Column mapping

Operelio matches your column names to CRM field names using common patterns. "First Name" maps to the first name field. "Email Address" maps to email. "Phone Number" maps to phone. Variations like "fname", "e-mail", and "tel" are also recognized.

The matcher is case-insensitive and ignores underscores versus spaces, so "first_name", "First Name", and "FIRST NAME" all resolve to the same field. If your column header uses unusual notation (camelCase plus dot notation, like contact.firstName), it may not auto-match. Check the mapping before running.

Auto-detection is a starting point. Always check the mappings before running, especially if your column names are unusual.

Each CRM field for the record type you chose has its own row. Click the column next to a field to change it, or pick No column to leave the field empty. A column you don't pick for any field is listed under Not used from your file and left out of the export. Required fields are marked Required. You can't continue to Review until every required field has a column and at least one field is filled. If a required value is empty in some rows, Operelio flags those rows but does not block export. With the CRM connected, the rows are your account's own fields, custom ones included.

Those warnings are about the shape of your file. If you are pushing rather than downloading, the report on the push screen goes further and checks your values against the CRM account you connected: a value that isn't on a restricted picklist, text longer than the field allows, a field your account doesn't have, a field your user can't write to. Each one arrives with a row count and an example, before anything is written.

If your data has separate columns that should combine into a single CRM field (like "street", "city", "state" into "address"), you can merge them during mapping. Pick the target field, select the source columns, and choose a separator. Operelio combines them in order.

The common case is names. Where the CRM has one Name field, as Pipedrive does, the mapping screen offers "First & Last Name (combined)" as a single column you can map to it. Both halves reach the CRM, joined with a space.

Three columns are worth pointing at deliberately when you are pushing to HubSpot, Salesforce, or Pipedrive.

An owner column sets who owns each record, matched to a user in your CRM; you can also assign the whole push to one rep instead. A notes column is attached as a note, rather than written into a field, on the HubSpot contacts and Pipedrive people and organizations the push creates. A record the push matches keeps the notes it has, and HubSpot companies and Salesforce records get no note. A company column finds or creates the Pipedrive organization, or the Salesforce account, and links the contact to it.

None of the three is a plain field mapping, so none of them counts as a column that got left behind.

Several cleanup toggles run during export. Split full name and Combine first and last name are on the Map step's Names row; the rest are under Clean-up rules on the Review step:

Use the Remove unmapped columns toggle to keep notes or internal columns in the export when you are debugging. Turn it off and any column you did not map still appears in the output file alongside the CRM-mapped columns.