Separate a new import from a merge
Creating a new table from CSV and updating an existing table are different operations. This example matches customer IDs against an established directory. Airtable documents the CSV import extension for paid plans; do not assume basic import provides the same merge workflow. Confirm which route your account supports before planning bulk updates or purchasing capabilities.
Preserve the source file and a recovery point
Check snapshots or another appropriate recovery method before importing. Keep an unchanged copy of the CSV and identify the columns actually needed. Protect a customer identifier such as 0012 from becoming 12 when a spreadsheet application opens and saves it. Try a small file to check text encoding, Japanese characters and date interpretation before exposing the full directory to conversion errors.
Choose a stable merge field
Match the same customer ID in the CSV and Airtable. Company names and personal names can change or collide. Separate blank keys, duplicate keys in the file and existing duplicates in the destination before importing. Agree how case and formatting are normalized; the matching behavior is not a substitute for a clean identifier policy. Avoid a bulk merge while the intended target is ambiguous.
Verify the table and column mapping
In the extension, select the intended table and map each CSV column to its destination field. If merging existing records, select the merge field deliberately and inspect projected new, changed and unchanged counts. Check both the base and table: a similar column layout in the wrong table is still the wrong destination. Leave fields outside the import's ownership unmapped.
Decide whether blanks clear or preserve values
An empty reply address can mean missing information or an intentional deletion. Set blank-value handling to match the agreed meaning and verify it on a practice record. Options for skipping blank or invalid CSV values should be tested rather than assumed. Keep manually written notes and workflow states outside the update mapping unless the import is explicitly responsible for them.
Reconcile three practice rows before expanding
Use an existing ID with changed data, a new ID and an existing ID with a blank optional field. Compare projected counts with actual records, including leading zeros and text. Investigate blank-key and duplicate-key cases separately. Reimporting the same valid merge file should not unexpectedly add new customer records; if it does, inspect key matching before trying a larger batch.
Record the import scope for ongoing operation
Keep the import time, source filename, period and affected counts so recovery can identify the change. Check current file and row limits and do not treat silently omitted data as success. If recurring imports justify Make or another automation tool, carry forward the same identity, blank-value and recovery rules. This is a preparation and verification workflow, not a report of a live customer-data import.
Official sources
Pricing, availability and feature limits can change. Check the linked official pages before subscribing.
- CSV import extension — AirtableInformation checked: 2026-10-30
- Getting started with views — AirtableInformation checked: 2026-10-30
- Airtable pricingInformation checked: 2026-10-28
- Airtable plans overviewInformation checked: 2026-10-28
- Airtable billable collaboratorsInformation checked: 2026-10-28
