How to Use AI to Check CSV Files Before CRM Imports
CSV imports seem easy. They often break your routing, attribution, or reporting.
Do not ask AI to clean your file. Instead, use AI to build a review process.
A clean file is useless if it ruins your system data. You must protect specific fields.
Protect these fields:
- Record ID or external ID
- Email address
- Owner
- Lifecycle stage
- Lead source
- Company or account name
- Created date
- Any field used for reporting
If these fields fail, your import fails your business.
Use this prompt to build a QA process:
I am preparing a CSV for CRM import. Review the headers and sample rows below.
Return:
- Fields safe to normalize.
- Fields needing manual review.
- Missing required CRM fields.
- Duplicate risks.
- Values that do not match my approved list.
- A pre-import QA checklist.
- Rows requiring review before import.
Do not change IDs, emails, owners, lifecycle stages, or attribution fields without flagging them.
Paste your headers, sample rows, and approved CRM values after the prompt.
A good AI response gives you a review table. It should show you what to check and why.
Example checklist:
- Owner: Check for missing or misspelled names to prevent bad routing.
- Lifecycle stage: Check for values outside your approved list to protect reports.
- Lead source: Check for duplicate labels like PPC and Google Ads.
- Email: Check for missing or duplicate addresses.
- IDs: Check for blank or changed IDs to prevent overwrites.
Always test a small batch before a full import.
Check these items during your test:
- Row counts before and after.
- Required field errors.
- Duplicate behavior.
- Owner assignment.
- Lifecycle stage mapping.
- Whether you overwrote existing data.
Keep your original CSV and a rollback file ready.
Use AI to make imports safer. Do not use it to skip the review.
Optional learning community: https://t.me/GyaanSetuAi