Is There A Doctor In The House ? Case Studies in Data Mining at the Keck School of Medicine of USC Presented by Michael Seymour Senior Director, Development Operations Keck School of Medicine / University of Southern California CARA Seminar Day October 21, 2005 Biola University

The Theory Behind the Madness Data Mining – -- needs to be practical (not just doing it for fun or to be a statistician) -- needs to be creative (think outside the box and play around) look for: consistent patterns, trends, irregularities or anomalies -- the searches you perform need to ask and answers questions that help in the overall development process -- needs to produce results The aim of data mining is to extract implicit previously unknown and potentially useful or actionable patterns and model from data.

The Theory Behind the Madness, Continued Data Mining empowers users to direct their activities by delivering accurate and useful information not available in raw data. Decisions in these situations are based on sound database intelligence, not on instinct or emotions. MODELS Clustering: identify groups of items that share a particular characteristic which is not pre-defined. Association: identify relationships between events that occur at one time. Sequencing: similar to “Association” except that the relationship exists over a period of time.

Actual cases (real life examples) CASE # 1Alumni Annual Fund CASE # 2Cancer Direct Mail Program

KDnuggets : PollsKDnuggetsPolls Successful Data Mining Applications (July 2005) Poll Industries/fields where you successfully applied data mining in the past 3 years [149 replies, 421 votes total] Banking (51) 12% Biotech/Genomics (11) 3% Credit Scoring (35) 8% CRM (52) 12% Direct Marketing/ Fundraising (34) 8% e-Commerce (11) 3% Entertainment/ Music (4) 1% Fraud Detection (31) 7% Gambling (2) 0% Government applications (12) 3% Insurance (24) 6% Investment / Stocks (5) 1% Junk / Anti-spam (5) 1% Health care/ HR (15) 4% Manufacturing (19) 5% Medical/ Pharmaceutical (12) 3% Retail (25) 6%Science (17) 4% Security / Anti-terrorism (5) 1% Telecom (23) 5%Travel/Hospitality (8) 2% Web (9) 2% Other (11) 3%

Case #1 Alumni Annual Fund Background:The Class of 1957 is considered one of our more active classes. What we did: In FY 2004, the Class of 1957 donors with previous giving of $1,000+ were targeted for a solicitation ask of $2,500+. We used our P!N data to identify alumni within the class and mailed a targeted solicitation letter asking for a certain amount of money, based on the P!N data and their previous giving. The ask for specifically for the class of 1957 scholarship fund. Data / Results FY: # mailed to: # of gifts: total amount:$8,600$24,600$31,840$12,704 [Note: 2006 data is only 3 months into fiscal year]

Case # 1 Alumni Annual Fund, continued Analysis: FY $1,000 + gifts 6 $100 + gifts FY $10,000 gifts ! $19, increase from previous year FY 2005decrease of $7, FY $5,000 gift to date

Case # 2 Cancer Direct Mail Program Background: Annual direct mail program for Cancer Center involving acquisition and renewals Plan: The idea was to move $50 / $100 / $250 to $500 / $1,000 donors. In FY 2004, we used P!N data to look at Cancer Direct Mail donor pool to move these donors to Cancer Research Associates (CRA) membership. Data / Results FY: Total acquisition pieces mailed525, , ,288605,243 Total renewal pieces mailed259, , , ,512 # gifts:1,978 26,552 28,874 31,593 total amount:$83,017 $1,299,467 $1,313,182$1,353,450 (only 3 month into fiscal year)

Case #2 Cancer Direct Mail Program, Continued Analysis: FY 2003Total $ raised:$239,561 Total donors: 208 $25,000 2 $5,000 7$1, $10,000 0 $2,500 10$ FY 2004Total $ raised:$157,739 Total donors: 166 $25,000 1$5,000 7$1, $10,000 1$2,500 10$500 17

Case #2 Cancer Direct Mail Program, Continued Analysis, Continued FY 2005Total $ raised:$97,191 Total donors:147 $25,000 0$5,000 4$1, $10,000 0$2,500 18$ FY 2006Total $ raised:$10,889 Total donors:32 $25,000 0$5,000 0$1,000 4 $10,000 0$2,500 2$500 0 [Note: 2006 data is only 4 months into fiscal year]

Sources “Deep Pockets – Where the Alumni Money Is” by Peter B. Wylie “The Many Facets of Data Mining” by Peter B. Wylie “Data Mining for Fund Raisers” by Peter B. Wylie

QUESTIONS AND ANSWERS COMMENTS DISCUSSION

Contact Information Michael D. Seymour Senior Director, Development Operations Keck School of Medicine University of Southern California (323) 442 – 3890