How to Format CSV Files for Contact and Opportunity Imports in Sparkforge

By Sparkforge Support Team ·Last reviewed May 3, 2026

Format CSV files for Sparkforge with a single sheet, a header row that matches your fields, and at least one of First Name, Email, or Phone per row. Use E.164 phone numbers, accepted date formats, and the exact country and timezone names Sparkforge validates against.

A clean CSV is the difference between a smooth import and hours of post-upload cleanup. Format your file before you upload it, and Sparkforge can map fields automatically, deduplicate accurately, and update existing records without creating ghosts.

Why formatting matters

Cuts down import errors and upload failures
Lets Sparkforge auto-map standard and custom fields
Enables deduplication and accurate updates
Supports custom fields and segmentation
Saves cleanup time after the import

What a CSV file is

CSV (Comma-Separated Values) is a plain text format where each line is a record and each field is separated by a comma. CSV files use the .csv extension and open in Excel, Google Sheets, or any text editor.

Keep one sheet per file — multi-sheet workbooks cause import errors.

Sample structure

First Name	Last Name	Email	Phone
Jane	Doe	jane@example.com	+11234567890
John	Smith	john@example.com	+10987654321

Required fields

Every row needs at least one of these to create or update a contact:

First Name
Email Address
Phone Number

For updates, include a unique identifier — Contact ID, Email, or Phone — that matches your deduplication settings. For opportunities, include the Opportunity ID to update an existing record. Without it, a new opportunity is created.

Field formatting rules

Field type	Accepted formats
Date	MM/DD/YYYY, YYYY/MM/DD, MM-DD-YYYY, YYYY-MM-DD
Multi-select / checkbox	Comma, semicolon, or period separators (e.g. `VIP, Lead` or `Gold; Silver`). Slashes are invalid.
Single dropdown	One value only (e.g. `Blue`)
Contact owner	FirstName LastName (e.g. `Logan Paul`)
Tags	Comma, semicolon, or period separated
Phone number	E.164 recommended: `+11234567890`. US-only fallbacks: `123-456-7890`, `(123) 456-7890`
Numeric fields	1.23, 1234, .123
Monetary fields	1234, 1,234,234.33
Contact followers	FirstName LastName, FirstName2 LastName2
Additional emails	Comma-separated list
Additional phones	Comma-separated, E.164 preferred

File requirements

Format: .csv only
Sheets: one per file
Max size: 30 MB
Header row: required and must match standard or custom field labels

Required vs. optional fields by import action

Action	Required fields	Notes
New contact	Name or Email or Phone	At least one of the three
Update contact	Contact ID or matching Name/Email/Phone	Depends on duplicate detection settings
Header row	Required	Must match Sparkforge field names

Country names

If your CSV has a Country column, each value must match Sparkforge’s validated country list exactly — case- and spelling-sensitive. United States works; USA or U.S. errors out. Two-letter ISO codes (e.g. US, CA, GB) are also accepted. Use the official name from the country list when in doubt.

Timezones

Timezone values are also case-sensitive and must match exactly — for example America/New_York, America/Los_Angeles, Europe/London, Asia/Kolkata, Australia/Sydney. Use the IANA timezone format Sparkforge accepts; abbreviations like EST or PST won’t map.

Tips before you import

Create custom fields in Sparkforge first using the same labels and data types as your CSV columns.
Strip blank rows and unused columns before saving.
Pick one date format and stick with it across the file.
Validate phone numbers in E.164 (+ followed by country code and number).
Use Additional phone numbers and Additional email addresses columns for extras instead of jamming them into the primary fields.

Frequently Asked Questions

Can I import contacts with multiple phone numbers or emails?

Yes. Use Additional phone numbers and Additional email addresses columns and separate values with commas. The primary Phone and Email columns hold one value each.

What happens if my CSV has fields Sparkforge doesn’t recognize?

Unmapped fields are ignored unless you map them to a standard or custom field during the import wizard. Create the custom field first if you want the data to land.

Will Sparkforge detect duplicate contacts automatically?

Yes, based on your duplicate detection settings. Sparkforge can match on Contact ID, Email, or Phone and either merge or skip the duplicate row.

Can I update existing contacts with a CSV import?

Yes. Include a unique identifier in the file — Contact ID, Email, or Phone — that matches your duplicate detection setting, and the import updates instead of creating new records.

Do I need to delete blank rows and columns first?

Yes. Empty rows and stray columns can confuse the field mapping and cause unexpected behavior. Clean the file before upload.