Beyond social listening: A framework for actionable marketing insights in pharma


By Rucha Pandit, Principal Consultant, USA, ATCS

Over the past decade, pharma companies have experimented with social media to drive customer engagement and build a positive brand image. However, the Covid-19 pandemic has pressed pharma presence further in the social space. It is obvious as most discussions related to vaccine trials, health products, and pharmaceutical research happened online in 2020, which held valuable insight for pharma companies about customer needs and pain-points. Social listening, which is now broadly used for marketing insights, has emerged as a powerful tool for pharma and biotech companies to track and analyse public sentiment, as well as, their true share of impact.

Leading pharma companies are now tapping into social and digital media for uncovering meaningful customer insights to make sure their product development and marketing strategies resonate with their customer’s expectations. During the Covid-19 pandemic itself, pharma companies requested social listening work from digital agencies to retool their media plans, sales material, and social media messages according to the market pulse. Social listening, when done right, allows pharma companies to track customer experiences, brand perceptions, sentiment drivers, influencer perspectives, caregiver concerns, and a lot more.

Last year was promising for social listening in the pharma sector as patients and doctors formed strong opinions online. Almost, every seventh person across the globe has shown some form of participation in Covid related conversations surfacing online, which created large volumes of unstructured big data with rich insights. Twitter was the most used platform with 628 million tweets related to coronavirus till May 2020.

Fear of the Unknown

Despite the active social engagement recently, many pharma companies are still skeptical when it comes to leveraging social listening tools and digital data. That is because their brand managers do not know how to fit these tools in their marketing mix. Besides, lesser clarity over such digital projects’s ROI and relatively less experience also make pharma companies limited to old techniques of primary market research that are proven and less risky.

The hesitant approach of pharma companies towards social and digital engagement where currently social data is only thought of as a quantitative input, rather than also being considered a qualitative insight to their broader strategy.  Some other reasons behind the approach of pharma companies are as follows:

  1. Insufficient Quality Information: The foremost reason why most pharma companies are still uncertain about leveraging social and digital data is because of the high volume of noise. The presence of huge volumes of data on social platforms makes it challenging for companies to filter unnecessary information.

2.  Ownership Dilemma: Despite growing efforts, social media largely remains unchartered territory for the pharma sector. Those who are leveraging it are also unable to realise its true potential as they have confined themselves to tracking follower counts, brand mentions, and conversation volumes. The dilemma of ownership can be observed, and brands are unsure whether the ambit of social media monitoring falls under R&D or marketing.

3. Adverse Event (AE) Reporting Challenges: The absence of proper legislation and clear regulatory guidelines for adverse event reporting on social channels also limits pharma companies from active participation. Companies are doubtful that their active participation will heighten the number of adverse drug experience cases online, which could be costlier and time-consuming for them in terms of the investigation.

To exploit the social media potential to its fullest and overcome the listed challenges here, pharma brands can institute the three-element framework comprising of technology, knowledge, and compliance for drawing meaningful customer insights from social platforms in a timely and well-organised manner:

Technology: Advanced Analytics and Machine Learning (ML)

By combining big data technologies and advanced text analytics, pharma companies can enable automated monitoring across platforms effectively. Edge computing concepts (ML, natural language processing, and semantic composition) powered smart algorithms are already accelerating the filtering process of unimportant information from large volumes of social data. The noise is blown out to make sure only relevant data goes forward for analysis.

Applying such a technology system can be particularly useful for identifying various author profiles and their intentions in a dynamic customer base. For example, identifying opinion leaders driving impactful social conversations about a particular category.

Pharma sector companies are also racing for this level of influence on consumer health decisions and behavior. For that, all their social listening activities must be measured against the share of voice or brand equity they create through social engagements.

Compliance: Partnership with Experienced Suppliers for AE Reporting

Pharma companies can address the legal issues around AE reporting on social media by teaming up with an expert technology supplier who makes sure internal compliance and legal requirements are met. Ideally, such a supplier should be able to deliver a customised, automated solution that can identify, classify, and report AEs in line with the company and region-specific compliance guidelines. Techniques like advanced text analysis can speed up the AE detection via such tools, having such a system in place will assist the pharma sector to overcome compliance issues greatly.

Social media listening paired with advanced analytics helps pharma companies garner valuable insights from customer’s interactions on social media. With careful utilisation of social listening tools, they can create better-targeted campaigns, stop the spread of misinformation, uncover new product ideas, measure market sentiment, track influencers, and analyse brand switching behavior effectively.


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