Chirag Somaya

Proposed data-driven recommendations for optimizing $200M in paid media spend by improving audience targeting and channel mix strategy, projecting a 12% increase in ROAS and a 5% reduction in CAC using SQL and Python for data analysis. Built and maintained 3+ interactive Power BI dashboards to visualize marketing performance, driving a 16% increase in orders and enhancing cross-functional reporting capabilities using data visualization techniques. Leveraged SQL to extract, transform, and integrate large datasets from CRM, web analytics, and ad platforms, reducing data discrepancies by 8% and improving data accuracy across systems using ETL processes. Developed advanced predictive models to forecast customer lifetime value and churn, enhancing marketing campaign planning and improving forecast accuracy by 10% through statistical modeling in Python.

Strategized, executed, and optimized multi-channel paid media campaigns across Google Ads, Meta Ads, Amazon Ads, and LinkedIn Ads for five brands, achieving a 25% lift in conversion rates and improved CAC through data-driven optimizations. Designed and implemented A/B tests on creatives, landing pages, and audience segments, leading to a 15% increase in CTR and 10% drop in cost per conversion through data-driven optimizations using Google Analytics and data analysis. Built actionable performance dashboards in Power BI and GA4, uncovering insights that enabled a $50K/month reduction in ad spend without compromising campaign effectiveness through data visualization and analysis. Managed $20K/day in media budgets, optimizing bids, pacing, and keywords to boost impression share by 40% and maximizing ROAS across channels using bid management tools and data analysis.

Assisted in planning, executing, and optimizing paid media campaigns across Google Ads and Meta Ads, contributing to a 22% increase in CTR and a 15% decrease in CPA by ad copy testing and bid adjustments using data analysis. Analyzed campaign data to create performance reports and insights that guided weekly optimization decisions, directly influencing a 10% improvement in ROAS across 3 client accounts through data analysis and reporting.