Most people arriving at ClippingCash already have a customer list somewhere: Yardbook, Jobber, a spreadsheet, or a notebook someone typed up. You do not have to retype it.
1 Export a CSV from wherever your list lives
ClippingCash detects your columns and lets you map them, so no specific format is required. An export straight out of Yardbook or Jobber works as-is, and so does a spreadsheet you built yourself.
Requirements:
- CSV file (UTF-8), up to 5 MB and 5,000 rows
- A customer name column is required; phone or email recommended
- Duplicates (same name plus phone) are skipped automatically
Keeping your list in Excel? Save it as a CSV first: the importer reads CSV files.
If you get a UTF-8 error, the app tells you exactly how to fix it: open the file in Excel or Google Sheets, then Save As > CSV (UTF-8) and try again. That is nearly always a file exported from an older tool with special characters in a customer name.
2 Upload the file
From Customers, click Import. You can drag and drop your CSV file onto the upload area or click Browse files.
The steps are shown across the top, and you can Cancel out at any point before the final click.
3 Map your columns
This is the step that does the work. ClippingCash tells you how many columns and how many customers it found in your file, then shows a three-column table: Your field, Column from your file, and Sample.
The guesses are pre-filled. Real exports usually map themselves, including cases where one of your fields comes from two of theirs: a first name column and a last name column get combined into the single customer name, and the table labels that row (combined) so you can see it happened.
The fields you can map are customer name (required), company name, phone, email, service address, city, state, ZIP / postal code, billing address, billing city, billing state, billing ZIP, notes, and email opt-out.
The Sample column shows a real value from your file for whatever column is selected. Use it. It is the fastest way to catch a mapping that looks right by name and is wrong in practice, like a “phone” column that actually holds a fax number.
Set anything you do not want to bring across to Don’t import. Billing fields are worth leaving unmapped unless the billing address genuinely differs from the service address.
If the name row is not mapped you cannot continue, and the page tells you so: A customer name column is required before you can import.
4 Import
The button is explicit about what is about to happen: Import N customers, with the real count from your file. Click it.
The page shows Importing your customers… with a running count of rows processed. It usually takes a few seconds.
When it finishes you see three numbers: Imported, Skipped as duplicates and Failed.
- If any rows failed, each one is listed with its row number and the reason. Fix those rows in your file and import the same file again. The rows that already landed are skipped as duplicates, so nothing doubles up.
- If some customers came in with no service address, the page says how many. They are imported, but they won’t appear on the map or in route optimization until you add an address.
Click View customers to see them.
After the import
Spot-check ten customers against your original file, particularly the phone numbers and addresses. Then check the GPS column on the Properties page: imported addresses get geocoded, and any that came in badly formatted will show as No GPS and want a pin correction before you try to route them.