Predictive Marketing Accuracy

Project Overview:
Developed machine learning models to enhance the accuracy of marketing KPI forecasting for a large-scale education and training organization.

Challenge:
Marketing teams lacked confidence in forecasting tools, resulting in misallocated budgets and inconsistent performance tracking.

Approach:
Deployed time series forecasting and supervised ML algorithms in Python to predict campaign KPIs, automating accuracy measurement and model recalibration through an API pipeline.

Results / Impact:
Achieved 95% predictive accuracy in KPI assessments, enabling precise performance tracking and budget optimization.
(Visual: Green and red bars show near-perfect alignment between predicted and actual campaign KPIs.)

Callout KPI:
95% Accuracy in Marketing KPI Predictions