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The future of medical content: The personal touch

The purpose of delivering personalised content to HCPs is not just about customer experience, it's about improving healthcare. Our Commercial Director, Tib Catania discusses what ‘deep learning’ means for the customer.
Artificial Intelligence (AI) was the buzzword of 2016 with most industries already investing in its shameless promise of revolution. Its proven uses are multiple and dynamic, but what does it mean for the customer? The answer lies in customer experience (CX), the holy grail of modern commerce. The key is having the power to predict what the user wants to see before they make the request: personalisation of content. Those who can use AI to their advantage, in terms of providing the optimum CX, will inevitably gain the competitive edge. However, for the pharma industry, there is a deeper purpose to deep learning because providing today’s healthcare professionals with individually tailored content is not just about improving CX, it is about improving healthcare. A magnitude of data is at our fingertips and we must now learn how it can be best employed, and when it ought not be utilised at all.

The GP is provided with what is needed, when it is needed, thanks to deep learning and the personalisation of content. In other industries, personalisation of content is nice to have – users might discover new music in their preferred genre. In the pharma industry however, it is critical.

So what does it mean for the pharma customer? In the dark ages of technology, healthcare professionals (HCPs) had to be search engine maestros in order to find that crucial piece of information hidden among the cobwebs of cyber storage. A GP, for example, may have been aware of three different treatment methods for the disease in question. Modern technology has developed a further 30 possible treatment options, while the complexity of modern diseases and comorbidities have resulted in a further 300 treatment combinations. Now add to the mix the development of 4D virtual reality (VR) screening alongside genome modelling and the GP finds themselves with the perfect treatment option for that individual patient. The GP is provided with what is needed, when it is needed, thanks to deep learning and the personalisation of content. In other industries, personalisation of content is nice to have – users might discover new music in their preferred genre. In the pharma industry however, it is critical.


Data processing on this scale could never have been conceived before deep learning but now it’s revolutionising the healthcare industry. It is the responsibility of product designers and marketers to decide how to present this information once it is processed, at what time and to whom. Determining this strategy is the path to CX success. Utilising explicit data input by users, geotargeting and ‘favourite pages’ is an antiquated strategy but when it is combined with the implicit data gleaned from the deep learning process, the outcome is an entirely unique and personalised user journey. Every element of the HCP’s habits is analysed: content, search, location, habits of peers and even browsing times to generate predictive analytics. With this technology, users will be given the answer to the question they have not yet even asked. An exciting prospect for other industries, without doubt, but a time-saving and potentially life-saving stalwart for pharma moving forwards.

Unlocking the potential of personalised content is the next big challenge for pharma. A good CX requires more than just the ability to comment on articles and save pages to ‘favourite’, it requires notifications, calls to action and emails unique to each individual user, at the time of day when such an alert will be most productively received. AI learns from the response to each repetition and improves the experience on a continual basis so that the CX can only get better. Pharma companies like epgonline.org, with a vast, global user database, are in a prime position to learn from what AI has to teach us about the user to ensure that the right media is presented at the right time. Basic personalisation of content sends video suggestions to those who habitually watch videos; advanced personalisation of content sends a video of an important guideline update to users interested in guidelines but who would not always watch videos.

The future of digital pharma is multiple versions of the same page, made up of interchangeable content which displays to specific users at calculated times of the day.

As with most things in life, there is a caveat to employing the strategy of personalised content: The user wants to feel satisfied with the content they are offered but they do not want to feel monitored. It is clear that the capabilities of AI are abundant and seemingly limitless, which is why those who want to provide the best CX will need to learn how to impose limitations. Content that isn't shown is equally important to content that is shown. As with the compatibility problem which had to be overcome during the introduction of mobile devices, so the problem of which content to display to which user on any given web page will have to be solved. The future of digital pharma is multiple versions of the same page, made up of interchangeable content which displays to specific users at calculated times of the day. Any one page will appear differently for a dermatologist, a nurse and a lab technician. Finding that perfect balance of what content to display and what to withhold, combined with a fast and deep learning AI that doesn’t feel like Big Brother, is the solution to personalisation of content.







23rd February 2017

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