The Scenario
You are a CRM manager at a mid-size nonprofit. Your organization has been using Raisely for three years across a dozen campaigns. Somewhere along the way, duplicate donor records accumulated. The same person donated three times under slightly different names, or signed up with two email addresses, or gave through a peer-to-peer fundraiser and also directly.
The new executive director wants a clean donor database in the CRM before the end of the quarter. The first step is pulling all Raisely users into a spreadsheet, finding the duplicates, and tagging the high-value donors before the data enrichment firm gets involved.
The slow version:
- Export Raisely users via the CSV export (which only gives you basic fields)
- Realize the CSV does not include the custom fields your campaigns collect
- Manually re-pull the missing fields from the Raisely user profile page for each record
- Import the CSV into Google Sheets
- Use COUNTIF to find duplicate emails, mark them manually
- Write a formula to calculate total giving per email
- Apply a "Major Donor" label manually to anyone above the threshold
- Two days later. You have 2,000 rows touched. The exec director's follow-up email is in your inbox.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI pulls all Raisely user records including custom fields, flags duplicates, and segments donors in one prompt — without you touching a formula.
Open the SheetXAI sidebar and type:
Fetch all users from my Raisely organisation including email, name, phone, and custom fields, paste them into this sheet, then highlight rows where the email appears more than once. Add a 'Segment' column that labels anyone with total donations over $500 as 'Major Donor' and everyone else as 'Regular'.
SheetXAI pulls all users from the Raisely API, writes them into the sheet, highlights duplicates, and adds the Segment column based on giving history. You walk into the executive director's office with a segmented database instead of a raw CSV.
What You Get
A clean, segmented donor database:
- Full user records — email, name, phone, custom fields
- Duplicate email highlighting — any email appearing more than once is flagged so you can review
- Segment column — "Major Donor" or "Regular" based on total giving history
- Custom fields included — not just the basic export columns
All 2,000+ users in one pull. SheetXAI handles Raisely's pagination automatically.
Want to add a "Last Donation Date" column or a "Campaign Count" column (how many campaigns they gave to)? Add it to the prompt.
What If the Data Is Not Quite Ready
A three-year-old donor database has problems beyond duplicates. Mismatched name fields, missing phone numbers, and inconsistent custom field usage are all standard.
When names are stored inconsistently across records
Some users have "FirstName LastName" in the name field, some have "FIRSTNAME LASTNAME", and some have only a first name.
Import all Raisely users. Normalize the name field to Title Case. Flag any record where the name field appears to contain only a first name (no space) in a 'Name Status' column as 'Incomplete'. Sort incomplete records to the top.
When you need to identify lapsed donors for a re-engagement campaign
The re-engagement team wants everyone who gave in 2022 or 2023 but has not donated in 2024 or 2025.
Import all Raisely users with their donation history dates. Add a 'Last Donation Year' column. Flag anyone with a last donation year of 2022 or 2023 and no donation in 2024 or 2025 as 'Lapsed' in a 'Re-engagement Status' column. Write their name, email, and last donation amount to this sheet.
When custom fields are blank for a large portion of records
A custom field called "Referral Source" was added mid-campaign and most early donors have it blank.
Import all Raisely users. Add the 'Referral Source' custom field as a column. Flag rows where this field is blank as 'Missing Referral Data'. Count how many rows have the field populated versus blank and write the count in cells A1 and B1 above the data.
When you need to build the full enriched export for the data firm
The data enrichment firm needs email, name, phone, total giving, last donation date, segment label, and duplicate flag — all in one clean sheet they can ingest.
Import all Raisely users. Add columns for: total giving (sum of all donation amounts), last donation date, segment ('Major Donor' if over $500, 'Regular' otherwise), and duplicate flag ('Duplicate' if email appears more than once). Normalize all name fields to Title Case. Sort by total giving descending. This sheet is being sent to an external data firm — make sure there are no blank headers and every column has a label in row 1.
The pattern: pull, clean, enrich, and format in one prompt. The output is ready to hand off, not ready to start work on.
Try It
Get the 7-day free trial of SheetXAI and ask it to pull your full Raisely user database into a sheet with deduplication and segmentation. The Raisely integration is included in every plan. See also how to bulk-create supporters without duplicates or the Raisely in Google Sheets overview.