Analyzing customer shopping patterns for a demo store including customer segmentation, product performance, and sales/marketing insights using PostgreSQL.
- Sourced data from Kaggle.
- Download and set up PostgreSQL environment.
- Create a table in SQL Shell (psql) under the existing database.
- Answer relevant questions concerning shopping trends and derive insights.
Customer Demographics and Behavior
- What is the age distribution of our customers?
- How do purchase patterns differ between genders?
- Which customers have subscriptions to the company and how does their purchasing behavior differ from non-subscribers?
Product Performance
- What are the top-selling products and categories?
- How does seasonality affect sales of specific categories or items?
- Which products have the highest and lowest review ratings?
Sales and Marketing Insights
- What is the impact of discounts and promo codes on purchase amounts and frequency?
- Which locations have the highest sales volume and revenue?
- How do shipping types affect customer purchase decisions?
- Data was synthetically generated and does not reflect real-world data. This is because there isn't much variance in data results (for example, male vs. female trends are almost identical, which isn't consistent with actual customer behavior). Despite this, the insights can be as impactful when applied to real-world data.