Customer Segment Behavioral Analysis

import matplotlib.pyplot as plt
import numpy as np

# Customer behavior dimensions
categories = ['Purchase Frequency', 'Avg Order Value', 'Brand Loyalty',
              'Price Sensitivity', 'Digital Engagement', 'Referral Rate',
              'Product Range', 'Response to Promos']
              
premium = [70, 95, 92, 25, 85, 75, 88, 45]
regular = [85, 60, 70, 65, 70, 55, 65, 78]
bargain = [90, 40, 45, 95, 80, 40, 50, 95]
occasional = [35, 75, 55, 55, 45, 65, 80, 60]

N = len(categories)
angles = np.linspace(0, 2 * np.pi, N, endpoint=False).tolist()
angles += angles[:1]

premium += premium[:1]
regular += regular[:1]
bargain += bargain[:1]
occasional += occasional[:1]

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

ax.plot(angles, premium, 'o-', linewidth=2.5, color='#5314E6', label='Premium Buyers', markersize=7)
ax.fill(angles, premium, alpha=0.1, color='#5314E6')

ax.plot(angles, regular, 's-', linewidth=2.5, color='#27D3F5', label='Regular Customers', markersize=7)
ax.fill(angles, regular, alpha=0.1, color='#27D3F5')

ax.plot(angles, bargain, '^-', linewidth=2.5, color='#F54927', label='Bargain Hunters', markersize=7)
ax.fill(angles, bargain, alpha=0.1, color='#F54927')

ax.plot(angles, occasional, 'D-', linewidth=2.5, color='#6CF527', label='Occasional Shoppers', markersize=7)
ax.fill(angles, occasional, alpha=0.1, color='#6CF527')

ax.set_xticks(angles[:-1])
ax.set_xticklabels(categories, fontsize=10, color='#374151', fontweight='500')
ax.set_ylim(0, 100)

ax.yaxis.grid(True, color='#e5e7eb', linestyle='-', linewidth=0.8)
ax.xaxis.grid(True, color='#d1d5db', linestyle='-', linewidth=0.5)
ax.spines['polar'].set_color('#d1d5db')

ax.set_title('Customer Segment Behavioral Profiles', fontsize=16, color='#1f2937',
             fontweight='bold', pad=25)

ax.legend(loc='upper right', bbox_to_anchor=(1.22, 1.1), fontsize=10,
          frameon=True, facecolor='white', edgecolor='#e5e7eb')

plt.tight_layout()
plt.show()