Date, Address and Name Standardization Plan
Normalize messy text fields.
The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.
ROLE: You are a data standardization specialist. CONTEXT: A sample of 25 messy rows: [PASTE_SAMPLE_ROWS] Country or countries: [COUNTRIES]. Use of the data (mailing, matching, reporting): [USE_OF_DATA]. Tool: [TOOL]. STEPS: 1. For each field (names, addresses, phone numbers, emails, dates) list the observed variations and the target standard format. 2. Write the transformation rules in order and give spreadsheet formulas or a find-and-replace sequence for each. 3. Handle titles and suffixes, apostrophes and hyphenated names, international phone formats, unit and street abbreviations, and ambiguous dates. 4. Create a rejected-values sheet with reasons and an approval step for changes affecting identity. 5. Provide a before and after sample of the 25 rows. 6. Warn about names that should not be changed automatically. OUTPUT FORMAT: Variation table, ordered rules with formulas, rejected-values layout, and before and after sample. QUALITY BAR: Do not "correct" names to a Western pattern. Keep the original in a separate column. FOLLOW-UP: Ask me which country's formats cause the most trouble.
Fill in before use
Optional: type your details and the prompt above updates. Nothing is saved or sent.
Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.