for air-purifiers and immunity building supplements during a flu season can be combinedwithautomated tele-health alerts for preventive care.

Amplifying the creative output – As AI generated design suits across Adobe and Figma make agile designing real, ChatGPT is accelerating the speed of spot-on content with A/B testing capabilities that instantly deconstruct complex healthcare narratives and imperatives that have traditionally dogged effective marketing content creation.

Greater market access – AI has made it easier to access critical medical evidence, and market access information as well as clinical trial results locally and globally. The automation of data collection and analysis has enabled healthcare marketers to make decisions with greater speed, and accuracy. Today, this quick and accurate decision-making ability is key to navigate the frequently changing regulatory landscape and the market dynamics. The entire process has become more agile and insightful for all stakeholders, enabling them to better navigate the regulatory landscape and market dynamics.

Honouring ethical obligations – Healthcare is one of the most sensitive industries, and there is a lot of regulatory as well as ethical oversight that marketers need to consider. There is no doubt about the immense potential that AI and ML offer, but it is important to ensure patient privacy, avoiding bias in ML algorithms, and maintain transparency in the decision-making process. By prioritizing ethical obligations, healthcare marketers can correctly harness the power of AI, and protect patients from misinformation and any risks to their wellbeing. AI/ML tools by their very nature offer “perimetering” capabilities that avoid “error-creeps”.

While healthcare marketers have often preferred discretion in the choice of marketing tools and techniques, AI/ML driven transformation is real. Adhering to ethical obligations and embracing innovation can help them harness the full potential of these technologies to build stronger, more inclusive, and resilient healthcare ecosystems globally.