Fashion Analysis: Understanding Customer Churn in Fashion Industry

Introduction

The fashion industry is growing daily and business owners need to understand customer behaviour to make profits and drive operations.The article delves into the customer churn across the fashion industry.

🎯 Project Objective.

The primary objective of this analysis is to replace gut-based decisions with research-backed strategies to improve stock management and customer retention.The analysis aims to:

1. Understand consumer behavior - This includes customer preferences,purchase frequency and understanding customer demographics.

2. Analyzing inventory performance - identifying fast and slow moving items to optimize stock levels.

3. Analyzing sales trends over time - Determining peak sales days, product categories and seasonal variations.

4. Time -based analysis - examining how timing affects consumer engagements and purchases using the rolling 3-Month Sum.

Dataset Overview.

The dataset used was inserted using SQL using the function;

create table fashion (
    clothing_type VARCHAR(8),
    category VARCHAR(11),
    price DECIMAL(5,2),
    discount DECIMAL(4,2),
    shop_outlet VARCHAR(50),
    delivery_date DATE,
    order_date DATE,
    revenue DECIMAL(7,2),
    customer_name VARCHAR(50),
    customer_email VARCHAR(50)

Key Fields in the dataset:
Clothing_type--Brand of the cloth
Category- category according to men,women or child price
Discount - Discount offered on clothes
shop outlet- Various shops that customers bought their clothes.
delivery date- Date when the bought clothes reached clients
order date - Dates when ordered were made
revenue - Amount generated from the clothes sold

customer name - Customers first and last name
customer email - Customers email address

Analysis and Findings:

🔵 To understand the consumers demographics we analyzed the top 10 customers by revenue and found that women and children clothes are the leading cloths type purchased a lot and leads in revenue generation.

Recommendation:

🟢 Shop oulets should consider discounting men's items to drive up sales , since there discount is directly related to sales.

Findings.

🔵 Analyzing shop outlets that had highest customer visits and made a purchase.

• Brightbean recorded the highest number of visits among all shop outlets.

• Brightbean also offered the highest discounts, which likely contributed to its higher foot traffic and engagement.

Interpretation.

• There’s a positive correlation between the level of discounts offered and the number of visits.
• Outlets providing more promotions and discounts attract significantly more customers.

Recommendations:

🟢 Replicate Brightbean’s Strategy: - Other outlets should adopt similar discount or promotional approaches (e.g., limited-time offers, loyalty discounts).

• Use data-driven promotion scheduling to align offers with customer visit patterns.

🟢 Improve Outlet Visibility: - Increase online presence and share shop updates on Instagram, WhatsApp, and TikTok to reach a broader audience.

Sales Trends by Day:

🔵 Friday recorded the highest sales, making it the peak shopping day.
🔵 Wednesday had the lowest sales, showing reduced customer engagement mid-week.

Interpretation.

• The spike in Friday sales reflects strong end-of-week consumer activity, possibly driven by payday spending or weekend preparation.

Recommendation.

🟢 Enhance Friday Promotions: - Launch “Friday Frenzy” or “Fresh Friday” sales to maintain and grow Friday momentum.
🟢 Boosting sales - use mid-week social media campaigns and personalized offers to attract attention.such as "Ladies Wednesday".
🟢 Marketing Implications: - Build pre-Friday hype through digital channels.

Time Based Analysis.

Findings.

🔵 Sales were highest on Fridays and Saturdays, showing that consumers prefer shopping toward the weekend.

Interpretation:

• The end-of-week sales peak aligns with consumer behavior trends, as most shoppers have more free time or disposable income closer to weekends.

Recommendations:

🟢 Enhance Weekend Engagement:

• Launch "Styling Saturdays" promotions to maximize weekend traffic.
• Offer free outfit styling services or photo-tag discounts (e.g., “Take a pic in-store, tag us, and get 10% off your next visit”).

🚀 Call to Action.

AS I have analyzed and explored the financial performance of this project, its crystal clear that data driven decision- making is crucial for optimizing sales, driving the growth of the business and retaining happy customers.

If you found this analysis insightful, consider sharing it with business stakeholders and your network . Also you can reach out or leave a comment if you want to apply the same techniques on your data.