Whitepaper: Using Artificial Intelligence and Machine Learning to Uncover True HCP Influencers
Using Artificial Intelligence and Machine Learning to Uncover True HCP Influencers
There is no doubt of the value for pharmaceutical and life sciences companies to effectively target and engage with health care providers (HCPs). Building relationships with key opinion leaders (KOLs) and collaborating with influential physicians and specialists is critical to longterm product growth and optimal patient outcomes.
Engaging with influential HCPs is also a better investment, returning approximately $6.50 in lift for every $1 spent on influencer marketing. It’s no wonder 68% of life sciences companies planned to increase their influencer marketing budgets in 2020.
However, the traditional mode of engaging HCPs is outdated.
By re-imagining HCP advertising sans the traditional prescriber-based or specialty list, medical marketers can uncover and activate the HCPs with the highest propensity to be brand ambassadors and ignore those less likely to create value. By applying artificial intelligence (AI), machine learning (ML) and evolutionary computation (EC) to real world data (RWD) it becomes possible to surface highly valuable influencers for channel optimization and increased Rx lift.
- Demonstrate the limitations of traditional HCP targeting.
- Outline a new methodology of identifying the most influential HCPs with the highest propensity to become brand ambassadors.
- Show how to get started with AI/ML solutions that deliver higher quality HCP lists to optimize channel spend and drive Rx lift