Profitable Casino Corp. (PCC) is a Harrah's wannabe, intent on mimicking Harrah's analytical marketing techniques. For example, PCC issues virtually all gamers a PCC "Rewards" card that accumulates points based on wagers placed, with incentive perks paid out when certain attainable thresholds are reached.
Importantly, the card captures gamers' play - how much they bet (per play and per visit), how much they win, how long they play, how fast they play, etc. For each player, proprietary algorithms calculate a "theoretical profit" based on usual win-lose percentages and the individual gamers' behavior at the slots and tables. The theoretical profit is based on actual betting behavior but corrects for luck (both good and bad).
Like Harrah's, PCC likes to experiment on a small scale with alternative marketing programs, do post-mortems on the tests to determine whether or not they were profitable, and then run with the successful programs and either modify or kill the unsuccessful ones. In order to analyze the programs, PCC relies on decision support systems.
You are to develop for PCC a decision support system (DSS) to analyze the success of promotional mailings. A promotional mailing is determined to be successful based on customers' "2nd visit" behavior. That is, (a) whether the customers returned to PCC or not and (b) how profitable they were if they did return after considering the cost of the promotion (e.g. free gambling chips, etc.). Because PCC e-mails all promotions, you can assume that program operating and administration costs are negligible. You can also ignore any time-value of money.
Part I: Expected Value Analysis
The DSS should provide the user the ability to enter the following data to determine if the promotion being examined has been profitable or not:
(1) The percentage of first-time visitors to whom you will mail a promotion. For example, the promotion could be a fancy e-mail from the PCC's CEO telling them how smart and important the visitor is with a voucher good for $65 in "fast start" chips redeemable on his next visit (but expiring in 90 days).
Default value: mail to 50% of customers
(2) The expected percentage of visitors who will return for a 2nd -visit on their own, i.e., do not receive some type of promotion but come back anyway.
Default value: 20% return on their own
(3) The expected percentage of visitors who receive the promotion who return for a 2nd -visit and redeem their "fast-start" voucher.
Default value: 33% of those who received a voucher return and redeem it
(4) The expected percentage of visitors who receive the promotion who return for a 2nd -visit but do not redeem their "fast-start" voucher (i.e., it may have expired or they forgot it).
Default value: 12% of those who received a voucher return but do not redeem the voucher
(5) The cost of the voucher awarded in this promotion (this value will need to be subtracted off the theoretical profit of a visitor to determine the "actual" profit of the visitor)
Default value: $65 voucher
(6) The average theoretical profit of a visitor on his 2nd visit who returns on his own without some type of promotion to attract him.
Default value: $85 in theoretical profits
(7) The average theoretical profit of a visitor on his 2nd -visit who returns after receiving the promotion and redeeming his voucher.
Default value: $101 in theoretical profits
(8) The average theoretical profit of a visitor on his 2nd -visit who returns after receiving the promotion but does not redeem a voucher (i.e., it may have expired or he forgot it).
Default value: $78 in theoretical profits