Data Mining - open to bidding

Task: Use dummy data to maximize revenue from direct marketing campaigns. Data: For the analysis, several tables are available:  Social-demographical data (age, gender, tenure in a bank)  Products owned + actual volumes (current account, saving account, mutual funds, overdraft, credit card, consumer loan)  Inflow/outflow on C/A, aggregated card turnover (monthly average over past 3 months)  For 60 % of clients actual sales + revenues from these are available (training set) Conditions:  The bank has capacity to contact only 15 pct. of the clients (cca 100 people) with a marketing offer and each client can be targeted only once. Proposed steps: 1. Create an analytical dataset (both training and targeting sets) 2. Develop 3 propensity models (consumer loan, credit card, mutual fund) using training data set 3. Optimize targeting clients with the direct marketing offer to maximize the revenue Expected result:  Which clients have higher propensity to buy consumer loan?  Which clients have higher propensity to buy credit card?  Which clients have higher propensity to buy mutual fund?  Which clients are to be targeted with which offer? General description.  What would be the expected revenue based on your strategy?