The Scenario
Your team is switching CRMs. The new platform is ready to import. What's not ready is the source data — 2,800 Helpwise contacts that need to arrive in the new system with name, email, and phone, deduplicated, in a single clean sheet. The migration vendor gave you a deadline of Thursday. It is Tuesday morning.
You've never done a Helpwise contact export before. You find a CSV option, download it, and open it in Sheets. The headers don't match what the migration template expects. There are duplicate email addresses in the list — you can count at least four from scrolling — and you don't know how many more are buried in 2,800 rows.
The bad version:
- Work through the CSV header mismatch column by column, renaming each field to match the migration template's expected format.
- Try to write a COUNTIF formula to surface duplicate emails across 2,800 rows, realize you need to handle case sensitivity too, and lose 40 minutes getting it right.
- Send the file to the migration vendor, wait two hours, and get back a note that 60 rows failed because several phone numbers came through without country codes.
The migration has a Thursday deadline and you are doing data cleanup work that should have taken twenty minutes. The constraint isn't time — it's that this is nobody's actual job, and it showed up in yours.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that reads your Google Sheet and talks to Helpwise directly. You describe what you need — the contacts, the fields, the dedup logic — and it handles the API calls and the sheet writes.
Search Helpwise for all contacts and write their name, email, and phone number into my sheet — paginate through all results until complete. Then identify duplicate email addresses in column B across all rows and mark them 'Duplicate' in column D, keeping the first occurrence marked 'Keep'.
What You Get
- Columns A through C filled with contact name, email address, and phone number — paginated through all 2,800+ records, not capped at a first-page result.
- Column D populated: "Keep" on the first occurrence of each email, "Duplicate" on every subsequent one.
- A complete, annotated export you can hand to the migration vendor without touching a COUNTIF formula.
What If the Data Is Not Quite Ready
Phone numbers are missing country codes
For any phone number in column C that doesn't start with a '+' or a country code, prepend '+1' as the default. Flag the changed rows with 'FIXED' in column E so I can review them before sending to the migration vendor.
Contact names are inconsistently formatted
Standardize all values in column A so that each name is in Title Case. Where the name field is blank, write 'Unknown' instead of leaving it empty.
You need to filter contacts by tag before exporting
Pull only the Helpwise contacts tagged 'Enterprise' and write their name, email, and phone number into my sheet. Paginate through all results.
The full migration prep: pull, dedup, format, and validate in one shot
Pull all Helpwise contacts into columns A–C. Mark duplicates in column D. Standardize names to Title Case in column A. For phone numbers missing a country code in column C, prepend '+1' and note 'FIXED' in column E. Then write a row count at the top of column F so I know how many records are going to the migration vendor.
One prompt. Clean file. Done before lunch.
Try It
Open a Google Sheet you'll use as the migration staging file, get the 7-day free trial of SheetXAI, and ask it to export your full Helpwise contact list with deduplication handled inline. Or see how to audit and delete stale tags once the migration is done.