Donor prospecting data is used to analyze and identify potential donors or donors that have more capacity to give to your organization. Prospecting data helps development teams and fundraisers segment prospects based on how likely they are to to give and how much they are able to give. Wealth screening & prospecting data helps answer key questions:

To receive donor wealth and prospecting data, you'll need to conduct a scan. You can scan a single supporter or scan a filtered list of supporters.

Not all scanned donors will return successful scan results. This can happen when no matching prospect is found or if one was found but the confidence of that match was not high enough. You can increase the likelihood of successful scans by ensuring donors have some key contact data.

Donor wealth and prospecting data can be viewed and utilized across the Funraise platform, including from a Supporter's profile, when filtering Supporter lists, and when creating custom reports or dashboards in Fundraising Intelligence.

There are 13 wealth and prospecting data points that can be displayed for a supporter, we'll cover these in detail below. The configurations for scores are managed by Funraise and can not be adjusted.

An example of prospect data on a supporter's profile.

The Prospect Score, also known as the Kindsight Score, tells you how likely a supporter is to give to your organization and how much they may be able to give.

On a scale of 1-4, with 4 being the highest, this score is a summary of several contributing factors including Propensity, Affinity, and Capacity. These contributing factors are described in more detail below.

Propensity Score is a prospect’s inclination to give their time or money to philanthropic causes generally.

The Affinity Score tells you whether or not the donor is likely to make a gift to an organizations like yours. For example, does this donor make gifts to nonprofits that focus on health, the arts, or education, etc.

Your organization's affinity category is selected by Funraise using your organization's NTEE code (derived from your organization ID number). You can adjust your affinity category in your platform settings.

The Capacity Score tells you a donor's estimated capacity to give to nonprofit causes over 5 years.

Two pieces of information are used to calculate the estimated capacity and range scores. The estimated 5 year capacity value is the highest of these two calculations:

The solutions from these formulas are also available as data points:

The Engagement Score (RFM) is a measure of the current relationship you have with your donor based off their donation data in Funraise.

RFM stands for Recency, Frequency, and Monetary. These three scores are weighted equally to make up the overall Engagement Score (RFM).

The scores that make up each of these three calculations (Recency, Frequency, and Monetary) are used to determine the overall Engagement Score, although they are not available as an individual data points returned from a scan.

The insights category compares two scores: Prospect Score and your Engagement Score (RFM). The insight category helps segment supporters based on what these scores reveal about the donors. There are four categories.

These categories are defined by which quadrant the donor falls into when comparing both the Engagement (RFM) Score and the Prospect Score.

For example, a donor with an Engagement Score (RFM) of 1 and a Prospect Score of 4 is a Hidden Gem because they have low giving engagement with your organization but have a high potential to give. This is the top left quadrant.

Planned Giving Scores are determined by a number of factors, and allow you to have a quantitative rating to estimate how likely someone is to be a planned giving prospect for your organization. Indicators for this score include:

Real estate estimates can provide another insight to a prospects total wealth. Two values are available to summarize real estate data.

This data shows the total count and total amount of all charitable donations identified for this donor. Keep in mind, this is data that is available in Kindsight based on known charitable donations to any organization, not just donations to your organization.

Fees are incurred for each successful scan. A successful scan means that wealth and prospecting data was returned. A scan that does not return wealth and prospect data will not incur a fee. Wealth scan fees are billed monthly.

Donor prospecting data is available for US and Canadian donors.

When a supporter is scanned and successfully returns prospecting data, that data will remain the same until the donor is rescanned. To regularly surface new insights, we recommend scanning key Supporters every 6 to 9 months, but at least once every 12 months.

We'll cover this in more detail above, but one important reason you may want to rescan donors prior to donor outreach is to receive an updated and accurate Engagement score(RFM) as this score takes into account any new donations in Funraise, since the last scan.

Yes. Any scan that results in wealth data being successfully returned will incur a fee.

No, you do not need a Kindsight account to access prospecting data. Funraise has partnered with Kindsight to make this data available for Funraise customers.

Funraise's donor prospecting data is not (yet!) an integration with your own Kindsight account. Funraise supporters are not synced with your Kindsight account. The configurations for scoring and weighting in Funraise are managed by Funraise and are not synced from your Kindsight account.

Prospecting data in Funraise is powered by our friends at Kindsight. Kindsight uses databases of publicly available data including demographic, wealth, and giving data. This data is then crunched and calculated by Kindsight, providing additional insights into individual's wealth, giving interest, and capacity.

Kindsight (iWave) provides prospecting data to thousands of organizations and is one of the most trusted platforms for donor insights. The data that comes from public records is very accurate. From that data some scores and capacity estimates are generated by making assumptions based on those facts. The system is also designed to only return data when the confidence score of a match is high — so if a scan returns data for a supporter, it means there is a very good chance it's reliable.