Artificial intelligence has enormous value in research in pharma.
Another great use of Artificial intelligence is in pharma marketing. Marketing requires numerous complex decisions that have traditionally been made based on a great deal of qualitative – not quantitative – data and, let’s be honest, gut feeling.
That doesn’t work in today’s multi-channel, data-driven environment.
Artificial intelligence simplifies the marketing executive’s ability to process large volumes of customer data and obtain accurate and consistent findings that can result in improved sales and real-world financial results.
Specific marketing challenges that machine learning algorithms can address include:
·Understanding of optimal strategic direction
·Enhanced value proposition identification
·Enhanced competitor differentiation
·Ability to see which segments will offer the most value to your brand as well as what levers to pull to maximize the growth from them
·Optimal resource and budget allocation for maximum market share gain, revenue and profit
·Rx switch prediction and correction
Many pharma marketers are behind the game when it comes to artificial intelligence based analytics. Very few are implementing leading edge analytics on good data that involve artificial intelligence, especially machine learning and deep learning. But these all exist already for pharma marketers, are simple to use and get strong results.
“Currently the main uses of AI are in research areas,” says Bates. “AI is far superior to human analyses, as it can analyze vast quantities of data that don’t fit into conventional computers.” It is also believed that the processing powers of AI are superior to other tools. In research on gene mutations, for instance, AI can churn through huge amounts of data and find valuable information.