Retail Customer Behavior Matrix

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(456)

n = 180
segments = np.random.choice(['Premium', 'Standard', 'Budget'], n)
data = {
    'Spend ($)': np.where(segments == 'Premium', np.random.normal(500, 100, n),
                         np.where(segments == 'Standard', np.random.normal(200, 50, n), np.random.normal(50, 20, n))),
    'Frequency': np.where(segments == 'Premium', np.random.normal(12, 3, n),
                         np.where(segments == 'Standard', np.random.normal(6, 2, n), np.random.normal(2, 1, n))),
    'Tenure (mo)': np.where(segments == 'Premium', np.random.normal(36, 12, n),
                           np.where(segments == 'Standard', np.random.normal(18, 8, n), np.random.normal(6, 3, n))),
    'NPS': np.where(segments == 'Premium', np.random.normal(65, 15, n),
                   np.where(segments == 'Standard', np.random.normal(40, 20, n), np.random.normal(20, 25, n))),
    'Segment': segments
}
df = pd.DataFrame(data)

sns.set_style("whitegrid", {'axes.facecolor': '#ffffff', 'figure.facecolor': '#ffffff', 'grid.color': '#eeeeee'})

palette = {'Premium': '#5314E6', 'Standard': '#27D3F5', 'Budget': '#F5B027'}

g = sns.pairplot(
    df,
    hue='Segment',
    palette=palette,
    height=2,
    kind='scatter',
    diag_kind='kde',
    markers=['D', 'o', 's'],
    plot_kws={'alpha': 0.7, 's': 55, 'edgecolor': 'white', 'linewidths': 0.6},
    diag_kws={'alpha': 0.5, 'linewidth': 2.5, 'fill': True}
)

g.fig.set_facecolor('#ffffff')
for ax in g.axes.flat:
    if ax:
        ax.set_facecolor('#ffffff')
        for spine in ax.spines.values():
            spine.set_color('#dddddd')
        ax.tick_params(colors='#666666')
        ax.xaxis.label.set_color('#333333')
        ax.yaxis.label.set_color('#333333')

g.fig.suptitle('Customer Behavior Segmentation', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)

plt.tight_layout()
plt.show()