Customer Behavior Descriptive Analysis

I have a sizeable, anonymized customer-level dataset covering purchase history, demographics, and digital interactions over the past two years. Your task is to run a thorough descriptive analysis that helps me understand how different segments behave—frequency, recency, monetary value, preferred channels, product affinities, seasonality patterns, and any other notable usage trends you uncover.

I will supply the raw CSV files plus a short data dictionary. You may work in Python (Pandas, NumPy, Matplotlib, Seaborn) or R (dplyr, ggplot2)—whichever lets you move fastest—so long as the code is fully commented and reproducible.

Deliverables
• Jupyter notebook or R script with all cleaning and exploratory steps
• Clear visualizations (charts, tables) that highlight key customer behavior insights
• A concise slide deck or PDF summary translating the findings into plain-English takeaways I can share with marketing and product teams

Acceptance criteria
• All code runs end-to-end on my machine without modification
• Visuals are labeled and easy to interpret
• Insights tie directly back to the business goal of understanding customer behavior

If you have recent examples of similar customer-centric analyses, feel free to mention them so I can gauge fit. Looking forward to seeing how you bring the story behind the numbers to life.