Facebook vs AdWords Ad Campaign Analysis

Business Problem

A marketing agency wants to maximize the return on investment (ROI) for clients’ advertising campaigns.
We ran two ad campaigns (Facebook and AdWords) in 2019 and need to determine:

• Which platform generates more clicks
• Which drives higher conversions
• Which is more cost-effective

The findings will help optimize budget allocation and advertising strategies.

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Live Demo

Try the app now: https://facebook-vs-adwords-analysis.streamlit.app/

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Research Question

Which ad platform is more effective in terms of conversions, clicks, and overall cost-effectiveness?

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Dataset

• Period: Jan 1 – Dec 31, 2019 (365 days)
• Platforms: Facebook & AdWords
• Features:
  • Ad Views
  • Ad Clicks
  • Ad Conversions
  • Cost per Ad
  • Click-Through Rate (CTR)
  • Conversion Rate
  • Cost per Click (CPC)

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Tools & Libraries

pandas, matplotlib, seaborn, numpy, scipy.stats
sklearn (Linear Regression, metrics)
statsmodels (time-series decomposition, cointegration)

Analysis Performed

Exploratory Data Analysis (EDA)

• Histograms for clicks & conversions
• Conversion categories comparison
• Weekly & monthly conversion trends

Correlation Analysis

• Facebook Clicks vs Conversions → Strong correlation (0.87)
• AdWords Clicks vs Conversions → Moderate correlation (0.45)

Hypothesis Testing

• H0: µ_Facebook ≤ µ_AdWords
• H1: µ_Facebook > µ_AdWords
• Result: ✅ Reject H0 (Facebook conversions significantly higher, p ≈ 0)

Regression Analysis

• Linear Regression model for Facebook clicks → conversions
• Predictive power: R² ≈ 76%
• Example:
  • 50 clicks → ~13 conversions
  • 80 clicks → ~19 conversions

Cost & ROI Analysis

• Monthly Cost per Conversion (CPC) trends
• Facebook more cost-efficient in May & November
• Cointegration test shows long-term equilibrium between ad spend & conversions

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Key Insights

• Facebook outperformed AdWords in both conversions and cost-effectiveness.
• Average Conversions/day:
  • Facebook ≈ 11.74
  • AdWords ≈ 5.98
• Higher ROI: Stronger relationship between clicks and conversions on Facebook.
• Best Days: Mondays & Tuesdays show the highest conversions.
• Budget Strategy: Allocate more budget to Facebook ads, especially in May & November.

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Visualizations

This analysis produces the following plots:

• Conversion distributions (histograms)
• Frequency of daily conversions by category (bar chart)
• Clicks vs Conversions scatter plots
• Weekly & monthly conversion trends
• Monthly CPC trend line

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How to Run

# Clone repo
git clone https://github.com/yourusername/ad-campaign-analysis.git
cd ad-campaign-analysis

# Install dependencies
pip install -r requirements.txt

# Run Jupyter Notebook
jupyter notebook campaign_analysis.ipynb

Future Improvements

• Add ROI dashboard (Tableau / Power BI / Streamlit)

• Include A/B test simulation for campaign optimization

• Extend analysis with multi-channel attribution modeling