Dear Mr. Brian,
After review of the sales and catalog data, we found important trends that may help identify characteristics of our most favorable target market. Given the volume of the data, we decided to focus on the amount spent as our primary dependent variable, and selective independent variables.
We first analyzed the qualitative data by performing chi-tests between each of the variables gender, own home, married, location, and previous customer. Out of these relationships, it appeared that there were definite correlations between such relationships as Gender & Own Home, Gender & Married Status, Own Home & Married status, and Previous Customer & Married Status. For instance, it is not completely random that our male customers, on average, are 23% more married and own 15% more homes than our female customers. Also, our married customers own 84% more homes than single customers, and on average our married customers make up 12.5% more of our previous customer base.
This data is important because it identified the relevant qualitative variables to match to quantitative variables. First of all, we decided that our important dependent variable is the amount spent from our customers in the last fiscal year as this is ultimately what our goal should be. Secondly, that men are our primary target audience. We first begin by establishing the fact that men, on average, spend $388 more on our products than women do.
We then ran linear regressions between the quantitative variables: age, salary, children, and catalogs sent. The average age Salary appears to have the strongest correlation with Amount spent out of all of the independent variables. From here we saw that men on average earn $16,005 (33% higher salary) more than our female customers. In addition, men have fewer children and received more catalogs, all factors that increase average spending.
The one area we may want to focus on is converting more men in our target into previous customers. This is the one category that had fewer men. 70% of our sales came from previous customers, yet less than half were male. We should look into customer retention strategies and increasing male participation since they produce more sales on average.