Welcome to my marketing campaign performance analysis project! As a data scientist, I've conducted an in-depth analysis of marketing campaigns to assess their effectiveness and understand customer engagement. In this project, I've delved into various metrics to evaluate campaign responses and make data-driven recommendations.
- Analyzed marketing campaign data to assess performance.
- Created visualizations to represent campaign response rates and trends.
Before you begin, make sure you have the following installed:
- Python (if applicable)
- Power BI (if applicable)
- Clone this repository to your local machine.
- Open the project folder in [Power BI / Jupyter Notebook].
The dataset used in this project contains information about customer responses to marketing campaigns, including acceptance rates, responses, and other campaign-related attributes.
I performed a comprehensive analysis to understand how different marketing campaigns performed in terms of customer acceptance and response rates. I explored key metrics such as campaign acceptance rates, response rates, and their trends .
I created various visualizations to showcase campaign performance:
- Bar charts depicting campaign acceptance rates and various data.
- Calculated measures to determine total response rates.
These visualizations provide actionable insights into which campaigns were successful and which areas need improvement.
Contributions are welcome! If you have ideas for enhancements or want to report issues, please email @ yuvarajspt1998@gmail.com or submit a pull request.