Paid Search Campaign
DATA ANALYSIS · MARKETING STRATEGY
Academic Project · Individual · Graduate · Spring 2026
Project Overview
I analyzed paid search campaign data for a shopping mall to evaluate performance, identify opportunities for optimization, and determine why strong traffic was not translating into profitable growth. Using Tableau, I transformed campaign metrics into visual insights and developed a strategic pitch for a CMO audience recommending how budget, targeting, and campaign timing could be optimized to improve return on ad spend.
My Contributions
Analyzed paid search performance and identified key drivers: Evaluated impressions, clicks, CTR, CPC, conversions, revenue, cost, and ROAS across campaign periods and ad groups to identify performance gaps, seasonal patterns, and differences between traffic-driving and high-converting campaigns.
Translated complex campaign data into visual insights: Self-taught Tableau using AI-assisted learning and video tutorials, building an interactive dashboard and data visualizations that made campaign performance, profitability, ad-group efficiency, and trends easier to interpret and communicate.
Turned findings into an executive-level marketing recommendation: Developed and presented a CMO-focused pitch recommending strategic budget reallocation toward high-performing mobile coupon and desktop promo-code campaigns, seasonal spending adjustments, A/B testing, and ongoing ROAS monitoring.
Key Deliverables
Analyzed shopping mall paid-search campaign data to evaluate performance across key metrics and identify patterns, strengths, and areas for improvement.
Created Tableau visualizations to make campaign performance easier to interpret and uncover meaningful trends within the dataset.
Translated campaign findings into actionable recommendations and developed a presentation communicating key insights and opportunities to a CMO-level audience.
SKILLS DEMONSTRATED
Data Analysis
Data Visualization
Performance Analysis
Insight Synthesis
Strategic Recommendations