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Fiverr Pro
English
$
USD
I will clean and match your donor, alumni, or membership database using fuzzy matching
Python Scraping and Data Cleaning Expert Fast, Clean, Delivered
I turn messy, hard-to-reach data into clean, structured files
you can actually use — fast.
Since 2021, I've helped businesses extract data from websites,
clean duplicate-filled spreadsheets, and au...
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
Stop losing donors, alumni, and members because your database is full of duplicates and mismatched names. I use advanced fuzzy matching (RapidFuzz + pandas) to merge records that Excel and CRMs misshandling nicknames, maiden names, married names, typos, and inconsistent formatting.
This gig is built specifically for nonprofits, universities, associations, and membership organizations. I merge donor records across years/events, clean alumni directories, and deduplicate membership rosters so your campaigns, appeals, and mailings go to the right people.
What I fix:
- Bill vs William, Judy vs Judith, Bob vs Robert (nicknames)
- Maiden married names, hyphenated last names
- Typos, missing middle initials, transposed letters
- Duplicate records from different systems (Raisers Edge, Blackbaud, Excel, Google Sheets)
- Multi-year donor lists, reunion attendee files, lapsed member rolls
You send me your messy file(s). I return a perfectly matched, deduplicated master file with a duplicate audit report. You get clean data ready to import for your annual fund drive, capital campaign, alumni gala, or membership renewal.
No login required. Your data is confidential.
My Portfolio
FAQ
Can you match records if my database has maiden names and married names for the same person?
Yes. I build custom matching rules that link maiden and married names using fuzzy logic, so “Susan Jones” and “Susan Smith (née Jones)” merge correctly. I also handle hyphenated last names.
What if my donor list uses “Bob” and the same person’s CRM entry says “Robert”?
I use a nickname resolution library plus fuzzy scoring to identify that “Bob” and “Robert” with matching last names and email/address are the same person, then merge them into a master record.
We have two separate systems—Raiser’s Edge and an Excel event list. Can you combine and match them?
Absolutely. Upload all files. I’ll merge them into one master table, deduplicate across systems, and return a single clean file with a map of which records came from where.
Is our donor data kept confidential?
Your data is only used for the matching job and is permanently deleted after delivery. I’m happy to sign a standard NDA or data processing agreement before you order.
