Key Functions

DonorScape’s philanthropic screening and predictive modeling tools provide insight into prospective donors’ “capacity” (i.e., ability) and “propensity” (i.e., likelihood) to give, critical attributes to consider when analyzing a prospect pool.

Philanthropic Screening

DonorScape Philanthropic Screening searches twelve of the best known and most respected data resources to provide you with more than 500 data points related to each of your prospect’s wealth, affiliations, and capacity to give.

DonorScape assigns each data point one of four accuracy levels, reported as Match Accuracy. This setting allows you to check the confidence level for each result so that you can decide whether to research prospects in-depth or work more quickly using only the most accurate data.

It’s important to understand that DonorScape’s philanthropic screening process does not estimate net worth or assume that a specific portion of an asset is “giftable.” Instead, our methodology creates a likely giving profile. Prospects each receive an overall Gift Capacity Rating, which is an estimated dollar value range of how much they could potentially give over five years to their favorite institution.

Predictive Modeling

DonorScape Predictive Modeling takes prospect analysis to another level, combining client supplied prospect details with premium third-party demographic information. Using this information, GG+A evaluates your individual prospects based on their overall household giving capacity and rates their propensity to give to your institution. This modeling process then generates independent ratings for different giving categories including the likelihood of major, annual, and deferred gifts.

Prospects are each assigned a Major Gift Rating that represents the relative likelihood an individual will donate at their gift capacity rating level, an Annual Gift Rating that identifies a target ask amount for an annual gift, and a Planned Giving Rating that represents the likelihood they will make a deferred donation based on their giving patterns and demographics. GG+A also produces a series of consumer segmentation codes for marketing communications and targeted outreach (PRIZM).

Predictive modeling takes into consideration a broad range of variables that correlate to specific giving behaviors, such as:

  • Recency and frequency of giving to your organization.
  • Relationship and participation factors unique to your organization, including current and prior volunteer involvement, leadership status, event attendance, and other engagement measures.
  • Demographic elements that are proven predictors for giving.
  • Wealth indicators, including estimated household income and home market value.
  • For healthcare organizations, additional information may include department of service, treating physician, and outcome.

See also: Guide to Ratings