You finish a wealth screening, or your development director comes back from a board meeting with a spreadsheet of 300 names and notes on who should be cultivated for the capital campaign. Now all of that needs to land on constituent records in Altru, and nobody wants to open 300 records one at a time.
Doing this in bulk is possible, but how you do it depends on where your prospect information actually lives in Altru. Get that wrong and you end up importing into the wrong field, or creating a second record for half your major donors. Here’s how to plan it so the update goes in once and stays clean.
First, decide what “prospect info” means in your database
Altru is not a full major-gifts platform, and different organizations store prospect details in different places. Before you touch an import, list the fields you plan to update and where each one lives today. The usual places:
- Constituent attributes. The most common home for things like capacity rating, affinity score, campaign prospect (yes/no), screening source, or assigned staff contact. Attributes are flexible and query-friendly, which is why many Altru shops use them for prospect data.
- Constituent codes or similar classification fields. Good for broad categories (“Major gift prospect,” “Planned giving prospect”), less good for anything with a value attached.
- Notes. Where narrative research and meeting summaries usually go. Notes are hard to report on, so don’t put anything here you’ll later want to filter by.
- Relationships and household records. Spouse links, board connections, or “knows” relationships that matter for cultivation.
If your team has been using several of these inconsistently, fix that decision now. A bulk update is the best chance you’ll get to standardize, and the worst time to invent a new field on the fly.
The main bulk route: the import process
For most prospect updates, Altru’s import tools are the answer. The general pattern is the same regardless of which data you’re loading:
- Match on the lookup ID, not the name. Add a column with each person’s Altru lookup ID to your spreadsheet before anything else. Matching on name and address is how duplicates get created. If your source file came from a screening vendor or a board member and has no IDs, pull them in with a constituent query export and match the two lists in a spreadsheet first. Expect to resolve some rows by hand.
- Pick the import type that fits the data. Updating attributes, codes, or core constituent fields each typically uses a different import format. Look at the import options available in your Altru instance and download or review the expected file layout for the one you need. If you’re unsure which import handles which field, ask Blackbaud support before guessing.
- Format values exactly as Altru expects them. Attribute values tied to a code table must match an existing entry character for character. “Major Gift” and “Major gift” are not the same. Add any new code table entries before you import.
- Run a test batch of five to ten records. Include at least one record that already has a value in the field you’re updating, so you can see whether the import adds a second entry or replaces the first. Attributes that allow multiple values behave differently from single-value ones, and you want to find that out on ten records, not three hundred.
- Review the exceptions. Every import produces rows that fail. Read the exception file, fix the source, and re-run only those rows.
- Run the full file, then check it with a query. Build a constituent query on the field you just loaded and compare the count to your spreadsheet. If 300 rows went in and the query returns 287, find the 13.
Before you run it: make it reversible
Imports don’t come with an undo button. Before the full run, export the current values for every record in your file, using the same query you’ll use to verify afterward. If something goes sideways, that export becomes your correction file. Note the date and the person who ran the import in a shared log, too. Six months from now, someone will wonder why 300 records all got the same attribute on the same afternoon.
When an import isn’t the right tool
Some prospect updates don’t fit neatly into a file:
- Narrative research. Long notes with formatting tend to import poorly. For a small number of top prospects, entering them by hand is often faster than cleaning the file.
- Changing one value on everyone in a group. If you need to flag every constituent who matches certain criteria, check whether your Altru setup includes a global change or bulk-update option for that field. Availability varies by field and by what your organization has enabled, so test in a sandbox or confirm with Blackbaud support. If it isn’t available, export the query results with lookup IDs, add the new value in a column, and import it back.
- Ongoing feeds. If you’ll be loading screening results every year, save your spreadsheet template, column mappings, and code table list. The second run should take an hour, not a week.
Clean up first, or you’ll update the wrong person
Prospect lists are almost always weighted toward long-time donors and members, which are exactly the people most likely to have duplicate records in Altru: one from an old gala, one from a membership purchase, one from a web donation with a different email. Run your duplicate review on the people in your file before importing. Otherwise the capacity rating lands on one record while gifts keep posting to the other, and your prospect reports will undercount your best donors.
Quick answers
Can I update prospect info from a query instead of a spreadsheet?
Indirectly. Use the query to produce the list with lookup IDs, export it, add your new values, and import the file. That round trip is the usual way to bulk-edit a defined group.
Will an import overwrite existing values?
It depends on the field and the import settings. Single-value fields usually update; fields that allow multiple entries may add a new one instead. Your test batch is where you confirm which behavior you get.
