Your membership file is probably the best list of future donors you have. These are people who already pay you every year, visit, bring their families, and open your emails. The hard part is finding the handful who could give a lot more, and doing it with the data Altru already holds before you spend money on outside screening.
This guide covers what Altru can tell you about members on its own, where it stops, and a workable process for turning a membership roster into a short, researched prospect list.
Be clear about what Altru does and doesn’t do here
Altru is built around admissions, memberships, and fundraising transactions. It keeps solid history on each constituent record: membership levels and terms, renewals, donations, event registrations, ticket purchases, and household relationships. That history is the raw material for prospect research.
What Altru is not, at least in most configurations we see, is a full prospect management or wealth screening tool. It doesn’t come with built-in capacity ratings, and it doesn’t have the deep moves-management pipeline you’d find in a dedicated major gifts system. If you’re not sure what your subscription includes, ask Blackbaud support or your account rep directly before you design a process around a feature you assume is there.
So the practical approach is: use Altru to find and rank the members worth researching, do the external research somewhere appropriate, then record the results back on the constituent record so the whole team can see them.
Step 1: Decide what “a good prospect” means for you
Before building anything, agree with your development lead on the signals that matter. For member-based organizations, these tend to be the useful ones:
- Tenure. Members who have renewed consistently for many years are loyal, and loyalty predicts giving better than almost anything else in your data.
- Level and upgrades. Anyone at your higher membership levels, and anyone who has moved up a level, has shown willingness to give more when asked.
- Giving on top of membership. A member who also makes donations, gives to an appeal, or buys gift memberships for others is already acting like a donor.
- Engagement. Event attendance, frequent visits, and volunteer activity all suggest a closer relationship.
- Recency. A strong history from a decade ago matters less than steady activity in the last couple of years.
Write these down with rough thresholds (for example, “five or more consecutive years” or “any donation over a set amount in the last 24 months”). Your thresholds will be different from anyone else’s, and that’s fine.
Step 2: Build the queries in Altru
Use Altru’s query tools to turn each signal into a list. It’s usually easier to build several simple queries than one complicated one, then combine the results.
- Active members at upper levels. A membership query filtered to current memberships at your top two or three levels.
- Long-tenured members. Filter on member-since date or number of renewals, depending on what fields your setup exposes. Check a few records by hand to confirm the field means what you think it means.
- Members who also donate. A constituent query that pulls current members and their donation revenue outside of membership payments over a set period.
- Upgraders. Members whose current level is higher than a prior level. Depending on how your data is structured, this may take some testing; a sandbox or a small sample is the safe place to try it.
Include the constituent’s lookup ID, name, household, address, email, current level, member-since date, and lifetime giving in your output fields. You’ll need those columns for scoring and for any outside screening.
If your organization uses smart fields for things like lifetime giving or last gift date, use them. They make queries faster and keep the numbers consistent across reports.
Step 3: Score and shortlist
Export the combined results to a spreadsheet and give each person a simple score: one point per signal they meet, maybe two for the signals your team weights most heavily. Sort by score and read the top of the list with someone who knows your members personally. They’ll spot the board member’s spouse, the retired trustee, and the person who already said no last year.
Aim for a list small enough to actually research. A few dozen names that get real attention beat several hundred that sit in a file.
Step 4: Do the outside research carefully
For the shortlist, you can use a wealth screening vendor or manual research from public sources such as property records, public company filings, foundation boards, and published donor lists from other nonprofits. A few rules worth following:
- Send screening vendors only the fields they need, and confirm their data handling terms first.
- Stick to public, relevant information. Note the source and date of anything you record.
- Remember members gave you their data to join, not to be profiled. Keep research proportionate and access limited to staff who need it.
Step 5: Put the findings back in Altru
Research that lives in someone’s spreadsheet disappears when they leave. Record the outcome on the constituent record using whatever your organization already uses for this kind of tracking, such as constituent attributes, codes, or notes. A simple, consistent set works best, for example a prospect status, an estimated capacity range, the assigned staff member, and the date reviewed.
Once those values are on the record, you can query on them. That means you can pull “members flagged as major gift prospects whose membership expires in the next 90 days” and make sure renewal time becomes a personal conversation instead of a form letter.
Make it a habit, not a project
Save the queries and rerun them on a regular schedule, quarterly or twice a year. New upgraders and new donors will appear each time. Review anyone already flagged to see whether their status still fits, and retire flags that are years old.
Done this way, prospect research on members stops being a one-time push before a campaign and becomes part of how your membership and development teams work together.
Quick answers
Can Altru screen members for wealth automatically?
Not that we’re aware of in a standard setup. Most organizations export a shortlist to an outside screening service and record the results back on the constituent record. Confirm with Blackbaud if you think your subscription includes something more.
Should we screen the entire membership file?
You can, but it costs more and produces a lot of results nobody follows up on. Filtering in Altru first and screening a focused list is usually the better use of budget.
Where should prospect notes live?
On the constituent record in Altru, in a consistent format, so the information is queryable and survives staff turnover.
