Starbucks Marketing A/B Testing Project

📌 Project Overview

This project analyzes a Starbucks dataset to evaluate the effectiveness of marketing promotions through A/B Testing. The goal was to determine if specific offers (A) led to a statistically significant increase in customer spending compared to a control group (B).

🎯 Business Challenge

Starbucks needs to optimize marketing spend by identifying which offers actually drive revenue and which are ignored. I analyzed customer response data to identify high-performing promotions and calculate the "Lift" generated by the experiment.

🛠️ Tech Stack

• A/B Testing Logic: Excel (Hypothesis Testing, P-Value calculation, Lift analysis)
• Data Analysis: Excel / Data Cleaning
• Visualization: Tableau / Excel Charts
• Reporting: Case Study Analysis (PPTX)

📊 Methodology

1. Hypothesis Setting: Defined the Null Hypothesis ($H_0$) and Alternative Hypothesis ($H_1$) for customer conversion.
2. Experiment Split: Analyzed the Test Group (exposed to offer) vs. Control Group (no offer).
3. Statistical Significance: Calculated P-values to ensure the results weren't just due to random chance.
4. Business Recommendation: Provided data-driven advice on whether to scale the promotion.

📁 Project Contents

• data: Contains the dataset used for the analysis.
• ab testing: Excel workbooks containing the A/B test calculations and statistical formulas.
• visuals: Visual representations of the test results and customer behavior.
• report: The final case study presentation for stakeholders.