How machine learning will change pharma marketing in 2018

Artificial intelligence and machine learning will have a major impact on pharmaceutical marketing in 2018. These developments are just beginning to scratch the surface of their true potential, but significant strides will be made, even at this early stage of the technology. Machine learning algorithms give marketers the ability to glean important insights from tracking data, allowing them to make more informed decisions.

In 2017, machine learning started to take off. In 2018, it will become a powerful tool in the pharma marketer's belt.

Artificial intelligence and machine learning as marketing tools

If it seems like you read the words machine learning and artificial intelligence every time you go online, it's no mistake. A quick look at Google Trends shows that searches for those terms have skyrocketed since 2015. Almost every industry on Earth will be disrupted or reshaped by powerful learning algorithms that can perform tasks of which no human being is capable. The field of pharma marketing is no different.

One aspect of marketing that artificial intelligence will likely disrupt is the long-held practice of A/B testing. Rather than putting out two advertising options into the marketplace and watching for reactions, a predictive intelligence notices subtle changes in ad engagement, steering the course of the campaign automatically. As PM360 noted, this method of real-time ad personalization is much more effective than standard A/B testing because it is much more granular. Not only does it take into account wide-sweeping audience trends, but also patterns of individual users.

Rather than breaking down audiences into generalized subcategories, a powerful AI could deliver content that is relevant at the individual level. That said, predictive intelligence isn't omniscient - it needs reliable data to produce trustworthy results. Therefore, marketers will need to utilize robust data tracking and metadata analysis to craft winning campaigns.

Artificial intelligence and machine learning algorithms can replace A/B testing.

Pharma marketing and predictive analytics

In the past, pharma marketers relied on historical data of past behaviors to inform their future marketing campaigns, especially when marketing to physicians. By analyzing survey data and behavioral reports, marketers have used previous actions to predict future behaviors. In a sense, AI and machine learning do that better - but they also do more.

According to analytics expert Kevin Troyanos, writing a guest article for PM360, predictive targeting paints a much more detailed picture of health care providers. Troyanos explained that a learning algorithm can comb through mountains of data in rapid order, then use that data to make predictions about an HCP's propensity for prescribing new medications and treatments. Not only do these algorithms take into account the doctor's past prescribing history, but also their demographic information and educational background.

What this amounts to is a mountain of data, processed at very fast pace. This enables marketers to make informed decisions more quickly. They will be able to adapt to new situations with ease, targeting HCPs with more granularity than has ever been possible.

Machine learning throughout the care continuum

No sector of the medical industry will be left untouched by the sculpting hand of artificial intelligence. From electronic health record technology to surgical practices and everything in between - digital tools are the future of healthcare. Pharma marketers who adopt this technology today will likely see great performance strides. In 2018, machine learning tools are the closest the industry has come to a holistic approach to HCP-targeted marketing.

Though the analytic methods are changing, the channels - print and digital - are the same. To learn more about how to leverage machine-driven content in today's crowded market, visit ELSMediaKits.com today.