Mailchimp Magical Import Overview

Insycle's Magical Import module supports the Mailchimp Contacts record type.

Navigate to Data Management > Magical Import. Then select the database and the record type in the top menu.

Select the CSV

Choose the CSV file that you would like to import.

The Preview panel will open and load the CSV rows, with a column for each field. Initially, you may see warning icons next to columns that don't exactly match field names in your Mailchimp database.

Select a Template

Select a template if you or someone on your team has already saved one that can handle importing from the same source. Templates streamline and standardize the import process, enabling the entire team to import data reliably and uniformly each time.

Magical Import templates load configurations that will affect the Data Mapping, Preparation, Validation, and Operations settings. When settings are loaded from a template, a blue number indicates where settings are applied.

If AI is enabled for your selected object type, the Data Mapping section will automatically expand after processing your CSV. If AI is not enabled, click the Data Mapping heading to expand the section manually.

Review and Adjust Field Mappings

After AI processing (or when setting up manually), review how your CSV columns are mapped to Mailchimp fields. AI will automatically map fields that it can identify with confidence. Any fields that still show a warning icon require your attention—either AI couldn't determine the appropriate mapping, or AI is not enabled for this object type.

For unmapped fields, click the Not Mapped dropdown and search for the corresponding Mailchimp field. You can also adjust any AI-suggested mappings if they don't match your intended use.

Specify How to Use the Values for Each Column

Next, tell Insycle how to handle data for each field by choosing one of the four Import Modes for each column:

• Update: Import CSV values into Mailchimp, overwriting existing Mailchimp values (will skip empty CSV values).
• Fill: Import CSV values only when there is no existing value in Mailchimp (will not overwrite existing Mailchimp values).
• Overwrite: Import CSV values, including empty CSV values, into Mailchimp (will overwrite existing Mailchimp values).
• Append: Add CSV values to existing values in Mailchimp. For example, append notes from a CSV to existing notes, or add values on multi-select fields (checkboxes or picklists).

Review and Confirm Matching Criteria

If AI is enabled, it will automatically suggest Matching Criteria based on your CSV columns and Mailchimp fields. Review these suggestions carefully, as Matching Criteria determine how Insycle compares your CSV data with existing Mailchimp records to identify matches for the same entity.

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

• Email address
• Phone number
• ID number
• Street address

You can modify AI suggestions or set multiple matching rules that are evaluated in order from top to bottom. This allows you to 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

Insycle attempts to match each CSV record using the first rule. If no match is found, it proceeds to the next rule, continuing until either a match is found or all rules are exhausted (in which case the CSV record is considered new or unique).

For best results, place your most precise matching criteria at the top of your rule list. Additionally, keep in mind that while names can be included as part of the matching criteria, they should be used in conjunction with other identifiers, as multiple individuals may have the same name.

Set Format for Dates from CSV

The Date Format tab allows you to reformat dates before importing them into Mailchimp.

Learn more about reformatting dates before importing data into Mailchimp.

Click the Data Preparation heading to expand the section.

Under Data Preparation, you can perform bulk edits to the CSV data before uploading it to Mailchimp. The options you select and apply here will be reflected in the Preview, not directly in Mailchimp.

Select fields from your CSV and apply formatting and transformation changes to the data. You can clean up, format, add or remove text, copy values to other fields, or make bulk updates before uploading to Mailchimp. These are the same functions found in the Transform Data module, which you can learn more about here.

As you add functions, you can click Apply after each one to see the changes in the Preview. 

Use Data Validation to filter out records that don't meet your quality standards, or to target a segment before importing them into Mailchimp. This feature helps ensure only clean, properly formatted data enters your system.

To set up data validation rules:

Click the Data Validation heading to expand the section.

Configure your validation criteria:

• Select one or more fields from the Column Name(s) dropdown
• Choose Include or Exclude from the Type dropdown:
  • Include: Only import rows that match this rule
  • Exclude: Skip rows that match this rule during import
• Set the Condition that values must meet (such as "Contains text" or "Contains digits")
• Enter any other text or parameters, if applicable

To add multiple rules, click Add Rule. Records must meet all validation criteria to pass—there is no prioritization of rules.

Click Apply to refresh the Preview with your validation rules applied.

After applying validation rules, the Preview will update to show which records will be excluded. Any rows that don't meet your criteria will display a warning icon. Hover over the icon to see specific details about why the record will be excluded.

  Data validation rules apply to the Preview data rather than the Mailchimp database or CSV file. If you've modified data using Data Preparation or other bulk updates, the validation rules will check against those updated values in the Preview.

Use Data Operations to update values on existing records in Mailchimp. 

Click the Data Operations heading to expand the section.

Make Bulk Changes to a Field 

On the Bulk Update tab, you can add a value to Mailchimp fields even if you don't have the field in the CSV. This will add the same value for all of the imported records.

By default, Insycle will perform your chosen action on all of your CSV data. If you only want to process a few records, return to the table under Preview and check the boxes beside the selected records.

At the bottom of the Magical Import page, there are four actions to choose from: Import, Compare (Preview), Delete, and Export.  

Import CSV Data into Mailchimp

The Import feature will enrich existing records or create new records from data you have in your CSV.

Select the Records Mode to instruct Insycle on how to handle the imported data during the import process.

• Update existing and create net new – If Insycle is unable to find a corresponding record, a new record will be created in Mailchimp.
• Only update existing – If a corresponding record is found, it will be updated with the data from your CSV import. Data that is not matched with an existing Mailchimp record will not be imported.
• Only create net new – Only records that can not be matched with an existing record in your database will be imported. Records that already exist in Mailchimp will not be updated.

You can also add the imported contacts to an existing Mailchimp Audience. Type to search existing audiences in Mailchimp. If you select an existing list, the Show link will let you open it in Mailchimp for a preview.

When you click the Import [X] Contacts button, you'll be prompted to confirm.

Look for Duplicates and Compare Values

Use the Compare (Preview) feature when you want a side-by-side comparison of CSV data against matching items in Mailchimp.

Compare features: 

• Create a new CSV report comparing your import CSV values to Mailchimp.
• See how many contacts from a file are net-new versus already existing in your database.
• Show CSV data side by side with Mailchimp data so you can preview how your CSV import would update data for existing records.
• Check unsubscribes against your Mailchimp database.

This is a read-only operation.

Learn more about using Magical Import to compare CSV data to existing records in Mailchimp.

Delete Listed Items from Mailchimp

Use the Delete feature when you have a CSV containing records you know need to be deleted. You can match the CSV rows to Mailchimp records and easily delete the data in bulk.

Learn more about using a CSV to specify records to delete from Mailchimp.

Export Mailchimp Data Side-by-Side with CSV Values

Use the Export feature when you want more information from Mailchimp about items you have in an external list. Put the items you want to look up in a CSV—you really only need the Matching Criteria used to look for matches in your database. Then select the Mailchimp fields you want to export for the matching records.

Export features:

• Create a new CSV report comparing your import CSV values to Mailchimp.
• Add any Mailchimp field values to include in the export using the Fields to Export.
• See how many contacts from a file are net-new versus already existing in your database.

This is a read-only operation.

Learn more about exporting CRM data for CSV comparison or enrichment.

After the import runs, the Import Result breaks down the import information—how many records you tried to import and how many succeeded, failed, were updated, deleted, or unmodified. Click the Run ID to open a CSV record of the import. Insycle will also send a CSV report of these changes to your email. 

Open the CSV file, and review the Result column to see how each row of your import was handled.

The Result column may show:

• Created - A new record was created in Mailchimp
• Updated - An existing record was found and updated with data from the CSV
• Failed - If there is an issue, the Message field will give you details so you can troubleshoot

You can also see the (Before) and (After Update) values side-by-side for each field in your import.

After you've seen the results in Mailchimp and are satisfied with how the import runs, you can save all of the configurations as a template to use each time you import a CSV with the same source and format. With a template, all of your settings are saved, including field mapping, actions, functions etc., so you will have minimal work for future imports.

Return to the Template menu at the top of the page and click the disk icon to save this as a new template, giving it an informative name.

Insycle uses Matching Criteria to compare your CSV to your Mailchimp data. Matching Criteria must be "unique identifiers." These are data points that could only belong to a single entity—such as email addresses, phone numbers, street addresses, or ID numbers.

Additionally, when using an email field, Insycle will automatically cross-reference any additional email fields in the records for a match. If using a domain field, Insycle will check additional domain fields. 

When you configure your Matching Criteria rules, the Preview will refresh, allowing you to see which records are already in Mailchimp. The records that Insycle found will become blue links that will open the record in Mailchimp.

If you rely on URLs to match imported data with records in Mailchimp, the formatting of those values can be key. Perhaps the data in Mailchimp is inconsistent, with different representatives entering URLs differently, or maybe website addresses are formatted differently in an external data source.

For example:

• https://www.acme.com
• http://acme.com
• acme.com
• www.acme.com

When importing, a CSV with varied URL formats might look like this:

Insycle lets you easily clean and format values from a CSV before import. All the cleanup occurs on the Insycle side, ensuring the import contains standardized data.

By using the Functions under Data Preparation, you can make bulk changes to the CSV data before it is uploaded. The options selected and applied here will be reflected in the Preview, rather than being directly applied in Mailchimp.

To eliminate format variants, you can isolate the second-level domain. Under Data Preparation, select the website or URL column, then select the Extract: Domain from URL function. This will retain only the second-level and top-level domains (acme.com). If you need to take it a step further and remove the top-level domain (keeping "acme"), add a second function to the column: Remove Top-level Domain. 

Click Apply, then review the changes to the column data in the Preview to verify that the column data matches the needed format. In this example, the domain has been extracted from the URL, leaving only the second-level and top-level domains. These are the values that will be imported into Mailchimp.

Learn more about cleaning data before vs. after importing it into Mailchimp.

You can use the Data Validation feature to limit the rows from your CSV that are imported based on the criteria you set. You might use this to import in segments that are handled differently or to exclude unwanted rows.

For example, if your CSV contains data from different countries but you want to import only records related to Poland, add a validation rule to check if the Country field contains "Poland."

When you click Apply, the Preview will update to show which records will be excluded. Any rows that don't meet your validation criteria will display a warning icon.

When date values are detected in a CSV, Insycle will decide which format is being used and make the values consistent when importing. 

Insycle will recognize the following date formats, all of which will work with or without the - or / symbols:

1. Date time with timezone: 2018-07-19T23:25:45.671-0400
2. Date time in UTC timezone: 2018-07-19T10:15:30Z 
3. YYYY-MM-DD HH:MM:SS
4. Date (YYYY-MM-DD): 2018-07-19 or 2018/07/09
5. Date (M-D-YYYY): 07-19-2018 or 7/19/2018

You can override this automatic standardizing using the Date Format tab, which allows you to reformat dates before the data is imported into Mailchimp.

Learn more about reformatting dates before the data is imported into Mailchimp.

With the Activity Tracker, you have a complete audit trail and history of changes made through Insycle. At any time you can download a CSV report that lets you see all of the changes that were made during an import operation.

Navigate to Operations > Activity Tracker, enter "import" to search for the Magic Import module, or look for a template name, then click the Run ID for the operation.

If AI is enabled for your object type, many warning icons may automatically disappear after the initial CSV processing. Remaining warning icons indicate issues that still need your attention.

If there are issues with a CSV row, a red warning icon will appear at the left end of the row and next to the relevant field in the Preview. Rows with errors will not be imported.

To learn what the problem is and determine steps to resolve it, hover over the red exclamation mark—an explanation of the error will display.

Several common reasons for the warning icon include:

• Your validation rules
• Several records match your criteria
• Invalid picklist values
• Invalid reference values
• Unmapped columns

Your validation rules. A row will show warnings and be excluded from the operation based on your validation rules. The warning info will list which rules apply to the row.

There are several records in Mailchimp that match. If multiple records have the same Matching Criteria, Insysle identifies these as matching records in Mailchimp.

If there should be only one record with this value, you may need to first merge duplicates and then try importing again.

If there are legitimate reasons for a Matching Field value to exist in more than one record, try adding additional Matching Criteria to make it more specific.

Invalid reference values. If a column is mapped to a Mailchimp field that references other data, such as owners or associated record IDs, and no match is found, an error will appear.

Invalid picklist values. If a Mailchimp field includes dropdown options and the data in your CSV does not match, you'll see an "Invalid picklist value" error. This value needs to be changed to match the dropdown options in Mailchimp.

To quickly fix the import data directly in the Preview, hover over a value and click the pencil icon.

Once you've selected your Matching Criteria, filter options will become available in the Preview. You can use the Show Only Warning Rows filter to view only rows with warnings.

If a record in your CSV is not being matched to a Mailchimp record and you know that it should be, there are several potential causes:

1. The Matching Criteria you chose does not match between the CSV and Mailchimp

   Insycle depends on your Matching Field selection to compare your CSV to your Mailchimp data. If Insycle can't find matches between the two sources, you may need to find a more reliable but unique field.

   Have a look at the data in Mailchimp using the Grid Edit module, adding columns to the layout so you can explore the fields and values. Then, compare this against the columns and values in your CSV to find a reliable but unique field that matches the two sources. 

2. You are using too many fields in Matching Criteria rule

   You can select more than one field in each Matching Criteria rule; however, ALL of the fields must match, not just one or some of them. If you include five fields and four of them match, but one doesn't, Insycle will not consider the rule a match.

   Typically, it is best to use a single field for your first Matching Criteria to improve the likelihood of finding existing records in Mailchimp. Then you can add additional rules to match multiple fields.

   

3. Your Matching Criteria is too broad

   Insycle uses Matching Criteria to compare your CSV to your Mailchimp data. If you're using a field that is not truly unique as Matching Criteria, it's likely that Insycle won't be able to identify one single record as a match. For instance, there could be many people with the first name, "John" in Mailchimp. This is why uniqueness is key.

   When selecting your Matching Criteria, make sure it is truly a "unique identifier." These are data points that would only belong to a single record—such as email address, phone number, street address, or ID number. For companies, it could also be company name, or company domain.

   

4. AI suggested inappropriate matching criteria

   While AI can recommend matching criteria, it might not always select the most suitable fields for your specific data. Review the AI-suggested matching criteria and adjust or replace them with more appropriate options based on your understanding of the data quality and uniqueness in both your CSV and Mailchimp.

5. There is a syncing issue

   To refresh the data in Insycle, navigate to Settings > Sync Status, and next to the account name, click the Sync changes from last day button (lightning bolt icon).

   

   Alternatively, you could log out of Insycle and then log back in.

   For help re-syncing a specific field, contact support.

If AI is not providing mapping suggestions or the suggestions don't make sense, check the following:

• AI settings are enabled: Navigate to Settings > AI and ensure that at least "Meta" level access is enabled for your selected object type.
• Column naming: AI works best when CSV column names are descriptive and similar to your Mailchimp field names. Generic names like "Column1" or "Data" may not generate good suggestions.
• Template conflicts: If you selected a template after AI processing, template settings override AI suggestions. Try clearing the template to see AI suggestions, or select the template first.

If AI is enabled but not working as expected, you can always map fields manually using the dropdown selections.

Even when using AI tools, it is normal that some fields are not automatically mapped. AI mapping works best when:

• Column names are descriptive: Fields like "email," "phone," or "company" are easily recognized
• Names match Mailchimp conventions: CSV columns that closely match your Mailchimp field names will map more reliably
• Data types are clear: Ambiguous column names or custom fields may require manual mapping

For any remaining unmapped fields (those still showing warning icons), manually select the appropriate Mailchimp field from the Not Mapped dropdown.

If you have set up formatting or standardization functions under Data Preparation but aren't seeing those changes reflected after importing your data, make sure that you click the Apply button.

You must Apply these updates to your CSV data before importing it into Mailchimp. You will see these changes reflected in the Preview.

Yes, Insycle will automatically map fields it can identify. However, if it cannot determine what a field should map to, a warning icon will appear under Data Mapping, and the Mailchimp field dropdown will display "Not Mapped." You should select the appropriate Mailchimp field to ensure the field is included in the import.

Yes, you can easily add to existing data using the Fill or Append Import Modes under Data Mapping.

• Fill: Import CSV values only when there is no existing value in Mailchimp (will not overwrite existing Mailchimp values).
• Append: Add CSV values to existing values in Mailchimp. For example, append notes from a CSV to existing notes or add values on multi-select fields (checkboxes or picklists).

Yes, Insycle provides many functions that can clean, format, and standardize data from your CSV before it's imported into your database. The options selected and applied here will be reflected in the Preview, not done directly in Mailchimp.

Under Data Preparation, you can select columns and apply formatting and transformation changes to the field data. These are the same functions found in the Transform Data module, which you can learn more about in the Function Catalog.

Yes, Insycle allows you to compare the CSV to existing data in your Mailchimp records. The Compare (Preview) tab in the final step provides a simple CSV report that shows the values from your original CSV alongside the values currently in Mailchimp.

To learn more, see the Compare CSV Data to Existing Records In Your CRM article.

AI mapping provides an excellent starting point and can correctly identify most standard fields when CSV column names are descriptive. However, you should always review AI suggestions because:

• Custom fields or unique naming conventions may not be recognized
• Similar field names might map to unexpected Mailchimp fields
• Your specific business requirements may need different field mappings
• Matching criteria suggestions should be validated against your data quality

Think of AI mapping as a time-saving assistant that handles the obvious mappings, so you can focus on complex or custom fields that need human judgment.

Yes, you can disable AI features by navigating to Settings > AI and turning off the toggles for the object types where you don't want AI assistance. You need Admin or Owner Insycle permissions to change these settings.

When AI is disabled, you'll manually map all CSV columns to Mailchimp fields and set your Matching Criteria.

You can also use a hybrid approach: enable AI for initial suggestions, then manually review and adjust mapping for each column to maintain full control while benefiting from AI's time-saving capabilities.

Yes, the Magical Import module can handle up to 100k rows for each CSV import. Keep in mind that the more rows and fields you have in your CSV, the slower the import process will be. If you run into any issues, try breaking the CSV into segments and removing any extraneous fields.