AI Omnichannel: Generating Revenue Through Optimization

I led the development and optimization of an AI-powered omnichannel marketing model within the Neuroscience division, driving an incremental annual revenue lift of $1.8M. The model integrated insights across eight channels, enabling personalized outreach and improving engagement with 20,000 healthcare providers across the US and Puerto Rico.

A key focus was refining the machine learning decision logic using factors like performance analytics, brand objectives, and user feedback to continuously improve the model’s effectiveness. This resulted in enhanced targeting and a more tailored approach, significantly boosting provider engagement and satisfaction.

The model contained 7 externally facing channels and one internal channel that delivered personalized messaging to the salesforce about their customer's script behaviors and engagement in other channels. I spearheaded the creation of a salesforce feedback loop that directly contributed to a 20% increase in adherence rates among 1,200 sales representatives. By incorporating user insights into our strategy, I not only ensured continued adoption of the capability, but also developed a best practice that was later adopted across other brands in the org.