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


How to Apply Formatting in Bulk So Records Have Consistent Values

Your team needs to segment CRM data to send personalized messaging and generate effective reports but is having trouble surfacing relevant records because of data inconsistencies. 

With Insycle, there are several ways you can standardize field data in your CRM. To analyze the variations in your database and make quick bulk changes, use the Cleanse Data module. The Transform Data module is perfect for standardizing data in bulk, one-time, or automatically on an ongoing basis. If you have data from an external source that you want to make consistent with your CRM while importing, use the Magical Import module.

Standardize Data with the Cleanse Data Module

The Cleanse Data module allows you to explore your data, identify opportunities for standardization, and bulk update records in your CRM. 

Process Summary

  1. Choose a field to explore.
  2. Analyze the variations and decide how to standardize.
  3. Filter records down to only those that need changing.
  4. Select records to modify.
  5. Specify what changes to make.
  6. Apply the changes to the CRM.


Step-By-Step Instructions

Step 1: Select a Field and Explore the Values

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. 
Step 2: Filter Out Records That Don’t Need Changing

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.

Step 3: Select Records, Specify the Change to Make, and Update the CRM

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. Note that there is no preview step here. Once confirmed, the update will be applied to your CRM.

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.


Records Aren't Showing Up in the Viewer

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.

Step 2 Filter

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, select the account, and click the Refresh Accounts List button. 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.


Standardize Data in Bulk with the Transform Data Module

With the Transform Data module, you can standardize job titles, industries, locations, and any free-text field in your CRM in bulk.

Process Summary

  1. Set filter criteria.
  2. Select records to update.
  3. Pick fields to modify and set standardization rules.
  4. Preview the changes. 
  5. Apply the standardization changes to the CRM records.


Step-By-Step Instructions

Step 1: Find Records That Need Cleanup

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.


Step 2: Set the Changes to Make on Field Data

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


Step 3: Preview Changes and Update CRM Records

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 for each field.


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.


Standardize Data from a CSV with the Magical Import Module

With the Magical Import module, you can import a CSV file, set standardization rules for fields, then apply those changes while importing into your CRM.

Process Summary

  1. Upload the CSV file.
  2. Map the CSV columns to the CRM fields and specify how to import the values.
  3. Select the unique identifier field, and choose an action to take.
  4. Set up the formatting rules to standardize the data. 
  5. Import your formatted CSV data.


Step-by-Step Instructions

Step 1: Select the File, Map Columns, and Specify How to Import Values

Select the CSV File for Import

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 that 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.

Map CSV Columns to CRM Fields

After uploading your CSV data, Insycle analyzes your file and compares the columns in the file to fields in your CRM database.

A column is included for each field in the CSV, with the CSV Column header appearing as the top row. Then, Insycle automatically detects the matching CRM fields and maps them for you. The second row shows the mapped CRM field names.

If your CSV contains fields that are not matched to your CRM, a red exclamation point icon will show. 


These "Not Mapped" fields need to be mapped manually by clicking the dropdown and finding the appropriate CRM field. If they remain unmapped, they will not be imported. If you choose to leave these unmapped you can remove them by hovering over the column name and clicking the “X”.

Specify How to Import Values for Each Column

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


Four Import Mode Options

  • Update – Update CRM records with all non-empty field data contained in the CSV.
  • Fill – Import CSV values only when the corresponding field in your CRM is empty.
  • Overwrite – Insycle will replace any existing data in your CRM with the data in the CSV—even if the CSV field is empty.
  • Append – Import values from the CSV and append (add them to) the existing data already in your CRM. A typical example of how “Append” is used would be in a “Notes” field, or to add to existing picklist data without including historical selections in your CSV. 

You can also preview and edit the import data directly in Insycle by clicking the pencil icon next to any field when you hover over it.


If a record has errors, the red exclamation point notification will be shown on the left side of the record. When you hover over the red exclamation mark, an explanation of the error will be displayed.


Records that have errors in them will not be imported. Other fields will be imported as normal.

Step 2: Select Unique Identifier Field and Choose Action to Take

Insycle uses Identity Fields to compare your CSV to your CRM data. Identity Fields must be "unique identifiers." This is data that would only belong to a single contact, such as email addresses, phone numbers, home addresses, or ID numbers.

For example, no other contact in the database would have Maria Hernandez's email address, phone number, or ID number listed on their contact record. If a contact record contains a match for Maria Hernandez's data in one of those fields, we know that is the contact record for Maria Hernandez.

Under Step 2 on the Import tab, select the Identity Field from the dropdown.

Note that 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. 


Select one of the Record Modes 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.
Step 3: Set Up Rules to Standardize the Data

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.

Go to the Functions tab of Step 3.

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


The Industry field 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.

Expected results of Existing Text → New Text: Fintech or Tech Support → Technology

The State/Region field uses the pre-built Standardize: US States, CA Provinces function. This standardizes states with their full name like this:

  • NY→ New York
  • new york → New York

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

Step 4: Set Up Bulk Actions to Take (Optional)

For additional control over the data you import, use the options under Step 4.

Magical Import set up bulk action to take

The tabs that appear vary by CRM and object type.

  • List – Add your imported data to an existing list. Only available for HubSpot contacts.
  • Bulk Update – Update a specific field on import. For example, you could update all imported records to have the Job Title of “Founder,” regardless of the data in the CSV file.
  • AssociateAssociate contacts to companies, deals, and custom objects automatically when importing data. Select a CSV field and the CRM field you’d like to match it with to create associations. When using Salesforce, this is known as “Link.”
  • Date Format – Format dates contained within your CSV file to your preferred standard.
Step 5: Select Records and Import the Data to Your CRM

By default, Insycle will attempt to import all of your formatted CSV data into your database. You can select individual records for import in the Record Viewer. 

⚠️ Note that changes are applied to your CRM immediately; there is no preview step. To import, click the Import Contacts button under Step 5. 


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.


A record of these changes can be found anytime in the Activity Tracker.

After you've seen the results in the CRM and you are satisfied with how the operation runs, you can save all of the configurations as a template to reproduce the same formatting operation in the future. 

Pro Tip: Filtering Out Records That Don't Match

In Magical Import, under Step 3, the Filter tab allows you to filter data out of your import based on fields and conditions you set.


In the example above, the CSV data for import will be filtered down to only contacts with a job title containing the word “Founder.” Because the “contains” Condition was used, this will include records that have job titles such as “CEO and Founder,” “Co-Founder,” etc. 


My Mapped Values Aren’t Being Standardized

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.


Frequently Asked Questions

Should I create a different template for each field I want to standardize?
Yes. For organizational purposes, it is best practice to create a new template for each field that you would like to standardize.
What functions are available for standardization?
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.

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