AI & Commercial Processes in Pharma: Hype, Hope, or Your Next Competitive Edge?
If AI isn’t in your sales strategy yet, what’s your plan B?
- On: March 13, 2025
Miguel Angel Martos
Commercial Excellence Director
How can AI help identify and segment key prescribers more effectively?
The main barrier we face in understanding the prescription potential of health professionals in most European countries is the granularity of the available information. To overcome this, we rely on more qualitative variables such as specialty, participation in medical congresses, publications in medical journals, and activity on social media.
To effectively analyse these variables, we employ advanced analytics techniques, specifically clustering. Clustering allows us to classify health professionals into distinct groups based on these qualitative factors.
Once these groups are established, we can analyse the promotion elasticity at the most granular level of data available. This enables us to observe the impact of our promotional efforts in terms of incremental sales, providing valuable insights for more targeted and effective marketing strategies
What KPIs should companies track to measure AI’s impact on commercial success?
Some of the KPIs that can be measured to assess AI’s impact on commercial success include:
Sales Growth and Market Share (MS%) Growth: Compare sales growth and market share percentage growth in areas where AI-driven improvements have been implemented against areas with similar characteristics where they have not (test and control groups). This helps isolate the impact of AI projects.
Share of Voice and Perception of HCPs: Measure the share of voice and gather feedback from HCPs on the quality and impact of visits. Assess the effectiveness of messages across different channels based on HCP’s perceptions of content quality. This can include metrics such as Net Promoter Score (NPS) and the impact on their Rx intention.
Customer Engagement Metrics: Track customer engagement metrics such as click-through rates, open rates, and social media interactions. AI can help optimise content and communication strategies to boost engagement and ensure that messages resonate with the target audience.
By monitoring these KPIs, companies can gain valuable insights into the effectiveness of their AI initiatives and make data-driven decisions to further enhance their commercial strategies.
What are the biggest challenges in integrating AI into existing commercial processes?
Integrating AI into existing commercial processes can present several significant challenges. Here are some of the biggest ones:
Data Quality and Availability: AI systems require large amounts of high-quality data to function effectively. Ensuring that data is accurate, complete, and accessible can be a major hurdle. Additionally, data may be siloed across different departments / systems, making it difficult to integrate.
Change Management: Introducing AI into existing processes often requires a cultural shift within the organisation. Employees may be resistant to change, so effective communication strategies are needed to gain buy-in within the organisation.
Regulatory and Compliance Issues: The use of AI in commercial processes must comply with industry regulations and data privacy laws. Ensuring that AI systems adhere to these requirements can be challenging and may require additional oversight.
Still relying on old-school sales tactics? Discover how AI changes the game from Miguel’s insightful case study titled “The Use of AI In the Commercial Process”.
Join the 2nd Annual Pharma Commercial Excellence Summit on the 2nd – 3rd of April 2025 at The Westin Madrid Cuzco!
Short Speaker BIO:
Miguel Angel Martos is a dedicated professional with a strong focus on innovation and artificial intelligence (AI) in the pharmaceutical industry. In his role as Commercial Excellence Director at LEO Pharma, Miguel is responsible for Business Intelligence, Forecasting, Sales Force Effectiveness, IT platforms, Alliance Management, Business Development, Strategic Projects, and Wholesaler Management. His work in dermatology products has contributed to the company’s ongoing efforts to improve patient care and operational efficiency.
Miguel is particularly passionate about integrating AI-driven solutions to enhance decision-making processes and optimise sales strategies. His efforts in leveraging innovative technologies have helped streamline various business functions at LEO Pharma.
Prior to his current role, Miguel gained valuable experience at EY and other advisory companies, where he developed skills in consulting, strategic planning, and project management. His time at EY provided him with a solid foundation in business development and the implementation of new technologies.
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