Tweet: The goal of our project is to understand revenue impacts and optimize marketing tactics with data-driven insights (user-data and gathered historical data) to utilize GenAI recommendations. This allows users to make informed decisions and achieve target revenue and review sensitivity analysis for areas of improvement. #MarketingAnalytics #AI #MachineLearning
Summary:
There are two parts to this project. The first is a sensitivity analysis; this is the backbone of the modeling used in this software package. The second half is the recommendation engine – a GenAI implementation on top of the sensitivity analysis that can provide recommended changes to the data uncovered in the sensitivity analysis that can lead a company to a specific target revenue.
The motivation behind this project stems from the large influx of historical context, but with that comes user’s tendency to struggle to understand the ramifications of different marketing-mix scenarios, while others grapple with the challenge of optimizing their strategies to meet revenue targets.
This software is designed to serve CMOs, by offering a user-friendly platform to conduct sensitivity analysis on historical and projected data. It addresses the critical problems of understanding revenue impacts and optimizing marketing tactics. The sensitivity analysis, forming the backbone of the system, illuminates the consequences of various marketing strategies.