Google Ads search campaign promoting a specialized history training course in Brazil. Focused on bottom-funnel conversions, optimizing for quality score, CTR, and increasing conversion rate while reducing CPA.
Analysis of a Google Ads search campaign, with performance insights visualized through Data Studio dashboards. Focus on optimizing quality score, CTR, increasing conversion rate, and reducing CPA
A visual comparison of the performance of beauty products based on key metrics from Google Ads campaigns, created using Excel. This analysis includes data cleaning and calculations to derive key metrics.
A visual comparison of the performance of beauty products based on key metrics from Microsoft Ads campaigns, created using Excel. This analysis includes data cleaning and calculations to derive key metrics.
A visual comparison of the performance of various beauty products based on key metrics from Meta Ads campaigns, created using Excel. This analysis includes data cleaning and calculations to derive key metrics.
Performance of platforms: Google Ads, Microsoft Ads, and Meta Ads. A bar graph was created to compare key metrics, providing insights for effective advertising strategies.
Interactive Tableau dashboard comparison of product campaigns on Google Ads, emphasizing key metrics analysis to enhance optimization, with data meticulously cleaned and prepared using SQL.
Interactive Tableau dashboard comparison of product campaigns on Microsoft Ads, emphasizing key metrics analysis to enhance optimization, with data meticulously cleaned and prepared using SQL.
Interactive Tableau dashboard comparison of product campaigns on Meta Ads, emphasizing key metrics analysis to enhance optimization, with data meticulously cleaned and prepared using SQL.
Python-generated graphs to analyze campaign performance by visually presenting key metrics to uncover trends, identify relationships, and provide actionable insights for optimizing future campaigns.
Python-based machine learning classification model using logistic regression to predict whether ROAS will be 3 or higher or less than 3, based on inputs CPC, Product Price, Quality Score, Spend, CTR, and CVR.
Python-based regression model that utilizes Linear, Ridge, and Lasso techniques to predict conversions from user inputs such as Clicks, Impressions, and CPC data, enhancing data-driven decision-making.