Analysis of 2000 customers reveals average age of 55.2 with median annual income of $52,140. Total spending averaged $609.20 with significant variation across customers. Campaign response rate was 15.0%, with customers accepting an average of 0.45 offers. These segments offer distinct targeting opportunities based on demographics and spending patterns.

Across 27 demographic segments, average age ranges from 36.0 to 70.3 years. Average total spending ranges from $29 to $818. Higher education and coupled marital statuses show higher average spending patterns. Campaign acceptance varies from 0.00 to 2.00 offers per customer across demographic groups.

Customer ages range from 28 to 131 years. The mean age is 55.2 years (median 54.0), with standard deviation of 12.0 years. The distribution shows tight spread, with most customers concentrated in specific age cohorts relevant for lifecycle marketing targeting.

Among 1983 customers with income data (0.8% missing), mean annual income is $52,140 with median $51,518. The distribution shows relatively balanced income levels, suggesting similar customer segments for premium vs. value positioning.

Mean spending is $609.20 (median $397.00). The 75th percentile is $1047.25 and 95th percentile is $1779.15, indicating significant whale customers. The right-skewed distribution suggests segmentation opportunities between volume and value customers.

Average spending by education level ranges from $67.95 to $664.29. PhD customers spend the most at $664.29 on average. The substantial (>50%) difference in spending between highest and lowest education groups suggests targeted product positioning opportunities.

Average spending by marital status ranges from $256.67 to $722.96. Widow customers spend the most at $722.96 on average. Household composition differences by marital status drive substantial variation in total spending patterns.

Wine is the highest-spending category at $306.06 average per customer. Top 3 categories account for the majority of spending, suggesting focus areas for inventory and marketing. The category distribution reflects customer preference patterns and premium product affinity.

The correlation between annual income and total spending is 0.795, indicating a strong relationship. Customers with higher incomes tend to spend substantially more, with marital status showing distinct patterns. This suggests income and household composition both drive spending behavior.

Strong correlations (max 0.581) between certain product categories indicate bundled purchasing patterns. Customers who spend on premium categories like Wine and Meat tend to spend on complementary categories, suggesting cross-sell and bundle opportunities.

The top 10 customers spend $2415.10 on average, 4.0 times the overall average of $609.20. These customers tend to have specific education and demographic profiles. Targeted retention and upsell strategies for this group can significantly impact revenue.