The Scenario
You've just wrapped a three-day conference. You collected 300 business cards, badge scans, and sign-up form submissions, and someone has already consolidated everything into a Google Sheet — first name in column A, last name in B, email in C, company in D. Your follow-up sequence launches Monday. It's Thursday afternoon.
The contacts need to be in Folk before any of that can start.
The bad version:
- Open Folk, click "New Contact," and start manually entering each row — name, email, company, repeat. By row 30 you're copying the wrong email into the wrong record.
- Export the sheet as a CSV and try to import it through Folk's native import — only to find that the column headers don't map cleanly and three required fields get dropped.
- Spend 45 minutes in Folk's help docs figuring out the right import format, reformat the sheet, re-export, try again, get partway through before hitting a rate error.
Your sequence goes out Monday whether the contacts are ready or not. Entering 300 records by hand across the next two days is not a plan — it's a punishment.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads your data, understands the structure, and through its built-in Folk integration it can create contacts in Folk directly from your sheet. You describe what you want, it does the work.
Create a Folk contact for every row in my "Conference Leads" sheet using column A for first name, column B for last name, column C for email, and column D for company — skip any row where column C is blank
What You Get
- A Folk contact created for every populated row with a valid email address.
- Rows with blank emails skipped cleanly — you get a count of skipped records, not a silent failure.
- A summary in the sheet sidebar showing how many contacts were created and how many were bypassed.
- No reformatting of your headers, no CSV intermediary, no import wizard to navigate.
What If the Data Is Not Quite Ready
The email column has mixed formats
Some rows have firstname@company.com, others have First Last <firstname@company.com>, and a few have nothing at all.
Normalize the email column in my "Conference Leads" sheet — strip any display name wrappers so each cell contains only the raw email address, then create a Folk contact for every row where the result is a valid email format
The sheet has duplicates from multiple scanner exports
You received data from two badge scanners and they overlap. Folk will reject duplicate emails.
In my "Conference Leads" sheet, deduplicate rows by column C keeping the first occurrence of each email, then create a Folk contact for every remaining row using columns A through D
Company names are inconsistent
Some rows say "Acme Corp," others "Acme," others "ACME Corporation" — and you want them standardized before they land in Folk.
Standardize the company names in column D of my "Conference Leads" sheet — collapse obvious variants of the same company into one consistent name, then create Folk contacts for all rows using columns A through D
The full cleanup and import in one shot
In my "Conference Leads" sheet: deduplicate by column C keeping the first row per email, strip any display name wrappers from column C so each cell is a raw email address, standardize company name variants in column D, then create a Folk contact for every valid row — skip any row with a blank or malformed email and give me a count of created and skipped records
The pattern: cleanup and creation happen in the same prompt. You're not running three separate passes before you can start the actual import.
Try It
Get the 7-day free trial of SheetXAI and open your next conference lead sheet, then ask it to push all 300 contacts into Folk before your follow-up window closes. Then check out how to bulk update contact fields from a sheet or go back to the Folk integration overview to see what else you can automate.