SATISH VAVILAPALLI

Lead Generation

• Implemented RFM segmentation and machine learning classification models to identify 3,000 high-value early adopters, driving$6M revenue growth within 3 months.
• Increased product conversion by 30% and market share by 5% through predictive modeling and targeted strategies.

Marketing Mix Modeling (MMM)

• Designed a Marketing Mix Model using Facebook's Robyn library to evaluate media spend effectiveness for key animal health products.
• Controlled for factors like seasonality, pricing, promotions, and geography; optimized $17M+ media spend, achieving a 1.3 short-term and 1.9 long-term lift ratio.
• Recommended budget reallocations (+12% potential uplift) by identifying high-performing channels (Social, OLV, Display) and mid-funnel tactics.

E-commerce Analytics Solution

• Designed and implemented an automated reporting solution to improve pricing visibility, driving a$150M margin impact across international markets $800M portfolio).
• Developed metrics and analytics frameworks for key e-commerce modules, including pricing, availability, placements, content, reviews, and ratings.
• Delivered actionable insights to optimize e-commerce performance for retailers, enabling faster decision-making and improving direct-to-consumer (DTC).

• Delivered sales baseline and uplift analysis using advanced regression techniques (Linear, Ridge, Bayesian) to evaluate promo and non-promo sales trends.
• Conducted e-commerce performance key driver analysis to identify growth KPIs across pricing, availability, placements, and media, driving actionable insights for business growth.
• Built AI-driven anomaly detection models (Isolation Forest, Random Forest) to flag data quality issues and prioritize market opportunities for global leaders.
• Designed a global resource allocation model to optimize marketing budgets across countries based on growth rates, ROI, and revenue potential.
• Developed time series forecasting models (ARIMA) to predict trends and improve decision-making for resource allocation.

Tools & Technologies:
Python, Databricks, SQL (Teradata), Alteryx, Datarobot, Power BI, MS Excel, Machine Learning (Linear Regression, Ridge Regression, Bayesian Regression, Decision Trees, Random Forest, Isolation Forest), Time Series Forecasting (ARIMA), Anomaly Detection

• Developed statistical propensity models to optimize account targeting for sales teams, improving efficiency and conversion rates.
• Designed data-driven solutions to prioritize high-value customers across thousands of product lines.

Tools & Technologies: R, SQL Server, Logistic Regression

• Built POS billing solutions and analytical reports for retailers, monitoring sales trends and identifying opportunities to drive sales and margin.

Tools & Technologies: SAS, SQL Server, MS Excel