Chris Cannon Saint Louis Zoo October 26, 2001

1. The Association of Professional Researchers for Advancement - Missouri/Kansas ChapterData Mining Basics and Applications Chris Cannon Saint Louis Zoo October 26, 2001

2. What is Data Mining? • Data Mining is the process of seeking and utilizing educated guesses about your constituents to identify and target groups or specific donors and prospects for strategic actions. • The end goal of data mining is to increase the number and quality of prospects and donors available for cultivation and solicitation. Cannon - Data Mining Basics and Applications

3. The Role: Why is it important? • The role of prospect research and management is to provide the organization with pertinent, timely and actionable information that assists with the fulfillment of the organization’s mission. Cannon - Data Mining Basics and Applications

4. The Role: Why is it important? • Information is a powerful tool that, when coupled with strategic plans of actions, can lead to strategies for bolstering support from existing donors and developing future supporters. • We don’t seek information for information’s sake Cannon - Data Mining Basics and Applications

5. The Role: Why is it important? • Data mining can assist with providing information and developing strategic plans of action for constituents • Today, we’ll discuss coupling the information we can gather with the ideas we have about our donors and prospects to develop strategic actions Cannon - Data Mining Basics and Applications

6. What is needed for Data Mining? 3 • Access to information about constituents or prospects • This can be in-house databases or external lists, etc. • Educated guesses about likely donor characteristics and possible prospect pools • Systematic means to seek information about these guesses • Testing to determine the validity of the characteristics as explanatory variables Cannon - Data Mining Basics and Applications

7. How to Research 101(applies to data mining equally well) • Be thorough and consistent. • Start at the beginning (inside-out;top-down applies here, too). • Develop a logical pattern and a specific set of standard sources. • Record all relevant findings and the fact that research occurred. • Set a time limit! Research should not impede on human contact. • When you here hooves, think horses but hope for zebras. Cannon - Data Mining Basics and Applications

8. Access to Information • What types of information are of use when data mining? • In-house resources are key • Must know giving and involvement history • External resources also important • Useful to fill in the gaps to follow through with a “hunch” and find new groups of prospects • Experience of others proves a useful guide Cannon - Data Mining Basics and Applications

9. Access to information - in-house • In-house resources refer to your organization’s database, paper files and institutional memory • The type of information that may be of interest varies by organization, but these are commonly useful, as can be the absence of information: • giving history, including funds, appeals, giving patterns, etc. • involvement history, including boards, events • home and other asset information, address info. and zip codes • relationship and contact information Cannon - Data Mining Basics and Applications

10. Access to information - external • External resources refer to digital and paper resources you obtain from outside sources • Some of the best external resources include: • giving to other institutions (Inez Berquist; annual reports) • board affiliations elsewhere (sorkinsonline; annual reports) • home and other asset information (appraisal sites) • business (ownership) information (Secretary of State site) • political support information (FEC at tray.com) Cannon - Data Mining Basics and Applications

11. Sources of Information • There are 4 1/2 primary “sources” of information, all of which can • provide information that overlaps. In fact, the overlap of sources is a key component to verifying information: • Organization-specific files (constituent/prospect in-house files, including information provided by volunteers and institutional memory….the best sources!) • Paper Sources (Older and unique sources tend to be paper files) • On-line Web Sources (Many free sites provide excellent data) • Pay-sources and the “invisible web” Cannon - Data Mining Basics and Applications

12. Sources of Information: Organization-specific files • Your organization’s institutional memory and files are critical to basic research. Ask those close to you who and what they know and how they can help. • Volunteer, staff and board information, in-house files and information tell you where to start (and when to stop). • This information provides key links among donors and prospects. • It also provides critical data for verification of your findings. Cannon - Data Mining Basics and Applications

13. Sources of Information: Paper Sources Whether in-house or at the school or public library, paper (or microfiche) files are sometimes our only hope (making our esteemed librarians our best friends). What sources are often the most useful? • Relevant newspapers • Dun & Bradstreet, etc. • Who’s Who • Good ol’ phone books • Martindale-Hubble • NFP Annual Reports • Yearbooks • Alumni Directories • SEC filings (S1, DEF 14A) • Foundation directories • (Local) magazines Cannon - Data Mining Basics and Applications

14. Sources of Information: On-line Web Sources There are many free sites that offer information on all manner of research subjects. Here, a few sites are noted based on the type of information they provide. Although overlap is inevitable, these sites are broken into 4 basic subjects: 1) General 2) Individual 3) Corporate 4) Foundation (Please note that web addresses change from time-to-time. The following were accurate as of CHANGE DATE/UPDATE SITES.) Cannon - Data Mining Basics and Applications

15. Sources of Information: On-line Web Sources - General • http://www.princeton.edu/one/research/netlinks.html (great resource for links to nearly every component of wealth identification and prospect data verification) • http://gwis2.circ.gwu.edu/~gprice/listof.htm (comprehensive listing of on-line resources, including many "hidden" sites standard search engines can’t scour) • http://www.internet-prospector.org/ (an Internet journal for how to scour the web for information) • http://www.presbyterianchurchusa.com/lamb/ (a useful site for links and ideas from David Lamb, a well-known prospect researcher) • http://www.richmond.edu/develop/research/ (another useful site for links and ideas from Univ. of Richmond ) • http://pubweb.acns.nwu.edu/~cap440/ (a good site from Northwestern.) • PRSPCT-L is the standard for prospect researchers listservs (PRSPCT-L-subscribe@yahoogroup.com to subscribe) Cannon - Data Mining Basics and Applications

16. Sources of Information: On-line Web Sources - Individual Individual Information: http://www.ama-assn.org/aps/amahg.html (the AMA's doctor web site) http://www.martindale.com/locator/ (the site for lawyer searches) http://www.amcity.com or http://www.bcentral.com (40 business journals) Public Information: http://www.tray.com/ (FEC's site for all campaign gifts for federal elections) http://www.ancestry.com(for the social security death index) http://www.langenberg.com (number of address/phone number directories) http://www.pac-info.com/ (appraisal sites and many other public record sites) Salary and Securities: http://finance.yahoo.com (one-stop source for corporations and their leaders) http://www.tenkwizard.com (the best, indexed site for SEC information) Cannon - Data Mining Basics and Applications

17. Sources of Information: On-line Web Sources - Individual Real Estate Appraisal Special: Real estate ownership is pubic record and a valuable wealth indicator. St. Louis City and County and St. Charles County have on-line databases: INSERT SITES Additional items, such as different mailing addresses, neighbors and trust information, can provide new directions. Cannon - Data Mining Basics and Applications

18. Sources of Information: On-line Web Sources - Corporate & Foundation Preparing for the $0.34 proposal can be quick and effective using the following types of web sites: Corporate Sites: http://finance.yahoo.com http://www.tenkwizard.com corporate-sponsored web sites Foundation Sites: http://www.fdncenter.org (the first source for foundation information, esp. larger foundations) http://www.guidestar.org (an indexed site for 600,000+ nonprofits) http://www.cof.org (Council on Foundations site) http://www.mcf.org/mcf/forum/articles.htm (good general info. and guidance) Cannon - Data Mining Basics and Applications

19. Sources of Information: On-line Web Sources - What’s Missing? When using free on-line resources, a broad, search engine query can narrow your efforts or indicate that your general search is too vague or broad to be effective. Keep in mind that search-engines do not catch everything nor do they review all pages (see next slide). A few of the more effective and popular search engines are: http://www.google.com http://www.altavista.com http://www. savvysearch.com Cannon - Data Mining Basics and Applications

20. Sources of Information: Pay Sources and the “Invisible Web” • Pay Sources are varied in cost, quality and depth of the information, means of access, etc. Some of these sites include: • http://www.dialogweb.com • http://www.knowx.com • http://www.lexis.com • Additional services from P!N, Grenzebach Glier, Marts and Lundy, etc. can pare down your org’s info. to target top prospects • Gary Price (http://gwis2.circ.gwu.edu/~gprice/listof.htm) provides the best source of links for non-indexed sites, such as census info. Cannon - Data Mining Basics and Applications

21. The Art of the Educated Guess • Prospect researchers are in the business of helping to develop educated guesses. • We can never know anyone’s “net worth” • Patterns in giving to your organization should show some signs to help identify and target future donors. • The best predictor is often previous behavior and our best future customers are typically our current ones Cannon - Data Mining Basics and Applications

22. The Art of the Educated Guess • The existence or lack of the two sources of information go into developing “variables” to consider: • In-house information • For example, no giving in a record • External information • For example, board affiliations present in Sorkins Cannon - Data Mining Basics and Applications

23. The Art of the Educated Guess • In-house Resources • Consider what you can usually find on all donors: giving and event attendance • What do these tell us? • Fund interests, frequency, size, initial, appeal • Type of event, frequency, audience Cannon - Data Mining Basics and Applications

24. The Art of the Educated Guess • External Resources • Consider what you can usually find on all prospects: name and address • What do these tell us? • Marital status, poss. age, life cycle stage • Zip code, street name, proximity Cannon - Data Mining Basics and Applications

25. The Art of the Educated Guess • The options are nearly limitless: • Birthdates, children, grandchildren • Home value, home ownership, multiple homes, commercial properties • Business contacts and affiliations, board contacts and affiliations • The absence or presence of suffixes, prefixes, zip+4 • Events, gifts, volunteerism • Because there are so many options, you need a system or two to narrow your data mining efforts Cannon - Data Mining Basics and Applications

26. Systematic Means for Data Mining • So far, this discussion mirrors the fundamentals of research • What differentiates data mining from research? It’s 100% pro-active • Systematic processes, queries, data screenings and other methods that identify and target (groups of) donors and prospects to be approached strategically based on the presence or absence of information Cannon - Data Mining Basics and Applications

27. Systematic Means for Data Mining • We won’t discuss here technical statistical issues • Chi-square, t-tests and (binomial) regression analyses can be used by trained professionals but you don’t need them to be effective • There are also companies (like those here) that can provide these services for your organization • Today, let’s discuss systems that you can apply when you arrive to work on Monday Cannon - Data Mining Basics and Applications

28. Systematic Means for Data Mining • Fundamental components of employing data mining (internally): • You must be able to run queries, extractions, lists, pulls or whatever your organization calls them • Preferably, you can entertain more than one variable at a time, for example, giving and address information • The development of the list criteria must make sense • The resulting list should be analyzed and acted upon Cannon - Data Mining Basics and Applications

29. Systematic Means for Data Mining • Three simple samples to get started: • In-house report review • In-house query analysis • External data mining • The Key is that each organization will have different hunches and different variables will explain more or less, so experimentation and testing will prove useful Cannon - Data Mining Basics and Applications

30. Systematic Means : In-house review • In-house report review, a simple example: • Run report every week/two weeks for all donors of $x or more (at the Zoo, it’s $250 and above) • Review report, looking for wealth indicators (mainly zip code, street address, business affiliations, business ownership) • Assign any likely candidates for a personal follow-up by development officer Cannon - Data Mining Basics and Applications

31. Systematic Means : In-house review • In-house query, another example: • Develop a query that identifies your best performing zip code (the Zoo’s is 63124, surprise!) and total giving to your organization • Sort the results listing the largest amounts first and remove any constituents with a clear moves manager • Assess and assign the remaining group (down to a certain level) for a personal contact or mailing Cannon - Data Mining Basics and Applications

32. Systematic Means : In-house review • External data mining: • Guess which street donates the most money • Go to that appropriate county’s web site and enter that street • Compare the list of names from the county with a query from your organization’s database • Add all those not in your database and send a solicitation, perhaps signed by an influential neighbor Cannon - Data Mining Basics and Applications

33. Testing what you think • The only way data mining becomes valuable is to test and record your hunches • Mailings are the most likely option • Make sure your sample is large enough • Record and measure results • Devise tests that succeed even if response is poor • Develop in-house systems for responding to these estimated guesses Cannon - Data Mining Basics and Applications

34. Data Mining as a Strategic Action • This session should illustrate how effective and easy data mining can be • While more elaborate possibilities are available, testing your organization’s collective wisdom in the ways described is a great first step toward harnessing the information you possess. Cannon - Data Mining Basics and Applications