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The two technologies are helping HCPs spread information and collect data in new ways.
More industries are prioritizing social media as they recognize its significance for appealing to consumers. Healthcare and life sciences are no exception. For healthcare professionals (HCPs), social media is now a driving force for disseminating information, advocating for change, and connecting with patient communities and peers.
According to a survey of more than 4,000 physicians, nine out of 10 physicians use social media for personal reasons, while two-thirds use it for professional reasons—a number that is growing higher every day.1 One UK study showed that HCP posts about healthcare increased from 10% in 2013 to 50% in 2019.2 And, according to Sermo’s May 2022 Physician Impact Report, two-thirds of physicians spend an average of two hours and 22 minutes on social media platforms a day.3
“While social media engagement among HCPs varies, our data shows emerging digital opinion leaders engaging in relevant social media conversations in certain markets at least once a day,” said Siniša Slijepčević, founder and CEO of Cantab Pi, Aktana partner and leading data analytics and machine learning technology company. Cantab Pi brings dynamic targeting capabilities and more than two million HCP profiles from a range of sources, including social media and clinical journals, to Aktana’s Contextual Intelligence platform. “The number of posts directed towards peers is doubling in many markets—the more specific, innovative posts prove the most engaging for HCPs. For instance, top physician influencers routinely publish links to therapeutic-specific presentations after speaking at a conference, and these often garner the most interactions.”
Novartis is the first to implement the blended solution. “We have a business imperative to harness as much intelligence as possible from the wealth of data we manage,” said Paul Thompson, global director of AI enablement and orchestration at Novartis.
Modern technologies like AI and machine learning will be critical to helping life sciences commercial teams orchestrate interactions across a mix of traditional and non-traditional customer engagement channels. AI quickly finds patterns in volumes of data, capturing social media behavior to suggest the next best action to take with an HCP or the best content to serve up. Natural language processing captures valuable sentiment data from HCPs who are sharing content, retweeting articles, and annotating news announcements. As HCPs divulge attitudes, preferences, and interests via social, pharmaceutical companies will need to pay better attention—especially when trying to deliver more valuable content to HCPs already inundated with information.
Similarly, pharmaceutical companies can use social media to find key opinion leaders more effectively—a process that is often manual and inefficient. Analytical methods can be applied to social media datasets to help medical science liaisons quickly identify established and emerging leaders with the greatest influence in their therapeutic areas and learn more about the type of content they find most relevant.
In life sciences R&D, AI is inspiring exciting advances—such as DeepMind’s AlphaFold, an AI systemthat has predicted the structure of more than 200 million proteins. Now, AI is also showing its value in commercialization, especially in analyzing the volume of new data sources available (with social media being just one). AI is becoming a vital technology for sales and marketing teams, as well as medical science liaisons (MSLs), who are struggling to discern the most productive ways to engage with HCPs.
“I recognize that social media is only one piece of the omnichannel customer engagement toolkit,” explained Slijepčević. “But applying AI to social media allows you to know what your customers are thinking and saying when you are not in the room for an accurate understanding of their interests and needs.”
Intelligence platforms designed to incorporate all data sources are the key to optimizing omnichannel customer engagement. By ingesting a wide range of data sources, intelligence technology can better inform commercial and medical teams for more personalized interactions with customers. Social media is a critical data source that life sciences companies are not yet maximizing to its full potential—for instance, some are starting to search social media to learn of key digital opinion leaders but far less are capturing insights for all of their target HCPs active on these platforms.4
How it Works
Using a combination of various technologies and analytics skillsets, an AI engine aggregates data from multiple external data sources, such as scientific publications, social media, and clinical trial databases. Raw data is interpreted by advanced machine learning/AI, then synthesized into next-best-action recommendations and customer insights delivered directly to sales representatives, marketing teams, and medical science liaisons in their respective tools. HCPs can benefit from more relevant interactions with the pharmaceutical industry including more high-value content, providing specific disease-state information they want.
Some examples of how this translates into real-life action include:
AI can also help companies identify digital influencers and recommend specific actions or content to serve those influencers. For example,Cantab Pi calculates digital and traditional influence scores for each customer by deploying advanced algorithms on data such as social media followers, engagement on social media posts, co-authorship of scientific papers and related citations, event participation data, and more. From this, intelligence platforms can recommend tailored next-best-actions for the top digital opinion leaders in a market.
Additional use cases include using AI to map out the optimal customer journey, such as the optimal event to invite a speaker or the right time to send an invite or follow up.
Assessing Business Value
AI is already being deployed to commercial life sciences teams to optimize HCP engagement, providing next-best-action recommendations that include engagement timing, channel, content, and sequence of actions personalized for each HCP. However, with the addition of social media data, AI-powered recommendations are significantly more effective.
“It really all comes down to personalization,” said Erin Fitzgerald, Chief Marketing Officer at Sermo, a physician social platform engaging with more than 1.3 million HCPs across 150 countries. Sermo provides physicians with a professional community that fosters peer-to-peer collaboration. “AI-driven insights make it possible for life sciences companies to meet customers where they are with personalized content, format, and sequencing. HCPs are inundated with content, so the more relevant it is, the more likely HCPs will engage.”
In a series of Cantab Pi pilot studies, email click rates increased 2.5-3 times as compared to the control group. One global pharmaceutical company increased sales by over 3%—translating to 30% faster sales growth—after four months of deployment to 40 sales representatives in Europe compared to the control group. Additional KPIs such as positive responses to surveys and conversion to digital channels also demonstrate statistically significant positive results.
Social media data also contributes to the accuracy of the next-best action suggestions. “About 30% of the accuracy of a recommendation can be attributed to social media and other similar public data sources, while the other 70% is linked to internal data sources,” explained Slijepčević. “This ratio goes up to 50% for key influencers as there is a strong correlation between social media data and an HCP’s influence.”
Semi-private, physician-only social media platforms like Sermo’s may offer additional value compared with open, all-purpose social channels like Twitter. According to Sermo, 86% of HCPs say they value the information on physician-only platforms and nearly 9 in 10 view this information as credible.5 Almost 40% of surveyed HCPs follow pharmaceutical companies or branded treatment accounts on physician-only platforms.
Either way, it’s clear that social media is increasingly well used by HCPs. One surveyed doctor said, “instead of reading the content in a name-brand ad to learn more, I’ll search for that brand on social media to get the patient perspective.”6
Expect to see the use of social media data to inform commercial decisions not only continue but accelerate. Baby Boomers or “granfluencers” are joining the younger generation of physicians as digital influencers. Regardless of age or demographics, social media activity increases HCPs’ professional reputation, according to a 2021 study.7
“There is such momentum in the number of HCPs joining the social media conversation that it is becoming part of their professional portfolio. If you want to be a leading physician, you need to be active on social,” said Slijepčević.
Social media will become increasingly more crucial in supporting omnichannel engagement in life sciences as the sales model evolves. For instance, sales territories are becoming larger, thanks to the internet making geography less of a restriction. And as daily consumer experiences continue to raise HCP expectations for personalized engagement, life sciences companies have a lot to gain from online dialogues that capture detailed information around HCP interests and preferences.
“At the beginning of the pandemic, physicians leaned into online communities and other social media platforms to debate things like the use of oxygen therapy to treat COVID-19 patients,” added Fitzgerald. “Peer-to-peer communities provide a trusted, collaborative environment that is highly contextual. We have seen steady growth since 2019 and expect it to only grow faster across all social media platforms.”
Prudence in Deployment
The data and the early experiences of forward-looking life sciences companies point to social media as an important data source where AI can yield significant advantages. Yet, it’s also prudent—and even critical to its long-term benefits—that companies consider the best practices around collecting data privacy and securing customer consent. “I would add that we need to introduce some new best practices related to pharmacovigilance, too,” said Slijepčević.
Adding Social Media to The Medical Bag
Social media should be just one element in the next-best-action equation. The more quality data sources about HCPs, the richer and more reliable the AI-generated insights about those HCPs to inform a better omnichannel engagement strategy for commercial teams.
More importantly, it’s important that life sciences companies don’t forget the value of the human in any AI undertaking. Though we live in an age of fast technological innovation and vast computing power, human insights remain indispensable particularly in developing long-term relationships with doctors. Human inference and nuance are crucial in spotting anomalies, identifying patterns, drawing sensible conclusions, and interpreting sentiment undertones. Success will ultimately be a joint effort, where AI augments the skills of human sales representatives, brand managers, and MSLs.
About the Author:
As a senior product manager, Sam McClain is responsible for Aktana’s Contextual Intelligence Engine and out-of-the-box machine learning modules. Previously, he worked as part of Aktana’s Services Team as a Delivery Engineer and Solutions Architect. Sam can be reached at email@example.com.