Sales Data Behavior Insights

I have a complete dump of our sales data and need it translated into clear, actionable insight on customer preferences. The sole focus is understanding customer behavior, not broad market trends, so every cut of the data should point back to what drives people to choose one product, bundle, price point, or channel over another.

The raw files can be delivered in whichever structure you prefer—CSV, SQL, or a direct BI connection—and I am open to Python, R, Power BI, Tableau, or a combination that will surface patterns quickly. The end goal is to know, with evidence, which product attributes and buying contexts most influence a purchase so that future campaigns and merchandising decisions can be laser-focused.

Deliverables
• A cleaned, well-documented dataset ready for reuse
• Exploratory notebooks or scripts showing each transformation and statistical test
• Interactive visual dashboard highlighting key preference segments
• A short executive summary (2-3 pages) translating the findings into next-step recommendations

Acceptance criteria
• Every chart or metric must map back to sales data only
• Insights must be tied directly to customer preferences (not churn, not general trend spotting)
• Code/notebooks run end-to-end without manual edits on my machine

If you see additional value in touching on purchase patterns or churn later, flag it as a future phase, but keep the current scope tightly on revealing who prefers what—and why.