Data Cleaning, Profiling, Enrichment and Fuzzy Matching in Google Sheets
Flookup is a powerful Google Sheets add-on that uses fuzzy matching to clean, deduplicate, profile, enrich and standardise your records, all in minutes.
162K+ users on Google Workspace Marketplace · 12,000+ daily active users · Since 2018 · Google-verified for security
Free tier from install, no credit card. Match previews plus one 50 row menu run per day, up to 10 runs a month, with a 7-day AI trial included.
Who Uses Flookup?
Flookup is built for people who clean and match records in spreadsheets. The common thread is a list of names, organisations or records that do not quite match, and a deadline.
Researchers and Academics
Match author, institution and survey-response names across datasets without exporting to another tool.
Librarians and GLAM Teams
Clean catalogue records, authority files and collection metadata while keeping the work visible in the sheet.
Data Analysts and Operations
Deduplicate customer, supplier and product lists, then standardise the variants that exact matching misses.
The same workflow fits sales, finance, HR and admin teams that need to reconcile lists before a report, migration or upload. See how Flookup compares with OpenRefine for research and library work.
Join Over 12,000 Daily Active Users
"Flookup has been a game-changer. The fuzzy matching function saves me hours of manual work cleansing data across multiple files. So much faster and more accurate than anything else I have tried!"
"This tool fits perfectly into our Google Sheets workflows. The fuzzy matching is easy to use and the customer support team is incredibly helpful. Highly recommended!"
"Flookup is fantastic for fuzzy matching and address scraping. It has saved us weeks of work and improved our data quality significantly. A must-have add-on!"
"Fantastic customer service and a huge time-saver for data cleansing. The ability to handle thousands of rows efficiently has transformed how we manage our spreadsheet data."
See Flookup in Action
Featured Articles from the Blog
Read practical guides on data cleaning, fuzzy matching and automation in Google Sheets.
What Is Data Cleaning? A Guide for Google Sheets
Understand the fundamentals of data cleaning in Google Sheets. This guide covers key concepts, common data quality issues and practical strategies using Flookup Data Wrangler, plus a short checklist to get started.
Top 10 Fuzzy Matching Algorithms Explained
Go beyond exact matches. This guide demystifies fuzzy matching algorithms, explaining how they work, what similarity scores mean and how to apply them for smarter data cleaning. Includes recommended thresholds and examples to help you choose settings.
How to Remove Duplicates in Google Sheets
Go beyond basic duplicate removal. This guide shows you how to eliminate all types of duplicates in Google Sheets, including fuzzy and partial matches, using Flookup. Step-by-step examples make it easy to follow along on your own data.
Comparing tools? Start with Power Query vs Flookup Data Wrangler, Ablebits Power Tools vs Flookup Data Wrangler and Alteryx vs Flookup Data Wrangler.
Advanced Data Cleaning Operations
Choose the workflow that matches your dataset and clean records quickly with advanced fuzzy matching and standardisation. Flookup Data Wrangler runs inside Google Sheets.
Fuzzy Matching
Reconcile records across datasets despite typos, abbreviations and inconsistent formatting.
Deduplication
Remove near-duplicate rows that exact matching misses, including phonetic and typo variants.
Workflow Templates
One-click AP reconciliation, order-to-shipping and user list consolidation jobs.
Learn from Examples
Show dirty-clean example pairs and the system learns the transformation without any formulas.
Data Cleaning Automation
Schedule deduplication and standardisation from every 15 minutes to daily.
Sheets AI Assistant
Describe your data problem in plain language and receive formulas or direct execution.
Data Cleaning Spreadsheet Formulas
Type FLOOKUP, FUZZYSIM, DEDUPE and ULIST directly into cells.
Column Profiling
Scan a column for row counts, nulls, duplicates and format inconsistencies.
Enrich Data
Add ISO countries, US states, company suffixes and TLDs next to your input.
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Last updated: October 2026