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Smart content engines are real-time decision engines, powered by machine-learning algorithms to deliver personalised modular online content that is relevant to the individual healthcare professional (HCPs) at an exact moment in time.

The healthcare industry continues to undergo a transformational shift, with technology being a key driver. The use of machine learning to enable website content personalisation promises to dramatically improve the value of medical content accessed by HCPs, and ultimately enable better-informed clinical decision-making.

HCPs are facing a significantly more complex information landscape with more digital channels and increasing volumes and complexity of clinical data. Healthcare companies need to adapt to deliver medical content to HCPs that is accurate, relevant and understandable. Since the pandemic started, many HCPs have felt they are struggling due to the vast amount of information they need to consume, and a significant proportion feel ‘spammed’ due to the amount of information, often irrelevant, that they receive. In other sectors, smart content engines have been shown to give a 35%+ increase in audience engagement and over 100% increase in on-site conversion.

Implementing the use of smart content engines in the healthcare space provides a rich and relevant content experience that will lead to increased engagement with content and will help HCPs to inform themselves effectively along their learning journey, empowering them to make better decisions for their patients.

Smart content engines work alongside the technology platforms already in place, with the added value of bringing content personalisation to life in three key ways.

1. Machine learning is a powerful technology that can help healthcare companies personalise delivery of content for HCPs. By analysing data from HCP interactions with emails and on websites, machine-learning algorithms can identify patterns in user behaviour and preferences in real time, enabling companies to tailor their communications with individual HCPs by powering website personalisation.

2. Modular content strategies are important when using multiple channels for communicating complex medical content to HCPs. Content is broken into small modules in varying formats, which can undergo medical, legal and regulatory (MLR) review and approval, and then be used across multiple channels. Modular content strategies allow more flexibility in using pre-approved content that can be combined in different ways, according to the omnichannel communication strategy.

3. HCP website personalisation is achieved through the deployment of real-time machine-learning algorithms (data analytics and personalisation recommendations) that enable the web pages to adapt and evolve based on individual HCP real-time behaviours. Once activated, algorithms can be trained to tailor the HCP engagement with the relevant modular content in line with HCP needs.

When machine learning and modular content are combined within a smart content engine, the result is a powerful tool that delivers personalised, understandable information to individual HCPs across touchpoints.

Here are some of the ways that you can use this approach to improve communication:

Delivering personalised experiences: personalised content can be delivered to HCPs based on their unique needs and preferences.
This can build trust and improve engagement by making it easier for HCPs to find the exact complex medical information they need at that precise moment
Optimising the HCP learning journey: the delivery of clinically relevant content can be optimised to meet HCP’s needs at any given point in their individual learning pathway. Additionally, the data collected can help MSLs to understand HCPs’ needs and, for instance, ensure they proactively bring the most useful information with them to meetings
Personalising email campaigns: machine-learning algorithms analyse data from HCP interactions to identify common themes and preferences allowing creation of personalised email campaigns that address specific and validated information needs and concerns. Emails are created for HCPs opting in, with follow-up links to MLR-approved modules of medical content that not only meet the HCPs’ real-time need, but are also easy to digest. This can lead to a 15% increase in clicking through to the relevant healthcare company website
Understanding what content works: unbranded or third-party websites are an increasingly important communication channel for the healthcare industry. By using machine-learning algorithms, healthcare companies can identify common interests and topics, and tailor their landing page content accordingly.

In conclusion, healthcare companies should embrace website content personalisation to ensure they meet HCPs’ real-time needs. While the jury is still out on how to apply generative artificial intelligence (AI), the use of machine learning is a proven value-add, with tools that can give audiences content they genuinely need to support their personal online learning approach. This results in higher HCP engagement, delivering value and building trust with healthcare companies, and crucially, ensuring that HCPs have the most relevant information exactly when it is needed.

Smart content engines: personalising medical content to meet healthcare professionals’ real-time needs