You can find relationships in your data by using the FindRules procedure.
The FindRules procedure uses the Associations mining function
to find relationships in your data.
Your database might include a data table that contains customer
data. You might want to find out whether relationships exist between
the values in the columns of this table. For example, a relationship
might indicate that in a certain number of cases one column has a
specific value if other columns have a specific value combination.
For example, the FindRules procedure might find out that
70% of the male customers who have an online access to their account
also have a credit card. You can exploit this cross-selling information
in the next marketing campaign.
You can also apply the
FindRules procedure to retail transaction
data. A sales transaction consists of the items that a customer bought
during a visit to the retail store. The information is stored in
a table with at least the following columns:
- The identification of the sales transaction
- The purchased items
The items with the same associated transaction ID are bought
together. If you apply the
FindRules procedure to a transaction
table, you might find out the relationships between the purchased
items. They indicate, for example, that in 45% of the cases, customers
who buy cereals also buy fruit in the same transaction. With this
cross-selling information, you can decide where to place the products
in your store or which products you might discount in the next marketing
campaign.