KMK President Michael Karbachinskiy was featured in PM360 discussing the use of AI and Machine Learning in pharmaceutical sales.
The best use case we have found for predictive analytics is in helping to improve pharmaceutical sales force effectiveness and to bolster the activities of sales reps by using data-driven insights. While predictive analytics is widely used to estimate the number of calls to be delivered and several other tasks, AI is still very new on the commercial side. But one application we have found to be good use of AI/ML is for the rep’s next-best-behavior to be calculated and communicated constantly in real time.
When sales reps are operating in territories under similar conditions (the same quality of targets, managed care, etc.), but performing differently, AI-powered predictive analytics can provide clues on how to improve sales behavior.
Improving Sales Rep Performance
Reps do not have an easy way to know what they need to change to sell more. By using AI to track and monitor the process, we can analyze rep behavior within similar territories and show reps the best specific behaviors that will most likely improve sales results. Over time the algorithm continues to learn and adjust and improve upon best practices.