Import from CSV
One guided wizard imports people, companies, households, or tasks from a spreadsheet in four steps. Matched, tagged, and deduplicated.
2 min read
Prepare the file
Use a CSV with a header row. Column names like “First name”, “Email”, “Phone”, “Company”, or “Tags” are preselected automatically on the mapping step. For people: a Company column links each person to a company, creating the company if no existing one matches its name. Addresses do the same for households. A Tags column applies its comma-separated tags to just that person. For companies and tasks the wizard needs a mapped name column. Rows without one are skipped. For households, rows matching an address you already have (or repeated in the file) are skipped, and new addresses are queued for geocoding. Both UTF-8 and Excel-exported CSVs work as-is.
The four steps
Upload Drop the file or browse to it. You’ll see the row and column counts before anything else happens. Map columns Each column gets a best-guess field match. Review and correct it. Anything left unmapped shows a “Skipped” chip and is left out. Review For people, duplicates are matched by email, the same identity rule used everywhere in pplCRM. Rows that match an existing person let you merge (fills blank fields, never overwrites), skip, or import as new anyway. Rows with a broken email address get their own choice: skip them or import without an email. Add a comma-separated tag list and/or a list here too (tags also apply to household imports). Other types show a plain recap: how many rows will import and how many will be skipped, and why. Import Confirm the recap and click Import N people (or companies, households, tasks). The import runs in the background, so you can navigate away while it works. It lands in import history and the Activity log either way. If you stay, the done screen offers View imported records, Import another file, or Back to import history.
After the import
Spot-check a few records against the source file. If you chose "import as new anyway" for any matched duplicates, run the Duplicates finder to reconcile them when convenient. The import history row shows what type each import was and keeps the original file downloadable for 90 days; for people imports, skipped rows are downloadable with the reason each was skipped.
Test with a small file first
Related
Try this on sample data.
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