To learn which products are most likely purchased together is a very powerful knowledge helping online merchants or any other company increase their sales. A good example explaining what a Proactive Sales Module is can be an online music shop selling tracks or ringtones.

The idea is that we analyze list of purchase transactions (what customers buy as a single purchase is: track1, track23, track76, ..., track17) and search for associations within purchases digging out buying behaviour of different type of customers. Thus we have two results: 1. we can say f.e. that if somebody buys trac23, track67 and track 44 then he will also buy track 17, and furthermore one can predict that if somebody buys track23, track67, track44 then he would also like to listen to track86.

All of this comes from analyzing purchase transactions made by other customers. This can be done once a day f.e. or even live for a single customer while he makes his purchases on the site.

This leads to the following scenario: an online customer buys one track, the script checks what other tracks usually come with this one and your online shopping cart displays links to these tracks f.e. on the right panel attracking customer's attention. When the customer buys second track (not necesserely from the right panel) the procedure repeats and so forth till he stops buying or exceeds "the knowledge" hidden in the purchase transaction data.

This results to customers easier finding tracks of their interest and increasing purchases (they get links to tracks they are interested in, because the analysis is based on the purchases of the customers with the same taste).

This module is implemented as a PHP module returning analysis results in XML format that can easily be integrated into any online shop or a web store.