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.

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