Data Visualization Project: Customer Shopping Trends Dashboard

Customer Shopping Trends Dashboard

Dashboard Link:
Customer Shopping Trends Dashboard

Abstract

The Customer Shopping Trends Dashboard provides a user-friendly interface for analyzing customer behavior and purchasing patterns. It helps businesses align their strategies with customer preferences by offering insights into product categories, regions, age groups, subscription statuses, seasonal behaviors, promotional offers, and more. These insights can assist in optimizing inventory, improving customer experience, and fine-tuning marketing tactics. Additionally, the dashboard includes gender-based comparisons to further assist businesses in tailoring their strategies to meet gender-specific demands.

Introduction

The dataset for this project is the Customer Shopping Trends Dataset from Kaggle, containing various features such as demographics, purchase frequency, preferred shipping and payment methods, and more. It consists of 19 columns categorized into:

Numeric Variables: Age, Purchase Amount (USD), Review Rating, Previous Purchases
Categorical Variables: Gender, Category, Location, Size, Color, Season, Shipping Type, Payment Method, Purchase Frequency
Binary Variables: Subscription Status (Yes/No), Discount Applied (Yes/No), Promo Code Used (Yes/No)

The primary objective of the dashboard is to detect purchasing patterns and help businesses make data-driven decisions for growth.

Objectives:

Understand customer preferences by analyzing various factors.
Improve customer shopping experiences by gaining insights and adjusting marketing strategies.

Dashboard Design

The dashboard provides an overview of key metrics, such as total customers, subscribed customers, average rating, and sales. It includes filters for date, age group, gender, product category, location, season, and more. Below are the key sections and findings from the dashboard:

Product Category Analysis

How do customer preferences change across seasons?
Key Finding: Footwear is most popular in winter, while clothing is consistent across spring, winter, and fall.
What are the most popular product categories among male and female customers?
Key Finding: Clothing and accessories are popular among both genders.
How does the average purchase amount vary between male and female customers?
Key Finding: Accessories have the highest average purchase amounts; gender-based variations are insignificant.

Location-Based Analysis

How do customer purchasing habits differ across locations?
Key Finding: High sales in Montana, California, Idaho, and Illinois.
What are the most popular product categories in the top 5 locations?
Key Finding: Clothing and accessories are consistently popular across top locations.
Which regions have the highest subscription service engagement?
Key Finding: Montana, California, and Idaho have the highest subscription engagement.

Age-Group Analysis

How does the quantity of purchases vary by age group?
Key Finding: Adults make the highest number of purchases.
What is the purchase frequency among different age groups?
Key Finding: Adults purchase more frequently compared to young adults and seniors.

Seasonal Purchase Analysis

Which products are most popular during different seasons?
Key Finding: Coats and jackets dominate winter, while shoes and sandals are popular in fall.
What is the seasonal distribution of purchases across categories?
Key Finding: Accessories peak in spring; footwear sales rise in winter and fall.
Which season exhibits high discount usage?
Key Finding: Discounts are most used in winter.

Payment & Shipping Method Analysis

What payment options do customers prefer?
Key Finding: Credit cards are the most preferred, followed by PayPal.
Which shipping type is most frequently selected?
Key Finding: Free shipping is the most preferred, followed by store pickup.

Rating & Promotional Analysis

How do average ratings vary across product categories based on gender?
Key Finding: Men rate products slightly higher than women.
What is the impact of promo code usage on review ratings?
Key Finding: Promo codes do not significantly affect review ratings.

Subscription Analysis

Which age group is most engaged in subscriptions?
Key Finding: Adults have the highest subscription involvement.
Is there a difference in purchasing trends between subscribed and non-subscribed customers?
Key Finding: Subscribed customers, both male and female, show higher past purchases.
What is the distribution of promo code usage across subscription status?
Key Finding: 90% of subscribers use promo codes compared to 20% of non-subscribers.

Mohammad Sakibul Islam