Sample CSV for Cleaning Phone Numbers Before Import
This sample file works like a small test kit for the Bulk Phone Normalizer tool. Download it, run it through the workflow, and compare which rows stay import-ready versus which rows are separated into a needs-review file.
Quick answer
Use this sample CSV as a simple before-and-after test: download it, run it through the tool, then compare the cleaned output and the separate needs-review output before importing real data.
What This Sample Test Kit Includes
- Already valid international numbers
- Local-format numbers with country context
- Rows with missing country context
- Extension text inside the phone cell
- Multiple phone numbers stored in one field
- Free-text notes mixed into the phone field
How to Test the Sample in the Tool
- Download the sample CSV
- Upload it in the Bulk Phone Normalizer tool
- Select Phone as the phone column
- Select Country as the optional country column
- Process the file and compare the cleaned CSV and needs-review CSV using the same workflow shown on How It Works
What This Sample Demonstrates
- Already international rows stay valid and remain import-ready.
- Rows with enough context are safely normalized into E.164.
- Risky rows are sent to review instead of being guessed automatically.
Sample Input Preview
The input file keeps familiar contact-export columns such as name, company, phone, country, and email. Only the phone column is processed. All non-phone columns stay intact through the workflow.
| First Name | Company | Phone | Country | Expected outcome |
|---|---|---|---|---|
| Ava | North Peak Labs | +1 415 555 0123 | US | Cleaned |
| Liam | Harbor Metrics | (415) 555-0198 | US | Cleaned |
| Sophia | Blue Oak Media | 555-0123 | (empty) | Needs review |
| Ethan | Atlas Freight | 555-0123 ext 4 | US | Needs review |
| Charlotte | Verity Systems | +1 415 555 0123, +1 415 555 9999 | US | Needs review |
Sample Cleaned CSV Preview
The cleaned CSV is the file meant for import. It keeps the original columns, replaces the selected phone value with E.164, and appends status fields so you can audit what was normalized before importing.
| First Name | Company | Phone | Country | phone_status | phone_reason |
|---|---|---|---|---|---|
| Ava | North Peak Labs | +14155550123 | US | valid | Already international |
| Liam | Harbor Metrics | +14155550198 | US | valid | Normalized to E.164 |
| Mia | Brightline Health | +442079460056 | United Kingdom | valid | Normalized to E.164 |
| Noah | Summit Ops | +442079460056 | United Kingdom | valid | Already international |
Sample Needs-Review CSV Preview
The needs-review CSV protects import quality by isolating rows that should not be auto-fixed. These rows keep the original columns and add reason fields so the issue is clear before you clean them manually or retry a later import. For a final pass before importing real data, use the Phone Import QA Checklist for CSV Files.
| First Name | Company | Phone | Country | phone_status | phone_reason |
|---|---|---|---|---|---|
| Sophia | Blue Oak Media | 555-0123 | (empty) | needs-review | Ambiguous local number |
| Ethan | Atlas Freight | 555-0123 ext 4 | US | needs-review | Extension detected |
| Charlotte | Verity Systems | +1 415 555 0123, +1 415 555 9999 | US | needs-review | Multiple numbers in one cell |
| Benjamin | Pine Harbor Legal | call after 5pm: 415-555-0130 | US | needs-review | Extra text / notes in the cell |
Why Some Rows Are Separated Instead of Auto-Fixed
This tool is designed to improve import quality, not to guess through risky data. Rows are separated into the needs-review file when auto-fixing them could create bad contact records, incorrect E.164 values, or failed imports.
- Rows without enough country context stay out of the cleaned CSV
- Rows with extensions are separated instead of being silently rewritten
- Rows containing more than one phone number are not auto-picked
- Rows with extra note text inside the phone field are preserved for manual review
Review rows are separated to protect import quality and preserve trust in the cleaned output. For more edge cases and reason labels, see the FAQ.
More resources
Browse the Resources hub, review how the workflow works, learn what E.164 format means, or check the FAQ.