…and the power of analytics has proven to be a core lever of accelerating commercial performance. Since Covid, the role of the rep has been under scrutiny – and with the declining influence of the sales force, the pharma industry is finding new ways to revitalize its engagement strategies and how to surface insights – ultimately redefining its commercial models.
The topic of AI naturally got much attention and with good cause. While in some instances, it was discussed that AI ultimately would make the sales force obsolete, the majority, however, saw AI accelerating the need for a personalized customer experience. AI can indisputably help with effective call planning, field routing, and content selection – but in the future, delivering personalized key messages and a solid customer experience becomes a vital lever for building HCP-trust and credible interactions.
Complementing the topic of increased focus on customer experience, three other closely linked matters were heavily discussed – all with the purpose of ensuring efficiencies, increasing the quality of interactions, and delivering yield from commercial efforts:
In a nutshell, the traditional way of commercial engagement has been through a brand-centric approach. Basically, through a brand, one has historically deduced assumptions about what key messages a given HCPs or segment might want to see and hereafter targeted that HCP by automating the delivery of the message in voluminous touchpoints.
Next Best Action (NBA) makes up for this – among a universe of actions, NBA is intended to deploy models that use predictive analytics to recommend individual HCP-level content and channels based on historic interactions and touchpoints; and, thus, deliver carefully selected messages that are sequenced through a journey.
The pharma value chain is one of the longest, and omnichannel customer engagement helps in shortening this as much as possible. The pharma industry is currently moving from a multi- to an omnichannel approach for customer engagement – an instrumental change to be able to truly harvest the power of predictive analytics (ref. point 1). This implies systematizing customer information to enable the delivery of content in successive engagements.
Omnichannel is all about personalization – but personalization is not the destination, rather, omnichannel customer engagement is an ongoing process of gathering, analyzing, and applying data to improve marketing material and campaigns.
While Natural Language Processing (NLP) has many obvious use cases in e.g. pharmacovigilance, medical literature reviews, and working with Real World Evidence, it is yet to ratify its position in the frontline toolbox. NLP is ultimately about unleashing the value of unstructured data by identifying novel connections and relationships in, e.g., free text.
Combining data points in the shape of, e.g., structured information like objections and reactions from frontline interactions with free-form text such as MSL and sales rep call notes and triggered surveys with free text fields will enable insights into HCP’s opinions, not just behaviors – all empowered through careful sentiment analysis, that ultimately will allow for increased personalization and targeted interactions across digital as well as physical channels.
All in all, it has been a great experience being part of the Reuters Pharma 2023 Conference in Barcelona – and the above insights from the conference all underline the importance of data and analytics as a vital component in the commercial models of tomorrow in pharma. We look forward to being back again next year!