Adam
Dandi
ADAMS PROJECT

Retail Dashboard Transaction Analysis

Completion

March 20, 2024

Overview

This project focuses on analyzing retail transaction data to uncover key trends, patterns, and performance indicators. By leveraging insights from various metrics such as revenue, profit, discounts, and customer behavior, the analysis aims to enhance strategic decision-making and drive business growth.
Data Details
The company faced challenges in understanding customer purchasing behavior, identifying top-performing products and categories, and optimizing payment methods and discount strategies to maximize profitability. The dataset includes comprehensive retail transaction information sourced from Looker dashboards. It spans a timeframe from January 2021 to November 2022, encompassing: Revenue data: $8.69 billion total revenue. Profit data: $2.03 billion total profit. Discounts: $33.83 million total discounts. Quantitative metrics: 13,559 total transactions and 4,000 customers. Categories: Product, customer, payment method, and category breakdowns
The Problem
Mobile and Tablet category contributed to 39.8% of revenue, making it the leading category. COD (Cash on Delivery) accounted for 67.6% of transactions, indicating a reliance on this payment method. Key product insight: "IDROID_BALRX7-Gold" generated the highest revenue ($1.037 billion). A majority of customers demonstrated a preference for non-discounted products, indicating potential for optimizing promotional strategies. Focus marketing efforts on the Mobiles and Tablets category to capitalize on its strong performance. Diversify payment methods by promoting digital wallets and online banking to reduce reliance on COD. Implement targeted promotions for top customers and products to boost retention and sales. Adjust discount strategies to maintain profitability while enhancing value for customers.
The Solution
The project employed data exploration and visualization techniques to: Identify revenue and profit trends over time. Segment performance by payment methods and product categories. Analyze customer purchasing patterns to determine high-value customers and products. Highlight areas for optimizing discounts and promotions.
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