IMPLEMENTATION OF PREDICTIVE MODELLING OF PRESCRIPTION GROWTH THROUGH MARKETING MIX MODELLING

Abstract: The pharmaceutical assiduity is faced with a grueling question moment how can they effectively spend their marketing budget while adding the number of prescriptions? This exploration proposes a result to this problem by using data- driven prognostications to identify which marketing sweats are actually effective. We’ve designed a system that analyzes different marketing sweats similar as deals representatives visiting croakers, free samples, online advertising, medical conferences, and special juggernauts to identify their factual effectiveness on the number of conventions written. Our system uses statistical analysis and intelligent features that consider delayed goods( since marketing doesn’t work incontinently) and long- term goods( since moment’s advertising can impact hereafter’s opinions). The system analyzes the literal data of conventions and marketing spending, cleans the data, and generates prophetic models that can actually tell marketers what works. We’ve enforced our system and created visual interfaces that help interpret the results. The analysis demonstrates that online marketing is a crucial factor affecting and direct marketing to croakers are the most effective, and more intelligent budget allocation can increase returns by 15 – 20 chance points. This system provides a foundation for pharmaceutical marketers to make informed opinions grounded on real substantiation.

Keywords: Market Mix Modeling, Prescription Growth, Regression Analysis, Adstock, ROI Optimization, Feature Engineering, Pharmaceutical Marketing, Predictive Analytics.