Here Dr Phil Brierley of Tiberius teamed up with David Vogel of Data Mining Solutions. The objective was to maximise the profit of a mailout by determining who to mail and what product offering they should receive.
There were two components required to solve the task,
1. Build propensity models for each of the 2 products
2. Use the propensity scores to decide which product to allocate (given certain constraints) in order to maximise profit.
Even in the absence of optimisation techniques, component model rankings generally corresponded to overall challenge performance. Both our component models were ranked 1st.
The competition was very close, but our solution generated 1.3% more profit than the next best solution.
||Tiberius Data Mining & Data Mining Solutions
||DMW Worldwide LLC
|Honourable Mention:Travelers, Salford Systems, Merkle, Data Management Marketing