Consumer-Insights-Project

Click here for tableau dashboard

Project Overview

Objective: Analyze shopping behavior to uncover customer insights, purchasing trends, and promotional impacts using SQL and visualize the findings through a Tableau dashboard.

Goal: Develop SQL skills for business analytics by solving key questions related to customers, products, promotions, and satisfaction, supporting data-driven decision-making.

Data Analysis Queries (SQL)

A series of SQL queries were used to address the some analytics questions. Key highlights include:

• CTEs and subqueries to group, rank, and filter data.
• Aggregate functions like AVG, COUNT, ROUND, and conditional grouping with CASE statements.
• Analysis of seasonal trends, promo usage, and review ratings to identify actionable insights.

Tableau Dashboard

The findings from SQL queries were visualized using Tableau to create an interactive dashboard

Key Performace Indicators(KPIs):

• Avg. Purchase Amount
• Avg. Review Rating

Tools and Technologies

• SQL: Data extraction and analysis.
• Tableau: Visualization and dashboard creation.
• Data Source: "shopping_behavior_updated.csv (included in the repository).

Business Insights

1. Top-performing categories: Footwear emerged as the most profitable category with an average purchase amount of $60.26.
2. Promo Codes Impact: Promo codes influenced 30%+ of purchases, with a notable difference in purchase amounts.
3. Seasonal Trends: Spring observed the highest number of purchases, with specific items driving seasonal sales.
4. Customer Loyalty: Recurring customers with active subscriptions contribute significantly to sales.

Author

Shams Sadhin
Mail: sadhinss@mail.uc.edu
LinkedIn: https://www.linkedin.com/in/shams-sadhin/
Tableau: https://public.tableau.com/app/profile/shams.sadhin/vizzes