Data Cleanup

Clean 10,000 rows of messy data in minutes.

Names in 15 formats. Addresses missing zip codes. Phone numbers with random dashes. Duplicates everywhere. Alteryx charges $5,195/year. You have a spreadsheet formula.

Try the live demo Calculate your ROI

Your data is a mess. Everyone knows it.

Every CRM export, form submission, and CSV import dumps inconsistent, incomplete, duplicate-riddled data into your sheet. Cleaning it by hand is soul-crushing.

40+ hours

To clean 10,000 rows manually

Find-and-replace, PROPER(), TRIM(), SUBSTITUTE()... stacked 8 functions deep. For every column. Then the next spreadsheet arrives and you start over.

$5,195/yr

Alteryx Designer license

Enterprise data prep tools cost thousands per year. They require training, separate software, and a data engineering degree to configure properly.

23%

Of CRM data goes bad every year

People move, change names, switch phone numbers. Without continuous cleaning, nearly a quarter of your contact data becomes useless annually.

3 formulas. 10,000 rows. Minutes.

Type a formula. Drag it down. AI understands context, not just patterns. It fixes what PROPER() and TRIM() never could.

1

Paste your messy data into Column A

CRM exports, form submissions, scraped data, CSV imports, any source, any format. Paste the raw data into column A.

Your data
A1: "john SMITH"   A2: "Dr. Jane M. Doe PhD"   A3: "bob"   A4: "SARAH CONNOR-WILLIAMS"
2

Type =AI_CLEAN(A1) in B1

AI reads each value, understands what it is, and standardizes it. Not just capitalization. It handles titles, suffixes, hyphenated names, abbreviations, and edge cases.

Formula
=AI_CLEAN(A1)
John Smith
3

Drag down to B10000

Select the cell corner and drag. SheetSense processes all rows with staggered API calls. Every name standardized with context-aware formatting.

Result
B1 through B10000: all standardized
10,000 names cleaned in minutes
4

Use =AI_FIX() for addresses, =AI_EXTRACT() for mixed data

Different columns, different problems, same approach. AI_FIX standardizes addresses with missing info. AI_EXTRACT pulls structured data from unstructured text blobs.

Formulas
=AI_FIX(C1)    =AI_EXTRACT(D1, "phone numbers")
123 Main St, Springfield, IL 62704
5

Full dataset, clean and ready

Every column standardized, every address complete, every phone number formatted. Copy-paste the results as values and your clean dataset is permanent.

Your output
10,000 rows: Names | Addresses | Phone Numbers | Emails
All standardized, all consistent, all done

Watch messy data become clean data.

Three tabs. Three types of mess. Click "Clean Data" and watch AI standardize everything. Just like it works in your Google Sheet.

Data Cleanup - SheetSense Demo
B1
fx
=AI_CLEAN(A1)
--
Rows Processed
--
Issues Fixed
--
Time Saved
--
Accuracy

Same spreadsheet. Completely different data quality.

On the left: the data dump you dread. On the right: clean, standardized, ready-to-use records.

Before: The data dump
1john SMITH | 123 main st springfield | (555) 123-4567
2Dr. Jane M. Doe PhD | 456 oak avenue, apt 2b | 555.987.6543
3bob | 789 elm | 5551234567
4SARAH CONNOR-WILLIAMS | 321 pine street, chicago IL | +1-555-000-1234
5mcdonald, ronald j. | po box 100 | N/A

+ 9,995 more rows of inconsistent formatting...

After: Clean, standardized records
1John Smith123 Main St, Springfield, IL 62704(555) 123-4567
2Dr. Jane M. Doe, PhD456 Oak Ave, Apt 2B, Chicago, IL 60601(555) 987-6543
3Bob789 Elm St(555) 123-4567
4Sarah Connor-Williams321 Pine St, Chicago, IL 60614+1 (555) 000-1234
5Ronald J. McDonaldPO Box 100--
Data Quality Improvement (10,000 rows)
Names fixed
87%
Addresses fixed
72%
Phones fixed
61%
Duplicates
14%

How much time are you wasting on data cleanup?

Enter how many rows you clean per month. See what you save in time and money versus doing it by hand or buying enterprise tools.

Rows cleaned per month 10,000
39.8 hrs
Hours saved per month
$1,981
Saved vs manual cleanup
$9.99
SheetSense monthly cost
0.2 days
Payback period

Annual cost comparison

Alteryx
$5,195/yr
Manual labor
$23,880/yr
SheetSense
$120/yr

Estimates based on publicly available pricing and industry averages as of March 2026. Actual savings may vary.

Replace $5,195/year tools for $9.99/month.

Every method compared side by side. Prices verified as of March 2026.

Method Annual Cost Time for 10,000 Rows Setup Time Handles Edge Cases
Manual (formulas) $23,880 40+ hours None No
Alteryx Designer $5,195/yr 1-2 hours 8+ hours (training) Yes (with config)
Python + pandas $150/hr 2-4 hours 8-20 hours Depends on dev
OpenRefine Free 3-5 hours 4+ hours Limited
SheetSense Best Value $120/yr 5-10 minutes 60 seconds Yes (AI-powered)

Manual labor estimated at 15 seconds/cell for cleanup at $50/hr. Alteryx pricing from alteryx.com. Python assumes freelance developer at $150/hr.

4 AI functions. One clean dataset.

=AI_CLEAN()
Standardizes names, titles, and text data. Handles capitalization, honorifics, suffixes, and hyphenated names.
"john SMITH" -> John Smith
=AI_FIX()
Repairs and completes addresses. Adds missing zip codes, expands abbreviations, standardizes formatting.
"123 main st" -> 123 Main St, Springfield, IL 62704
=AI_EXTRACT()
Pulls specific data from unstructured text. Extracts phone numbers, emails, dates, names, or any custom target.
"Call me at 555-1234" -> (555) 123-4000
=AI_PARSE()
Splits unstructured data into structured columns. Parses mixed-format entries into consistent fields.
"John, 555-1234, NYC" -> [name, phone, city]

Your spreadsheet is smarter than your data prep workflow.

Free forever. 50 AI calls/month. All 20 functions included. No credit card required.

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