Clean Data in Google Sheets with Sheets AI Assistant

What Is Data Cleaning in Google Sheets?

Data cleaning in spreadsheets used to mean switching between tools, copying data back and forth or manually editing cells. Flookup brings powerful data cleaning capabilities directly into your spreadsheet workflow through the Standard Data Cleaning menu. To understand what AI-driven cleaning tools actually do and when they help, read our guide to AI data cleaning.

Instead of manually reviewing each row, you apply functions from the Standard Data Cleaning menu to clean, standardise and match your data. Results update when your source data changes, making your cleaning workflow repeatable and auditable.

Step 1: Standardise Your Text

Flookup provides a suite of functions accessible through the Standard Data Cleaning menu. Here are the essentials:

Step 2: Find Fuzzy Matches Across Sheets

The Fuzzy Match function finds the best match for a value in a lookup table, even when there are spelling variations or typos. Access it from the Standard Data Cleaning menu and configure the source range, lookup range and similarity threshold.

Example: You have a list of company names in one column and a master list in another. To find the industry for "Acme Corp" (even if the master list has "Acme Corporation"), run the Fuzzy Match function with an 85 per cent similarity threshold. The function returns the industry along with a confidence score.

Text Standardisation

The Text Standardisation function cleans text by removing diacritics, punctuation, stop words or extracting domains from URLs. Access it from the Standard Data Cleaning menu.

Example: Clean a column of addresses by removing punctuation and diacritics. The function processes every cell in the selected range in one pass.

Step 3: Remove Duplicate Entries

The Deduplication function removes duplicate rows based on fuzzy similarity, not just exact matches. Configure the similarity threshold to control how strict the matching is.

Example: Remove duplicate customer names from a list, keeping the first occurrence of each. The function compares every row and consolidates matches above your chosen threshold.

Similarity Scoring

The Similarity Scoring function calculates how similar two text strings are, returning a score from 0 to 1. Use it to audit match quality after deduplication or fuzzy matching.

Example: Compare two product descriptions to verify they refer to the same item before merging records.

Unique List Extraction

The Unique List function extracts unique values from a list, treating similar entries as duplicates. Configure the similarity threshold to control grouping.

Example: Get a unique list of city names, treating "New York" and "NYC" as the same location.

Your AI-Powered Assistant

The Sheets AI Assistant is one sidebar. The Mode dropdown offers Recommendation Mode, which suggests the right Flookup function for your task, and Execution Mode, which offers an Execute task dropdown with Multi-step workflow, planning and running automated cleaning workflows directly on your sheet, and Direct AI clean, cleaning your selected range with Smart Data Cleaning in one pass. Instead of navigating the Standard Data Cleaning menu or figuring out which function to use, you simply describe what you want to achieve.

How It Works

1. Describe your goal: Tell the assistant what you want to accomplish in plain language. For example: "I need to match customer names from my sales data against a master customer list, even when there are spelling differences."
2. Get a function suggestion: The assistant analyses your request and suggests the appropriate Flookup function for your task.
3. Refine if needed: If the suggestion is not quite right, ask follow-up questions or provide more context.

When to Use the Assistant

• You are not sure which Flookup function to use for your task
• You need help choosing the right settings for your data
• You want to combine multiple functions for a complex workflow
• You are new to Flookup and want guidance on best practices

Open it via Extensions > Flookup Data Wrangler > Sheets AI Assistant in your Google Sheets menu. There is a single sidebar with no separate Smart window.

For automated multi-step execution, switch to Execution Mode and keep the Execute task on Multi-step workflow to chain cleaning operations from a single description. To clean a range directly with AI, set the Execute task to Direct AI clean, describe the problem in plain language, tick the operations and confirm. Learn more.

Smart Data Cleaning in One Pass

When you already know the range and want the AI to clean it directly, switch to Execution Mode and set the Execute task to Direct AI clean. Select the range, describe the problem in plain language such as "Standardise company names, remove Ltd and Inc, fix casing", tick operations like trim, casing, punctuation and merge variants, then review the credit estimate and confirm. Mentioning an operation by name ticks its checkbox automatically. Cleaning costs 10 credits per value and needs any active Data Nova plan.

Practical Examples

Example 1: Reconciling Vendor Lists

Scenario: You have a list of vendor names from invoices and a master vendor database with name and vendor ID. You need to match each invoice vendor to the correct ID.

Solution: Use the Fuzzy Match function from the Standard Data Cleaning menu. Select your invoice vendor names as the source and the master database as the lookup range. Set the similarity threshold to 85 per cent. The function returns the vendor ID with a confidence score for every matched row.

Example 2: Cleaning Contact Data

Scenario: You imported contact data from multiple sources and need to standardise phone numbers and remove duplicates.

Solution:

1. First, run the Text Standardisation function to remove punctuation and diacritics across the affected columns.
2. Then run the Deduplication function to remove near-duplicate rows above a 90 per cent similarity threshold.

Example 3: Finding Similar Products

Scenario: You have two product catalogues from different suppliers and need to identify which products are the same despite different naming conventions.

Solution: Use the Similarity Scoring function from the Standard Data Cleaning menu. Select the two product description columns. The function returns a similarity score for each row. Products with scores above 0.8 are likely the same item.

Workflow Tips

Start with the Demo

Before installing Flookup, try the Data Cleaning Spreadsheet Formulas in our live demo spreadsheet. No installation or account required.

Use the Right Threshold

The similarity threshold controls how strict the matching is. Lower values find more matches but may include false positives. Higher values are more precise but may miss valid matches. Start with a mid-range threshold and adjust based on your results.

Standardise Before Matching

For best results, clean your text data before performing fuzzy matching. Run the Text Standardisation function to remove punctuation, diacritics and extra spaces. This improves matching accuracy significantly.

Process in Batches

For very large datasets (10,000+ rows), process data in batches or use the Data Cleaning Automation feature for automated processing.

Getting Started

Installation

1. Install the Flookup Data Wrangler add-on from the Google Workspace Marketplace.
2. Open your Google Sheet and go to Extensions > Flookup Data Wrangler > Account Management > Profile activation.
3. Enter your Profile ID to activate your plan. Plans do not auto-renew.
4. Start using Flookup's Standard Data Cleaning.

Try Before You Buy

Explore the Data Cleaning Spreadsheet Formulas in our live demo spreadsheet. No installation needed.

Frequently Asked Questions