Customer Behavior Analytics

End-to-End Data Intelligence Dashboard
3,900 Customers 18 Features $233K Revenue

Executive Overview

High-level KPIs and performance snapshot across all dimensions.

Total Revenue
$233K
Across 3,900 customers
Avg Order Value
$59.76
↑ Clothing leads at $60.03
Avg Review Rating
3.75
Out of 5.0
Subscriber Rate
27%
1,053 subscribers
Avg Past Purchases
25.4
Per customer
Top Season
Fall
$60,018 revenue
Revenue by Category
Clothing dominates at 44.7% share
Clothing Accessories Footwear Outerwear
Clothing: $104,264 | Accessories: $74,200 | Footwear: $36,093 | Outerwear: $18,524
Revenue by Season
Relatively balanced; Fall slightly ahead
Fall 60018, Spring 58679, Winter 58607, Summer 55777
Purchase Frequency Distribution
Spread evenly across all 7 tiers
Every 3 Months 584, Annually 572, Quarterly 563, Monthly 553, Bi-Weekly 547, Fortnightly 542, Weekly 539
Payment Method Mix
All 6 methods near-equally distributed
PayPal Credit Card Cash Debit Venmo Bank
PayPal 677, Credit Card 671, Cash 670, Debit Card 636, Venmo 634, Bank Transfer 612

Revenue Deep Dive

Product, location, discount and shipping breakdown.

Total Revenue
$233,081
Top Category
Clothing
$104,264 — 44.7%
Top Product
Blouse
$10,410 revenue
Top State
Montana
$5,784
Top 10 Products by Revenue
Blouse, Shirt, and Dress lead the pack
Category × Season Matrix
Revenue contribution across all seasons
Shipping Type Performance
Avg order value by shipping preference
Discount Impact on AOV
Discounted orders show slightly lower average
Top 10 States by Revenue
Geographic spread across 50 states

Customer Demographics

Age, gender, subscription, and loyalty analysis.

Total Customers
3,900
Male / Female
68% / 32%
2,652 Male | 1,248 Female
Average Age
44.1
Range: 18–70
Subscribers
1,053
27% of total
Avg Loyalty Score
25.4
Previous purchases
Customers by Age Group
56–70 age band has highest revenue spend
Gender Revenue Comparison
Male customers drive majority of revenue
Subscriber vs Non-Subscriber
Subscribers have higher loyalty scores
Review Rating Distribution
Majority of ratings fall in 3.1–4.5 band

Shopping Behavior Patterns

Promo codes, size preferences, colors, and purchase frequency.

Promo Code × Discount Matrix
Combined effect on avg order value
Size Preference
Distribution across S / M / L / XL
S M L XL
S, M, L, XL preferences
Revenue by Purchase Frequency
How often customers buy vs total spend
Top 10 Colors Purchased
Most preferred product colors
Category Mix by Gender
What each gender buys most

Customer Segmentation (RFM)

Recency-Frequency-Monetary proxy segmentation based on previous purchases and order value.

Champions
—
High spend + high frequency
Loyal
—
Consistent buyers
Potential Loyalists
—
Mid-frequency shoppers
At Risk / New
—
Low engagement
Segment Size Distribution
Customer count per segment
Avg Order Value by Segment
Champions spend significantly more
Sample High-Value Customers (Champions)
Ranked by previous purchases + order value
Customer IDAgeGenderLocation Prev PurchasesOrder ValuePaymentSegment