Standardize Job Title, Industry, State, Country, or Any Other Free-Text Field

Navigate to the Cleanse Data module, and in the top menu select the database and record type. Then explore the default templates for a pre-built solution.

Under Step 1, search for the field you want to clean up. The results table shows field properties, including the field type and the number of unique values within the field across your database.  

Click the checkbox beside the field.

The different values that are contained in your database for the selected field will populate the Record Viewer at the bottom of the page.

Explore the different field variants to identify inconsistent or irrelevant values. Use the checkbox to expand a value set.

This opens up a secondary Viewer below the first, where you can review the individual records and get additional context.

To see more information for each of the resulting records, you can alter the fields in the Record Viewer by using the Layout tab in Step 2. 

When looking to fix specific values, use the filter to work with a focused subset of your data. 

Under Step 2, click the Filter tab and select the field to work with. Use the Condition to set the rule that the data in the selected field must meet. 

In the below example, only records that include the phrases "CEO" or "Chief" in the Job Title field will be part of this cleanup task. The bar "|" character is used to separate multiple values. 

When you click Search, the Record Viewer table at the bottom of the page will be updated.

In the Record Viewer, check the box for the values you want to update. Or to make more granular changes, select individual records in the secondary Viewer below the first.

Under Step 3, specify what the selected field values should be changed to. In this example, all the records that have a Job Title of "Chief Executive Officer," will be updated to "CEO."

Click the Update button and confirm the change.

To review changes after applying them in the CRM, use the Activity Tracker.

All settings here can be saved in a template. You can run similar processes and create templates for fields like Industry, U.S. State, Zip Code, or Country.

If you are sure a field contains data in your CRM but aren't seeing the values or records in the Record Viewer at the bottom of the page, it is often due to the Filter settings under Step 2.

Here are a few things to look into:

1. Ensure there isn't anything in the filter you didn't intend to use. This often happens if you start with an existing template.
2. Ensure that your filter is accurate and not too specific. For instance, if you are using the "is" operator in your filter, you might broaden the condition using "contains" or "starts with" to identify other records with slight differences.
3. Make sure that you have clicked the Search button.

If you still don't see the expected data, it is likely a field 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 Insycle support.

For a complete guide to troubleshooting issues with Insycle, please refer to our article on Troubleshooting Issues.

Navigate to the Transform Data module, and in the top menu select the database and record type. Then explore the default templates for a pre-built solution.

Under Step 1, set up a filter to narrow down the database records to show only what you want to change. This ensures you aren't needlessly running the process on all records in your database.

In this example, the filter will surface records where the Job Title contains "VP."

Click the Search button and scroll down to the Record Viewer at the bottom of the screen. You will see all records that match your filter.

In Step 2, you can set rules to format and clean up your data. It is best practice to create a separate template for each field you want to modify.

Select the Field, then choose a Function, telling Insycle how the data should be standardized. There are pre-built functions for standardizing phone numbers, countries, states, domains, and other values. Explore the Function Catalog for a complete list.

In this example, the Job Title field uses the Map: Values function. In the first function row, the Existing Text field will look for the values "vp sales," "vp of sales,” or "vice president of sales." The New Text field specifies that the text "VP Sales" should replace values that match the existing text.

In the next example, the State/Region field uses the Standardize: US States, CA provinces function. This standardizes states to their full names like this:

• NY→ New York
• new york → New York

 

Preview Changes in the CSV Report

With the filters and functions set up, you can preview the changes. It's important to verify that your formatting works as expected before those changes are pushed to your live database.

Under Step 3, click the Review button and select the Preview option.

On the Notify tab, you can select recipients for the email report and add additional context for recipients. (Make sure to hit Enter after each email address.)

On the When tab, click Run Now and select which records to apply the change to (you could do All, but if you have many records, you may just want to do a chunk for your preview), then click the Run Now button.

Open the CSV file from your email in a spreadsheet application and review the (Before) and (After) values side-by-side. This example shows the Job Title (Before) and Job Title (After).

If the results don't look the way you expected, go back to your filters in Step 1 and functions in Step 2 and try making some adjustments, then preview again.

Apply Changes to the CRM

If everything in your CSV preview looks correct, return to Insycle and move forward with applying the changes to the live CRM data.

Click the Review button under Step 3 and select Update Mode. 

On the Notify tab, add any additional recipients, then click Next. 

On the When tab, you can choose to run and apply the update now, or you can set up an automation to run the template on a set schedule. The first time you apply these changes to the CRM, we suggest you Run Now.

After you've seen the results in the CRM and are satisfied with how the operation runs, you can save all of the configurations as a template, and set up automation so this formatting operation runs on a set schedule.

By automating with a template, you'll ensure that your fields are consistently formatted on an ongoing basis.

Select the Magical Import module from the left navigation, then select the database and the record type in the top menu.

Click the Choose button and select the CSV file you would like to import. Uploading a file into Insycle does not import it to the CRM right away; instead, you can prepare the data in a variety of ways before actually importing it to the CRM.

The Preview panel will open and load the CSV rows with a column for each field. 

Explore the templates to see if there's already something set up for your particular import task.

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.

Click the Data Mapping heading to expand the section.

Review and Adjust Field Mappings

After AI processing (or when setting up manually), review how your CSV columns are mapped to CRM 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 CRM field. You can also adjust any AI-suggested mappings if they don't match your intended use.

Specify How to Handle the Values from Each Column

With all relevant fields mapped, instruct Insycle on how to use the data on a field-by-field basis by selecting the Import Mode, located in the third row of the table.

The four Import Modes: Update, Fill, Overwrite, and Append—offer different ways to import CSV data into your CRM, ranging from updating existing records, filling empty fields, replacing data, to adding new information.

Review and Confirm Fields for Matching CSV Rows to CRM Records. 

If AI is enabled, it suggests Matching Criteria based on your CSV columns and CRM fields. Review these as they determine how Insycle compares data to identify matches.

Matching Criteria, like email or ID, are unique to individuals. For example, Maria Smith's email or ID shouldn't match others. If a record matches these fields, it's identified as Maria Smith.

You can adjust AI suggestions or manually select the Matching Field. Multiple rules can be created and evaluated in order for multi-criteria matching.

When you configure your Matching Criteria rules, the Preview will refresh, and you'll be able to see which records are already in your CRM. The records that Insycle found will become blue links that will open the record in your CRM.

If a record has errors, a red warning icon will be shown on the left side of the record. 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. Records with errors will not be imported. 

Click the Data Preparation heading to expand the section.

In this step, you set rules to make the field values consistent. This ensures that your data is standardized while it is being imported into your CRM database.

Select the Column Name of the CSV field, then choose a Function to tell Insycle how the data should be formatted. When finished, click Apply.

In the example below:

1. The Industry column uses the Map: Values function. The Existing Text field will look for the values "tech," "software,” or "computer." The New Text field specifies that the text "Technology" should replace values that match the existing text.
   This would change any values of "tech" or "software" to "Technology."
2. The Country/Region column uses the Standardize: Country Code2 to Code3 function. This standardizes states with their full name like this:
   • United States → USA
   • Poland → POL
3. The Website URL column uses the Extract: Domain from URL function, which retains only the second-level and top-level domains. This would standardize "https://acme.com" or "www.acme.com" to "acme.com."

Explore the extensive list of Function options in the Function Catalog to find formatting options for any field in your CSV.

Optionally, you may utilize various other tools and features to refine your CSV data prior to importing it into your CRM. For detailed information, refer to the Magical Import Module Overview.

Exclude data that fails to meet validation criteria. Use Data Validation to filter out records that don't meet your quality standards, or to target a segment before importing them into your CRM.

Update matching CRM records. Use Bulk Update to add a value to CRM fields, even if the field is not included in the CSV. This will add the same value for all the records.

Create relationships with matching CRM records using the Associate/Link feature (the title will vary depending on your CRM's naming convention) between CSV records and existing records in your database during import. Learn more about creating relationships when importing.

Define date formats. Override the default Date Format to choose a specific standard before importing the data into your CRM.

Make changes to values directly in the Preview. Hover over a value and click the pencil icon to make one-off changes before importing.

Select CSV Rows for the Operation

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. Leave the checkboxes blank to import all of the records.

Configure the Import

At the bottom of the Magical Import page, configure the Import.

Select the Records Mode to tell Insycle how the imported data should be handled during the import process: 

• Update existing and create net new – If unable to find a corresponding record, a new record will be created in your CRM.
• Only update existing – If a corresponding record is found, it will be updated with the data from your CSV import. Records that are not matched with an existing CRM 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 your CRM will not be updated.

  If importing HubSpot contacts, you will also have the option to add your imported data to an existing List. If importing Salesforce contacts or leads, you can add the imported data to an existing Campaign.

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

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.

Review the CSV file to see how each row of your import was handled. You can see the (Before) and (After Update) values side-by-side for each field in your import. 

If you see any "Failed" Results, review the Message to understand the issue and determine steps to resolve. You can also revisit any warnings shown in the Preview.

When you are satisfied with the results in your CRM, you can save all of the configurations as a template to reproduce the same formatting operation in the future. 

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 using the Map functions in the Transform Data or Magical Import modules, you must account for every variation in the field. Even small differences, such as extra whitespace or errant keystrokes, must be accounted for in the Existing Text field.

To account for these variations, you can:

• Use the Cleanse Data module to identify the variations that can be included in the Existing Text parameter.
• Use other transform functions before mapping. Clear non-letters, remove whitespace, or format the field in bulk before importing.

Functions will be executed in the order listed, so it might work best to include cleanup functions before mapping ones.

Yes. For organizational purposes, it is best practice to create a new template for each field that you would like to standardize.

The Transform Data and Magical Import modules offer dozens of functions to help you standardize data. You can change cases, format phone numbers, replace specific values, concatenate, remove whitespace and character types, standardize states or countries, and more. For a complete list with descriptions, see the Function Catalog.