Using SPSS To Work and a Descriptive Statistic Case - SPSS Help

Eagle Industry is a company that operates nationally manufacturing and selling industrial equipment. Its customer base is very large, and a fundamental part of Eagle Industry’s strategy is to analyze the customer data in order to draw meaningful conclusions about customer demographics, and many other account-related aspects.

Statistical Analysis

Part I: Descriptive Statistics

The first part of the analysis corresponds to a demographic analysis of the customer base. The table and following pie chart show the distribution of customers based on geographical location.

A relatively homogeneous distribution of geographical location is observed, with a slight majority based in the south.

Purchases last 12 months

Another relevant aspect for the analysis is the purchases the last 12 months. The volume of purchases is one the factors that need to be taken into account in order to classify an account to be “at risk”.

The following chart shows a histogram of frequencies

The mean total purchases in the last 12 months was $157, 133.8, with a standard deviation of $125,546.8

Number of Purchases last 12 months

This variable is somehow related to the purchases the last 12 months. Also, a small number of purchases last year may be an indication that the account is at risk. The following chart shows the respective histogram of frequencies

Adding information to the database

Using the provided database, information about Account Tenure and Average Order has been added. The new variables are defined as

\[Account\,Tenure=Current\,Year-Starting\,Year\] \[Average\,Order=\frac{Total\,Amount\,of\,purchase}{number\,of\,orders}\]

Account Size

The accounts can be classified based on the size of last year’s total purchases. The following tables provide information about the total amount of purchases made last year:

Based on the respective percentiles, one possible way to attach an Account Size to each account is assigning the clients in the 10% upper segment to the Large category, clients in the 25% - 89% range to the Medium segment, the rest to the Small segment. This means that the ranges for each segment are:

\[\text{Large:}\,\,\left( 265,500,\,\,\infty \right)\] \[\text{Medium:}\,\,\left( 66,625\,,\,\,265,500 \right)\] \[\text{Small:}\,\,\left( 0,\,\,66,625 \right)\]

Consequently, the database was updated using these criteria.

Risk Classification

A combination of the number of orders and the total amount purchased can be used to determine the risk associated to each customer. A client with a low number of orders the last year can be considered at risk, especially if the average size of the order was small.

The following table shows the percentiles for variable Number of Orders:

The lowest 25% is given by 3. The mean average order is $47,751. One way to assign an account to the “At Risk” category is that the number of purchases is less than 3, and the average order is less than $47,751. Also, account with one 1 purchase should be put at risk no matter what is the amount of that purchase.

Importance of the Accounts

One way to assign the account to either “Key”, “General” or “Marginal” account status is to combine information about tenure and size of the account. The following table shows information about the tenure of the accounts

One possibility to assign importance to the accounts is to assign the accounts to the Key group if the size of the account is large and the tenure is 13 years or more, to the General segment if the account of the account is large and the tenure is 12 years or less, and the accounts of size medium and small to the Marginal group.

Another way that it would be preferred consists on analyzing the data involving the total amount of sales, with cumulative information. The following table shows that:

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