analysthub-hub / customer-segmentation-and-marketing-campaigns-analysis Goto Github PK

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What motivated me to carryout an analysis on marketing campaigns and customer segmentation is that they are an essential component of how businesses promote their interests. It is therefore critical for companies to measure customer engagement with marketing campaigns, evaluate the effectiveness of previous efforts, and suggest data-driven strategies to boost engagement with upcoming campaigns. The data used in the project is taken from kaggle. I could not find a private company data, open for scraping and usage. Hence, my choice. 📰🗞️

• numpy for mathematical operations on arrays.
• datetime for date manipulation.
• pandas to perform data manipulation and analysis.
• seaborn for data visualization and exploratory data analysis.
• plotly to create beautiful interactive web-based visualizations.
• plotly express easy-to-use, high-level interface to Plotly.

  Languages

  Tools

• Which products are performing best?
• Which channels are underperforming?
• What does the average customer look like for the Company?
• Which marketing campaign is most successful?
• Which Regions perform best?
• Which costumer segment purchase more?
• What does the costumer segment which accepted the last marketing campaign look like?

Data Collection Getting data from Kaggle.

Data Cleaning and Preparation Removing irrelevant and restructuring the dataset for easy analysis.

Visualization and Reporting visually presenting data in form of charts and graphs.

Insights presenting observations from the analysis.

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To run the (.ipynb) project use Notebook or Google Colab, while Power BI for the (.PBIX) file.

For support, email [email protected].

• @njimonda

Contributions are always welcome!

Please adhere to this project's code of conduct.

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