Building Contact Lists with CSV Imports: A Clean Data Guide

Building Contact Lists with CSV Imports: A Clean Data Guide

CSV import is the bread-and-butter method for getting existing contact data into an SMS platform. Whether you're migrating from another platform, importing from a CRM, or loading a manually collected list, the process is the same — and the failure modes are consistent.

This guide covers how to prepare a CSV file that imports cleanly, validates correctly, and doesn't create compliance problems.

What a Valid Contact CSV Looks Like

A minimal SMS contact CSV needs at minimum:

• Phone number column: In a consistent format (ideally E.164 — see our guide on phone formatting)
• Optional: First name, last name, email, custom fields

A clean example CSV header row:

"phone,first_name,last_name,email,source,opted_in_at"

A clean data row:

"+15558675309,Sarah,Okafor,sarah@example.com,checkout,2025-01-15"

Common CSV Problems That Break Imports

Mixed phone number formats. Your CSV has some numbers as "(555) 867-5309", some as "555-867-5309", and some as "+15558675309". Most platforms will try to normalize these, but normalization logic varies. Standardize to E.164 before importing.

Numbers with extensions. "555-867-5309 x204" will break any parser. Strip extensions — they can't receive SMS anyway.

International numbers without country codes. "7911123456" for a UK number is ambiguous. It needs "+447911123456".

Empty rows. Blank rows in the middle of a CSV confuse many import tools. Remove them before uploading.

Special characters in names. Accented characters, apostrophes in names like "O'Brien", and quotation marks can break CSV parsing if not properly escaped. Most spreadsheet exports handle this, but check your data.

Duplicate phone numbers. The same number appearing multiple times will be deduplicated by good platforms, but it's better to clean it before import so you know your actual contact count.

Preparing Your CSV in Practice

In Google Sheets or Excel:

1. Create a clean column for phone numbers

2. Use a formula to normalize to E.164:

"=IF(LEN(REGEXREPLACE(A2,"[^0-9]",""))=10,"+1"®EXREPLACE(A2,"[^0-9]",""),IF(LEN(REGEXREPLACE(A2,"[^0-9]",""))=11,"+"®EXREPLACE(A2,"[^0-9]",""),A2))"

3. Copy → Paste Special → Values only (to freeze the formula results)

4. Remove any rows where the phone number column is blank or clearly invalid (fewer than 10 digits)

5. Export as CSV with UTF-8 encoding

The Critical Question: Do You Have Consent?

The most important check before importing any contact list is consent verification:

• Did every person on this list explicitly opt in to receive SMS marketing from you?
• Is your brand specifically named in the consent they gave?
• Do you have documentation of when and how they consented?

If the answer to any of these is "no" or "I'm not sure," do not import that list for SMS marketing purposes. Importing unverified contacts and texting them is a TCPA violation — even if the list came from your own CRM.

Contacts who signed up for email but not SMS don't automatically have SMS consent. Contacts who purchased from you don't automatically have SMS consent. Contacts from a purchased or traded list never have valid SMS consent.

Tagging and Segmenting on Import

When importing, use the opportunity to tag contacts with their source. Most SMS platforms support custom fields and tags on import:

• "source: csv_import_june_2025"
• "acquisition_channel: checkout"
• "opted_in_at: 2025-01-15"

These tags enable better segmentation immediately after import and make future compliance audits significantly easier. Being able to answer "where did this contact come from and when did they consent?" for any subscriber in your list is a core compliance capability.

After the Import

Run a small test send to 50–100 of your newly imported contacts before messaging your full imported segment. Check delivery rates (should be 95%+) and opt-out rates (should be under 1%). Abnormal failure rates signal a data quality issue you want to catch early.