Best Of·8 min read·By Faz·Updated Aug 7, 2026

Finding Planned Giving Prospects Already in Your File (2026)

Planned giving has an identification problem shaped unlike any other part of fundraising. The gift is large, the timeline is long, and the strongest predictor is not wealth.

It is loyalty. The donor most likely to leave you a bequest is often someone who has given modestly and consistently for a decade, has never been on a major gifts list, and has never been asked. Meanwhile the wealthy donor your screening flagged has given twice and has no particular attachment.

This guide is about planned giving prospect identification inside your own file, finding the first group, who are already in your database, using tools that look inward at your own records rather than outward at wealth data. Both approaches matter, and we will be clear about which does what.

Top pick: Gratefully is our pick for surfacing planned giving signals inside your own file, reading tenure, loyalty and quiet engagement across CRM, email and notes. DonorSearch and iWave lead on external wealth and age screening, which answers a different and complementary question.

The two questions, and why you need both

Question one: who in the world has capacity? Answered by external screening. Wealth markers like real estate, stock holdings and business ownership, plus age, plus philanthropic history elsewhere. This is what DonorSearch, iWave and Altrata sell and they are good at it.

Question two: who among our own supporters is likely to consider a bequest? Answered by signals inside your file. Tenure, consistency, engagement depth, life stage and behaviour.

For planned giving specifically, question two is the more predictive of the two, which is the opposite of major gifts. A bequest is not constrained by disposable income, which is why the modest lifetime giver is a serious prospect and the standard capacity-first approach systematically overlooks them.

Our AI donor research tools guide covers question one in depth, the external screening layer. This guide covers question two.

The signals that actually predict a bequest

Tenure above everything. Consecutive years of giving is the strongest single indicator in most files. Someone who has given every year for twelve years has demonstrated an attachment that no capacity score captures. A loyalty score built on depth of connection rather than depth of wallet is the mechanism that finds these hidden gems.

Consistency over amount. Twelve gifts of $50 outperforms two gifts of $5,000 as a bequest predictor.

Age and life stage. Genuinely relevant here in a way it is not elsewhere, and one of the few places external data helps directly with question two.

Quiet, sustained engagement. Opens your email, reads it, rarely responds, never attends. This donor looks disengaged on any activity dashboard and is often deeply committed.

Behavioural intent signals. Website behaviour is unusually predictive here. A constituent who visits your planned giving page three times in a month is signalling interest in a legacy gift about as clearly as it is possible to do without telling you.

Handraisers. Someone who has openly signalled intent through a survey, a form or an informal conversation. These are the highest-value names in your file and they are frequently lost, because the conversation happened once, four years ago, with someone who has since left. That is a records problem before it is a prospecting problem, and we cover it in donor portfolio handover.

No children, or no obvious heirs. Real predictor, uncomfortable to source, usually only known through relationship rather than data.

Faz says: The pattern I keep seeing is organisations screening for wealth, building a planned giving list of forty affluent strangers, and never contacting the retired teacher who has given every single year since 1998. She is the bequest. She has been telling you for twenty-five years and nobody in the building has read it as a signal.

The tools

1. Gratefully, best for signals inside your own file

Gratefully monitors planned giving signals from long-tenured supporters as one of its named signal categories, surfacing them in a daily action list with the reasoning attached.

What makes it fit this job specifically is that it reads across your CRM, email, documents and notes rather than the CRM alone. The handraiser conversation that lives in an old email thread, the note about a donor’s circumstances buried in a contact report, the twelve-year giving pattern nobody has looked at: those are exactly the inputs that identify a legacy prospect, and exactly the ones a CRM report cannot reach.

It also cites its sources for every statement, which matters more here than in most fundraising work. A planned giving conversation is delicate and long, and going into it on the strength of an unexplained score is a bad idea.

Where it does not lead. It holds no external data whatsoever. It will not tell you about property, or wealth, or that someone sits on three other boards. If your planned giving programme needs capacity confirmation or you are prospecting beyond your own file, you need a screening product alongside it. It is also dependent on what your records contain, which for older donors is often thin. Our Gratefully review covers this properly.

2. DonorSearch, best external screening for planned giving

DonorSearch combines wealth markers with philanthropic history and age data, which is the combination planned giving actually needs from external data.

Age is the part people forget. For most fundraising, capacity is the question. For planned giving, capacity plus life stage is the question, and few databases handle the second well.

Where it does not lead. External data does not know that someone has given every year since 1998 and replies personally to every acknowledgement. Screening produces capacity-ranked lists, and capacity is not the leading predictor of a bequest. Gratefully vs DonorSearch covers why these two are complementary rather than competing.

3. Dataro, best predictive modelling on large files

Dataro builds machine learning propensity models across your file, including for major and planned giving specifically.

For a large file, tens of thousands of donors, a trained bequest propensity model is a legitimate and efficient approach. Organisations adopting propensity scoring for major gift identification report portfolio conversion improvements in the range of 15 to 30%, though that figure covers major gifts broadly rather than planned giving alone.

Where it does not lead. A score without a reason is hard to act on in a conversation this sensitive, and small files do not contain enough bequest events to train a good model. See Gratefully vs Dataro.

4. iWave, best deep capacity database

iWave is the depth option for wealth and capacity research, useful once you have a name and need to qualify it thoroughly.

Where it does not lead. Same structural point as DonorSearch. It is a research database, not a signal detector inside your own file. Our iWave vs DonorSearch comparison covers the choice between them.

Which to buy, by situation

Your situation	Start with
Small file, long-tenured donors, no programme yet	Signals in your own file
Established programme, needs qualification depth	External screening
Very large file, direct-response heritage	Predictive modelling
Records scattered across CRM, email and drives	Signals, once records are usable
Prospecting beyond your existing supporters	External screening, unavoidably

Most small and mid-sized organisations should start inward. You almost certainly have unworked legacy prospects already giving to you, and finding them costs less than screening for strangers.

Saru says: There is a reason legacy giving rewards patience over analysis. The signal you are looking for was sent slowly, over many years, in small consistent amounts. No tool can compress that. What a tool can do is notice the pattern that a busy team has been scrolling past for a decade, and put the name in front of a human who can pick up the phone.

After identification: what actually happens

Identification is the easy half. Three practical notes.

Ask, gently and early. A bequest that is never discussed is a bequest that depends entirely on the donor thinking of it unprompted. Raising it costs you very little and it is the step most commonly skipped, usually because it feels awkward rather than because anyone decided against it.

Do not treat it as a gift conversation. It is a values conversation about legacy and what someone wants to be remembered for. Approaching it as a solicitation with a large number attached is how it goes wrong.

Steward the intention for years. A confirmed bequest is a relationship that continues for a decade or more. It needs recording somewhere durable, because the person who took the commitment will almost certainly have left before it matures. That is the handover problem again, and it is more acute in planned giving than anywhere else in fundraising.

Frequently asked questions

Who is the most likely planned giving prospect?

Typically a long-tenured, consistent donor of modest amounts, rather than a high-capacity recent donor. Loyalty predicts bequests better than wealth does.

Do we need wealth screening for planned giving?

It helps with sizing and qualification, particularly age data, but it is not where identification should start for most organisations. Your own file is the better first pass.

What is a handraiser?

Someone who has openly signalled intent to leave a planned gift, through a survey, a website form or a conversation. They are the highest-value names in your file, and they are frequently lost when the person who heard it leaves.

Can website behaviour really predict planned giving interest?

It is one of the stronger behavioural signals available. Repeat visits to a planned giving page in a short window is close to a stated intention.

How is this different from your AI donor research tools guide?

That guide covers looking outward, wealth screening and prospect research to find capacity you do not know about. This one covers looking inward, finding loyalty signals among supporters you already have. Different question, different tools, and most programmes need both.

Our records on older donors are thin. Does that block this?

It limits it. Giving history alone still gets you tenure and consistency, which are the two strongest signals, so you are not starting from nothing. See donor data readiness for what to fix.

The bottom line

Your best legacy prospects are probably already giving to you and have been for years. They do not look impressive on a capacity screen, they do not attend events, and they are easy to scroll past.

Start inward. Find the long-tenured, consistent, quietly engaged donors and the handraisers whose intent was recorded once and forgotten. Use external screening to qualify and size, not to identify.

Then have the conversation, which is the part no software touches, and record it somewhere that will survive the next three people who hold the relationship.

Written by

Faz

Faz is the founder of AIToolsBakery. Every tool on this site is personally tested with real-world writing tasks before a single word gets published. Sponsored content is always clearly labelled.