How Do I Map Columns During Import?

About

Column mapping is the second step of the Goliath upload wizard, appearing immediately after your CSV file is parsed. During this step, you match each column header from your spreadsheet to the corresponding Golioth field where that data should be stored. Goliath automatically suggests mappings for columns with recognizable names like “First Name” or “Phone 1,” but you retain full control to review, override, or skip any column. Accurate mapping ensures your contact and property data lands in the right fields, making it searchable, filterable, and ready to use in campaigns and workflows.

Step-by-Step Guide

1. Review auto-matched columns

   After your CSV is parsed, Goliath displays each column header from your file alongside a dropdown showing the suggested Goliath field. The platform uses smart pre-mapping to automatically match columns whose headers closely resemble known field names—for example, “First Name” maps to firstName and “Phone 1” maps to phone. Scan the list to verify that the auto-matches are correct.

2. Override or adjust mappings as needed

   Click the dropdown next to any column to change its destination field. You can select a different Goliath field from the list, choose Custom Field to route the column to an organization-defined custom field, or select Skip / Ignore to exclude the column from the import entirely. Unmapped columns that have no Goliath field match are ignored by default, so you only need to explicitly skip columns if you want to confirm their exclusion.

3. Map contact-specific fields (for contact uploads)

   When importing contacts, common mappable fields include First Name, Last Name, Full Name, Phone (with type mobile or landline), Email, Mailing Address (broken into street, city, state, and zip components), Contact Type, Tags, and any custom fields your organization has defined. If your CSV combines fields—such as a single “Name” column instead of separate first and last names—Goliath attempts to split the data automatically, though you may achieve cleaner results by pre-processing your CSV.

4. Map property-specific fields (for property uploads)

   For property imports, typical fields include Property Address (parsed into street, city, state, and zip), Beds, Baths, Sqft, Year Built, Owner Name, Owner Mailing Address, Tags, and property-specific custom fields. Ensure address components are mapped correctly so Goliath can geocode and display properties on maps and in search results.

5. Save your mapping for future uploads (if available)

   Some upload wizards remember your last mapping configuration for repeat imports from the same data source. Look for a Save mapping checkbox or toggle near the bottom of the mapping screen. Enabling this option allows you to skip the column-mapping step the next time you upload a file with the same structure, streamlining your workflow.

6. Proceed to finalize the import

   Once all columns are mapped or skipped to your satisfaction, click Next or Continue to advance to the final step of the wizard. Goliath will validate the data, report any problematic rows, and complete the import. Successful rows are added to your database, while rows with errors are typically reported at the end without failing the entire upload.

Pro Tips

• If your CSV includes extra header rows (for example, a title row followed by the actual column headers in row 2), use the wizard’s data starts on row option if available to tell Goliath which row contains your field names.
• When importing combined fields like a single “Name” column, Goliath will attempt to parse first and last names automatically—but manually splitting names in your CSV before upload yields the most reliable results.
• Bad or incomplete rows do not halt the entire import. Goliath processes all valid rows and provides a summary of any rows that failed validation, allowing you to correct and re-upload only the problem records.

Frequently Asked Questions

Q: What happens if my CSV has a “Name” column instead of separate first and last names?

Goliath attempts to split combined name fields automatically during import. For best results, consider pre-processing your CSV to separate first and last names into distinct columns before uploading.

Q: Can I re-import a corrected file if I notice errors after the upload completes?

Yes. You can upload a corrected CSV using the same workflow. If duplicate detection is enabled in Goliath, the platform will merge or update existing records rather than creating duplicates.

Q: Do bad rows fail the entire import?

No. Goliath processes all valid rows and reports any rows with validation errors at the end of the import. Successful rows are added to your database, and you can review the error log to correct and re-upload only the problematic records.

Q: What if my CSV has columns I don’t need in Goliath?

Select Skip / Ignore from the dropdown next to any column you want to exclude. Columns with no mapping are ignored by default, so you only need to explicitly skip them if you want to confirm they won’t be imported.