Raw data from multiple sources (sign-up forms, CRM exports, spreadsheets passed around by email) is usually messy: inconsistent capitalization in company names, phone numbers in different formats, mismatched date formats. AI can spot and standardize these issues far faster than checking row by row.
Important rule: always verify AI's output on a small sample before applying it to the whole file — AI can standardize incorrectly if it misreads the context of a column.
Try it now
- 1Identify common issues in the file: duplicate rows, missing data, inconsistent formatting
- 2Paste a sample of 20-30 rows into AI and clearly describe the standard format you want
- 3Ask AI to flag unusual rows rather than auto-fixing everything at once
- 4Verify the sample results before applying to the full file
Example prompt
"Here are 25 rows of customer data with phone numbers in inconsistent formats: [paste data]. Standardize them and flag any rows with fewer than the expected digits."