The Scenario
You manage the donor database at a nonprofit. The fundraising appeal goes to print in 18 days. The board wants a clean list — no duplicate solicitations. The 12,000-row donor database in Excel was migrated from three legacy systems, and the same person appears as "Robert Smith," "Bob Smith," and "R. Smith" in different worksheets.
A deduplication consultant quoted eight weeks and $40,000. You have 18 days.
The bad version:
- Sort alphabetically by last name and scan adjacent rows — groups "Smith, Robert" with "Smith, Robert A." but misses "Smith, Bob" entirely.
- Run SOUNDEX — generates so many false positives the review takes as long as a manual scan.
- Export to a data quality tool, configure match settings, run it, export results, spend two days mapping output back to donation history.
Every duplicate mailer costs $1.40 in postage. The campaign is large enough for the math to matter.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that reads your Excel workbook and calls Interzoid's full-name similarity key API for every donor row.
For each name in column A, generate an Interzoid full-name similarity key and write it to column B, then sort by column B so variant name groups are adjacent.
What You Get
- Column B: Interzoid name similarity key per donor.
- The workbook re-sorted so "Robert Smith," "Bob Smith," and "R. Smith" are adjacent.
- Donor clusters visible at a glance for manual review before you choose the canonical name per group.
What If the Data Is Not Quite Ready
Column A has first and last name combined — match on full name as-is
The name in column A is already a full name. Generate an Interzoid full-name similarity key for each row as-is and write it to column B, then sort by column B.
You want to score specific name pairs from a preliminary review
Compare every pair of names in columns A and B using Interzoid's name match score and write the similarity score to column C, flagging rows where the score exceeds 85 as likely the same person.
Some rows have blank names from an incomplete import
Skip rows where column A is blank or contains only whitespace. Generate an Interzoid name similarity key for all other rows and write to column B. Flag blank rows as 'MISSING NAME' in column B.
Full dedup workflow: keys, scores, canonical names, clean output
For each name in column A, generate an Interzoid name similarity key and write to column B. Add a COUNTIF in column C for cluster size. For clusters with more than one member, write the most complete name as canonical to column D. Flag singletons as 'UNIQUE.' Create a 'CanonicalDonors' worksheet with deduplicated rows using column D canonical names.
The appeal goes out with a clean list and a meaningful reduction in duplicate postage costs.
Try It
Get the 7-day free trial of SheetXAI and open your donor database workbook — ask SheetXAI to generate name similarity keys and group variants before you finalize the appeal list. Then see the spoke on cross-checking a prospect list against existing customers, or the full Interzoid integration overview.