Bulk Import Contacts: Bring Your Existing Data into AI Engage CRM

What is Bulk Import?#

The Bulk Import tool uploads a spreadsheet — CSV, XLSX, or XLS — and creates or updates hundreds of contact records in one operation. It is the fastest way to bring your existing customer database into AI Engage CRM when you are starting out, or to add a batch of new leads after a trade show or campaign.

Before you start — prepare your spreadsheet#

The importer accepts CSV, XLSX, and XLS files up to 50 MB. Before uploading, make sure your file is structured correctly:

• Row 1 must be column headers — e.g. First Name, Last Name, Email, Phone, Company

• One contact per row — no merged cells, no blank rows between data

• Consistent date format — pick one format (e.g. DD/MM/YYYY) and use it throughout

• Valid email addresses — used for duplicate detection; invalid emails will cause rows to fail

• Phone numbers with country code — e.g. +1-555-0101 or +44 7700 900000

• No special characters in headers — the auto-mapper works best with clean, readable column names

Step 1 — Import Contacts#

From the left sidebar, navigate to Contacts. Click the Import button at the top right of the contacts list — or go to CRM → Contacts → Create Contacts and click on Import Contacts. The Import wizard opens.

Step 2 — Click Import Contacts#

Step 3 — Upload your file and configure settings#

Drag your file onto the upload area, or click Choose File to browse. Once the file is selected, the wizard previews the first few rows so you can verify the data loaded correctly.

Below the file preview, configure the import settings:

• Import Mode — choose one of three options:

  • Add new records — only creates new contacts; skips any row that matches an existing contact

  • Update existing records — only updates contacts that already exist; skips rows with no match

  • Update existing and add new — updates matches and creates new contacts for rows with no match

• Duplicate detection field — the field used to match incoming rows to existing contacts (required when using Update mode)

• Contact Status — set all imported contacts to Active or Inactive

• Record Owner — assign all imported contacts to a specific CRM user (defaults to you)

• Compliance — confirm that you have permission to email these contacts

  

Step 3 — Map your columns to CRM fields#

The mapping step shows a table with three columns: your spreadsheet column name, a sample value from row 2 of your file, and a CRM field dropdown. The auto-mapper pre-fills as many mappings as it can recognise.

Review each row and correct any mismatches:

• Select the correct CRM field from the dropdown for each column

• Columns you do not want to import — select Don't use this column

• Each CRM field can only be mapped once — already-mapped fields are greyed out in the dropdown

• First name is required. Fields marked with a red asterisk * — you cannot proceed until all required fields are mapped

  

Step 4 — Assign to a Contact List (optional)#

Select one or more existing contact lists to add the imported contacts to, or create a new list on the spot. This step is optional — skip it if you do not use lists.

Adding contacts to a list during import is faster than tagging them individually afterwards, especially for segment-specific imports like "Trade Show Leads Q2" or "Newsletter Subscribers".

Step 5 — Review and start the import#

The Review step summarises everything you have configured: import mode, dedup field, record owner, contact status, field mappings, and selected lists. Check each section before starting.

Tick Send me an email when the import completes if you want a notification — useful for large files that take several minutes to process. Then click Start Import.

After the import — check the results#

When the import completes, you can view the full results from Contacts → Import (or Settings → Data Administration → Import). Each import job shows:

• Created — new contact records added

• Updated — existing contacts refreshed

• Skipped — rows ignored (duplicate in Add-only mode, or no match in Update-only mode)

• Failed — rows that could not be processed due to validation errors