Political Fund Raising with Geodemographic Tools

November 17, 1999
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November 16, 1999 - David Opitz was Chairman of the Republican Party in Wisconsin during its remarkable resurgence.Here he explains why GIS gets a major share of the credit! - ed.

In the political and candidate fund raising world, major donors normally attract the most media and public attention. However, the bread and butter of many party and candidate committees is the small donor. A small donor is generally defined as anyone giving less than $100 per election cycle. Development of small donors' files is a tedious and time consuming process usually undertaken by career type candidates or political parties. The attractiveness of a small donor file is the stability of the annual revenue that can be derived from it. This small donor file will also provide potential recruits to the major donor program. Generally, parties and candidates that have such files are considered to be in a much stronger position at election time.

Most parties and candidate committees maintain small donor lists. To renew and expand this file, an annual rite of prospecting for new donors is paramount. However, many parties and candidates find it difficult to understand or to justify the prospecting costs involved in such an effort. Therefore, there is always pressure to minimize or trim costs of prospecting.

The general practice in prospecting for new donors is to buy other successful fund raising lists: political or nonprofit. There are literally thousands of such lists available. The source is not as important as their yield or average dollars per name. These lists would cost from $.05 to $.25 per name. Despite these high costs, the best yield that could usually be hoped for might be a 1 or 2% return on the first contact; often the net on the first contact was negative. Costs could normally only be recovered over a five-year life of the response name. These factors, combined with short-term thinking, often resulted in insufficient effort devoted to new donor prospecting.

In 1996, the Republican Party of Wisconsin, using a GIS from Caliper and a database built from both commercial and public sources, created a geodemographic model donor. Such a model is a combination of demographic characteristics indicating the subset of the target that will be most susceptible to appeals. The resulting model, shown below, was developed by profiling common characteristics of their then-current small donor file of 4,000 names

  • Household: Male only or male and female
  • Household Income : Over $ 25,000 ( 55% from $30,000 to $45,000 )
  • Occupation: Retired,business owner, both blue and white collar worker
  • Home value: Over $50,000
  • With credit card: Yes
  • Age: Over 35
The Commercial data used in this analysis was from TransUnion. The public data was from voter registration files, driver license files, and occupational registration and licensing information.

Mapping served two critical purposes. First, it provided a reference point for address merging (not an exact science). This was important because we had so many and varied sources of data. The addresses of these different lists were of mixed quality. In some cases we actually matched names with addresses visually. Secondly one of our map layers was political boundaries. This layer was used to find concentrations of high historic Republican voter turnout.

In Wisconsin, election results are reported by the various level of political districts. The only way we could analysis it was with maps.

Having developed the above profile, a very large file of friendly nondonor Republicans was acquired way below the cost of $.05 per name. (Just exactly how the price was kept so low is among my trade secrets!) Using our small donor model, this file was prospected by both mail and telemarketing contact methods. Several interesting and rewarding lessons were learned.

Compared with normal yields of 1 or 2% for prospecting, our response was 18%. Because of this high level yield, prospecting costs went way down per donor name. Actually, there was a small profit made. This new donor file was also segmented by best contact method, schedule of contact, and message. As in voting, people are motivated to donate by message. Different message universes were identified and each donor "tagged" with whatever message motivated them to donate.

In conclusion, over a 2-year period this small donor program grew from 4,000 donors to over 40,000. The annual revenue grew from $200,000 to $1,200,000. This made the small donor program the largest single source of revenue for the Party. These new donors over a 5 year donor life will yield approximately $3,700,000. As one of our former, colorful Republican Governor"s would say "not too shabby".

The real accolades should go to the geographic information system and the database tools. Without the power of spatial orientation this story of locating the small donor could not be told.

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