CRM imports that don't break everything

Importing new data into a CRM should be routine. In practice, it's often where data quality goes to die. Duplicate records get created. Existing fields get overwritten. Picklists get polluted. And six months later, nobody trusts the CRM because nobody knows which records are real.

The most common mistake: importing without deduplicating first. If you add 5,000 new contacts to a CRM that already has some of them, you have created duplicates. Now your SDRs see two records for the same person, with different data, and don't know which to trust. Always run a deduplication pass against existing records before importing.

The second mistake: mapping fields incorrectly. The import CSV has a 'Title' column. Your CRM has a 'Job_Title__c' field. Someone maps them during import and now you have titles in two different fields, neither complete. Standardize your field mapping before import and validate it with a 10-record test batch.

The third mistake: importing without preserving source information. Six months from now, someone will ask where a specific contact came from. If every imported record doesn't have a source tag, an import date, and a confidence score, you will not be able to answer. Add these fields to every import template.

We recommend a three-step import process: validate a small batch first, run a full deduplication pass, then import with field mapping and source tracking. It takes an extra hour upfront but saves weeks of cleanup later.

For teams importing regularly, consider setting up a staging sandbox. Import to a test environment first, run quality checks, then push clean data to production. This is standard practice for code deployments. Your CRM data deserves the same level of care.