The pharma industry has been engaging with its consumers on social media for almost a decade now. Companies have become adept at using social media, and over time, their social campaigns have grown in scope and impact. One of the earliest successful social media campaigns was from Boehringer Ingelheim,1 in 2010; a celebrity-led campaign to drive awareness and screening for Chronic Obstructive Pulmonary Disease (COPD). It resulted in over two million Americans getting screened in less than two years.
By 2016, pharma companies had moved on to conducting a remote phase IV trial online, with patients being recruited on Facebook, 2 as well as crowdsourcing 3 of clinical trial protocols involving inputs from physicians and patients. Geographically or demographically focused campaigns to aid drug discovery, drug launches or regional growth are other areas where big pharmaceuticals have explored the effectiveness of social media.
In the process, pharmaceutical and biotech companies have also understood the importance of ‘social media listening’ in monitoring social media effectively and transforming millions of posts from physicians, patients and caregivers into valuable insights. Most large companies today have a comprehensive social media listening setup that includes coverage of conference websites, blogs, message boards or forums, video sharing sites, and social media platforms such as Facebook, Twitter, YouTube, Instagram, and more.
Despite the growth in social media engagement, the overall consensus is that most pharmaceuticals still struggle to truly utilize the power of digital and social data. True regional engagement, structured participation in forums and adopting multi-media formats like video posts are some of the next obvious digital outposts for pharma. However, few leading life sciences companies have ventured into these areas, perhaps because there isn’t enough clarity on the reactions or returns they can expect from such outreach programs. Underlying this apprehension are a few inherent challenges that pertain to social and digital engagement that include:
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Quality: Besides being fragmented and ephemeral, up to 50 percent of social media data is pure noise; and like all high-volume data scenarios, bad data can easily lead to bad insights
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Context: Without context, even good-quality data can deliver no insights. Layering social listening with the right domain taxonomy is crucial to understand the market, its active participants and their behavior
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Metric: Numerous studies have shown that the number of followers or volume of engagement do not guarantee pharma companies a competitive edge. Companies thus face challenges in measuring their true share of voice and brand equity when it comes to social media
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Regulation: The regulatory guidelines regarding Adverse Events (AEs) reported over social media are still evolving. Many life sciences companies fear that extensive social interactions can trigger more adverse drug experience reports online, requiring them to conduct a number of costly investigations into each event
To elevate their social media game beyond these challenges, pharmaceuticals should adopt a four-piece framework comprising of technology, domain, compliance and influence that can help generate trustworthy insights in a timely and prescriptive manner.
Technology: Advanced Analytics
Combining big data technologies with advanced text analytics offers companies the benefit of automated monitoring across platforms and formats, and also addresses data quality concerns. Edge computing concepts such as Natural Language Processing (NLP), semantic composition and Machine Learning (ML) are already helping in the development of intelligent algorithms that identify and segregate non-relevant information from large social data pools. The noise is filtered out and only the relevant data is taken ahead for analysis.
This technology set also helps identify various participant profiles and their motivations in a dynamic customer base, and can highlight influencers and leaders. It can also help visualize new classifications and segments of consumers for effective targeted campaigns. Finally, advanced analytics ensures that the data selected as input has high sensitivity to the events and promotions, providing the opportunity to tease out relevant insights.
Domain: Contextualization of Social Data
To identify the context in social data related to a particular therapy area, ML algorithms should be augmented with taxonomy and ontology developed by therapy area experts. This ensures that the sentiments and context of the customer discussions are appropriately tagged, increasing the richness of the information. This is particularly important as it allows in accurately capturing a brand’s share of voice against competitors and identifying key themes in the industry.
Building domain sensitivity into social listening can be a challenge since an effective research area or therapy-specific ML algorithm would have to be trained using millions of relevant customer conversations. Pharma companies should ideally adopt technology solutions that come bundled with relevant ontologies and theme sets.
Compliance: Regulatory Back Up for AE Reporting
Advanced text analytics is helping companies develop a separate workflow to capture AEs mentioned on social media. Pharma companies already have a strong mechanism to capture and store AEs reported through traditional channels. The same parameters from existing data are being used to develop a taxonomy to identify and segregate AEs from social data. The workflow is then routed to the appropriate compliance team without being included in the social listening analysis.
Even as regulators and stakeholders debate the validity of mandating the reporting of AEs mentioned on social media, putting such a mechanism in place will help the pharma industry get ahead of potential regulatory roadblocks.
Influence: Competing on Share of Voice & Brand Equity
According to a social media 4 study, over 40 percent of consumers say that social media impacts the way they handle their health. Pharmaceutical companies are essentially competing on social media for this potential influence on consumer behavior. All social media listening activities and the resultant insights should, therefore, be measured against the share of voice and brand equity a company garners through engagements.
Pharmaceuticals should look beyond metrics such as community size, number of posts or volume of engagements to track a unified brand metric comprising brand perception, campaign return on investment, reach and share of voice across all platforms. This should then be supported with intelligence on competitor campaigns and early detection of trends to help devise the right campaign strategy.
Active social listening enabled with big data technologies will allow pharma companies to efficiently harvest insights on perceived brand image, customer sentiment, brand switching behaviors, patient journey, unmet needs and other strategic business objectives. It will also allow them to measure the efficacy of their brand messaging quickly rather than having to wait for periodic primary market research.