Customer Data Analysis Automation

I need a clear, repeatable workflow that turns raw customer data into insights I can act on quickly. The files arrive in mixed-quality Excel sheets; some columns are inconsistent, others have missing values, and the volume is growing every month. I want a Python solution—Pandas is my usual choice—that cleans the data, performs the key descriptive analyses I outline below, and pushes the results back to Excel (or CSV) so I can share them with my team.

Here is what I expect:

• A well-commented Python script or notebook that reads the incoming Excel files, handles common data-quality issues, and stores the cleaned data in a tidy structure.
• Core analytics on customer behaviour (e.g., purchase frequency, average order value, churn flags) with the ability for me to extend the metrics later.
• An output workbook or CSV set that includes both the cleaned dataset and a separate summary sheet of the calculated metrics.
• Brief setup instructions so I can run the workflow on new files with one command.

Please include a detailed project proposal—outline your approach, any libraries beyond Pandas you would recommend, the structure of your deliverables, and a timeline. If you have relevant examples of similar customer-data projects, feel free to reference them so I can see your style and reliability.

I’m happy to clarify edge cases once you have reviewed the sample data I will supply. Looking forward to reading your proposal and seeing how you can streamline this analysis for me.