Mapping CSV Columns to CRM Fields, Field Logic, and Matching Criteria

In the Magical Import module's Data Mapping section, the Field Logic setting controls how values in each mapped CSV column are applied to the corresponding CRM field during import.

  Note: When AI is enabled, Insycle analyzes your CSV column names and automatically suggests field mappings (which CRM fields correspond to your CSV columns) and Matching Criteria (which fields to use for identifying existing records). Always review these suggestions carefully before proceeding, as they may not be a perfect fit for your specific use case.

After AI processing (or when setting it up manually), review how your CSV columns are mapped to CRM fields. AI automatically maps fields it can identify with confidence. Any field still showing a warning icon needs your attention—either AI couldn't determine the appropriate mapping, or AI isn't enabled for this object type.

For unmapped fields, click the Not Mapped dropdown and search for the corresponding CRM field. You can also adjust any AI-suggested mapping that doesn't match your intended use.

The image above shows the Data Mapping section of the Magical Import module, with a red warning icon next to the section title. The CSV Column row lists Email, Last Name, First Name, and Owner; Email, Last Name, and First Name are mapped, while Owner shows "Not Mapped" in gray with a red warning icon. An arrow points to the open Not Mapped dropdown, which lists candidate CRM fields — "Account Owner Date," "All owner IDs," and "Contact owner" — filtered by the search term "own."

In the Magical Import module's Data Mapping section, Field Logic controls how the values in a mapped CSV column are applied to the corresponding CRM field during import. AI suggestions do not affect Field Logic settings — you'll need to configure these for each column based on your specific requirements. There are four Field Logic options:

• Update: Import CSV values into your CRM, overwriting existing CRM values. Empty CSV values are skipped.
• Fill: Import CSV values only when there is no existing value in the CRM. Existing CRM values are not overwritten.
• Overwrite: Import CSV values, including empty CSV values, into your CRM. Existing CRM values are always overwritten.
• Append: Add CSV values to existing values in your CRM — for example, appending notes from a CSV to existing notes, or adding values to multi-select fields (checkboxes or picklists). When using Append on multi-select fields, you don't need to include the record's existing field values in your CSV — Insycle adds the new values alongside the existing ones without overwriting them.

The image above shows the Data Mapping section of the Magical Import module, with the Field Logic row highlighted in a blue box. The CSV Column row lists Email, Company Name, First Name, and Last Name, each mapped to the corresponding CRM Field. The Field Logic row shows a different option selected for each column: Update for Email, Fill for Company Name, Overwrite for First Name, and Append for Last Name.

In the Data Mapping section of Magical Import, Matching Criteria determine how Insycle compares your CSV data with existing CRM records to identify matches for the same entity.

If AI is enabled, it automatically suggests Matching Criteria based on your CSV columns and CRM fields. Review these suggestions carefully, since they directly determine which CSV rows Insycle treats as existing records versus new ones.

Matching Criteria are unique identifiers that typically belong to only one entity, such as:

• Email address
• Company domain (for business records)
• Phone number
• ID number
• Street address

The image above shows the Data Mapping section of the Magical Import module, with the Matching tab and Matching Criteria area highlighted in a blue box. The Matching tab displays a blue numbered badge showing "1." Under Matching Criteria, the Matching Fields dropdown is set to "Email," with icons to add another rule and duplicate the current one.

You can modify AI suggestions or set multiple matching rules that are evaluated in order from top to bottom. This lets you find matches based on multiple criteria in a single step. For example, you could use the following criteria to match contact records:

1. Email address
2. First Name + Last Name + Company Name
3. First Name + Last Name + Phone Number

The image above shows three Matching Criteria rules stacked in the Data Mapping section of the Magical Import module. The first rule's Matching Fields is set to "Email." The second rule's Matching Fields is set to "Company Name, First Name, Last Name." The third rule's Matching Fields is set to "First Name, Last Name, Phone Number." Each rule includes icons to add, remove, reorder, and duplicate the rule.

Insycle attempts to match each CSV record using the first rule. If it finds no match, it moves to the next rule, continuing until it finds a match or exhausts all rules—at which point the CSV record is considered new or unique.

For best results, place your most precise Matching Criteria at the top of your rule list. While names can be included as part of the Matching Criteria, always use them in conjunction with other identifiers, since multiple individuals may share the same name.

Note: While AI can provide an excellent starting point for field mapping and Matching Criteria, always verify that mapped fields actually contain the type of data you expect, and that Matching Criteria use truly unique identifiers for your use case.

Matching on Multiple Fields (AND Logic)

In the Magical Import module's Data Mapping section, a Matching Criteria rule that includes more than one field requires all of those fields to match — not just some of them. If a rule includes five fields and four of them match, but one doesn't, Insycle does not consider the rule a match.

The image above shows the Matching Criteria area of the Data Mapping section in the Magical Import module, outlined with a yellow dashed border and a yellow warning icon. The Matching Fields dropdown is set to five fields in a single rule: "Company Name, Email, First Name, Last Name, Phone Number," illustrating a rule that may prevent a match because the rule has too many fields.

This behavior interacts with the Records Mode you select for the import:

• Under Update existing and create net new or Only create net new, a CSV row that doesn't satisfy all fields in a rule results in a new record being created.
• Under Only Update Existing, a row that doesn't satisfy all fields in a rule is treated the same as any other unmatched row — it is not imported, since Insycle has no record it can confidently identify as the correct match. This doesn't show a warning icon in the Preview, since a non-match isn't one of the error conditions Insycle flags there.

The image above shows the "Action to take with the CSV" panel in the Magical Import module, with the Import tab selected. Under Records Mode, "Only create net new" is selected, alongside the other available options: "Update existing and create net new" and "Only update existing." A checkbox to email the CSV report to an address is checked, and an "Import 2 Contacts" button appears below.

Typically, it's best to use a single, precise field for your first Matching Criteria rule to improve the likelihood of finding an existing record in your CRM. You can then add additional rules to match on multiple fields.

If your CSV records aren't matching the CRM records you expect, see Troubleshooting Magical Import for common causes and how to resolve them.

In the Magical Import module's Data Mapping section, the Date Format tab sits alongside the Matching tab and lets you override how dates from your CSV are parsed before import.

The image above shows the Data Mapping section of the Magical Import module, labeled with a blue numbered badge showing "2." The CSV Column, CRM Field, and Field Logic rows show Email, Company Name, First Name, Last Name, and Phone Number columns, each set to "Update." The Date Format tab is selected, showing a blue numbered badge with "1," and the Matching tab also shows a blue numbered badge with "1." The Date Format field is set to "yyyy-MM-dd," with a sample reading "2025-04-21 or 2025/04/21."

For the full list of default date formats Insycle recognizes and how to override them, see Date Formats for CSV Imports.