How to Find and Remove Inactive Fields, Moving Data into Active Fields
In your CRM, various contributors have been using the same field differently, or have created new fields specific to their needs. You have a strong sense that there are extraneous and outdated fields, but you aren't sure which those are, and trying to manually sort through them in the CRM has been time-consuming.
Insycle simplifies the process of identifying and retiring legacy fields and merging relevant data into the correct field with a powerful combination of the Cleanse Data and Transform Data modules.
First, use the Cleanse Data module to:
- Export and review field properties, looking for inactive or redundant fields.
- Explore values in each field and decide how to clean up.
Then, use the Transform Data module to:
- Copy or move relevant data from your legacy field to your active field.
- Delete non-relevant legacy fields to reduce clutter.
Identify Legacy Fields to Retire with the Cleanse Data Module
The Cleanse Data module gives you a full top-down view of your data, including in-depth field metadata and the data each field contains.
In the Cleanse Data module, select the record type from the top menu.
To get a full picture of all the existing fields you have, click the Export button in Step 1.
This will generate a CSV file with properties for all of the fields currently in your database. The CSV helps you identify outdated and unused legacy fields quickly and easily. Learn more about interpreting these properties in the Pro Tip: Understanding Field Properties below.
All fields, not just those that seem unused or unimportant, need to be examined to ensure they are being used correctly. Then you can explore the field data to decide if it needs to be merged or can be deleted outright to remove clutter and improve organization.
Once you've identified a field that calls for further analysis, select the Field Name from the dropdown under Step 2. (This does the same thing as checking the box by the field name in Step 1.)
Once selected, the different values found in this field will populate the Record Viewer at the bottom of the page. The Count reflects the number of times a value is used.
Explore the different field values to identify inconsistent or irrelevant data and identify what needs cleanup. Use the checkbox to expand a value set.
This opens up a secondary Viewer below the first, where you can review the individual records that have the selected value.
To see more information for each of the resulting records, you can alter the columns included in this Record Viewer by using the Layout tab in Step 2.
Filter Out Records That Don’t Need Changing
When you're looking to fix specific values, use the filter to work only with an appropriate subset of your data. You can filter your data using any field in your database.
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.
Filtering is a critical feature for examining and identifying legacy fields. For instance, you could filter your fields by a specific amount of time using the "Create Date" field, such as records that have been created in the last six months.
Or you could filter by fields like "Last Activity Date," and set a date to surface fields that haven't had any activity in a long time.
Click the Search button and the Record Viewer at the bottom of the page will be updated.
Understanding how to interpret the information about each field can provide clues on issues and highlight possible data-cleansing tasks.
Field Label vs. Name
The Field Label is shown in the CRM interface while the Name is the column header in the backend database.
If there are two fields with a similar Field Label, such as "Phone" versus "Phone Number," looking at the underlying field Name may reveal different information that clarifies the actual purpose. You may want to update one of the Field Labels to reflect the difference.
Type, Value, and Writable
- Type – Field type, such as a picklist, number, text string, date, timestamp, true/false (boolean), etc.
- Value – Describes the type of data stored in the field such as text, number, date, true/false, etc.
- Writable – A checked/TRUE value indicates the field can be edited.
Unique Values (Distinct)
This is the count of different values that appear in this field across all records. This is a great place to look and see if there is data worth exploring. You could answer a question such as, "How many different job titles do we have?" It can also indicate a problem in fields where only a few values should be used, such as Industry, or Product fields. This is especially relevant on fields that should be limited to a picklist, or Yes/No values.
This is the number of records that don't have any value in the field.
Any field with a high number of Empty Values could indicate the field is unused or abandoned and needs cleanup. If there are 1000 records in your CRM and 950 don't have a value, this could indicate an abandoned or underused field.
Or, it could indicate a syncing issue between Insycle and your CRM. If you see field data in your CRM but the Empty Values number is high, contact Insycle support.
There are a few things to look into,
- Under Step 2 in the Filter tab, make sure that you have clicked the Search button.
- 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.
If you don't see data in the relevant field in Insycle, but the field contains data in your CRM, it is likely a field syncing issue. In this case, contact support through live chat to request a manual sync for the field.
Deciding What Data Needs to be Moved
The field export CSV will help you identify active, inactive, or redundant fields. By looking at the values that appear in the fields using the Record Viewer, you can decide which fields are the right ones to keep, and which to retire.
For each field you want to remove, you have to decide whether to delete the field outright (because it doesn't contain any usable data) or move the data to the appropriate, active fields.
Move Data from Legacy Fields to Active Fields with the Transform Data Module
Using the Transform Data module, you can easily copy or move data from legacy fields into an active or new field.
For this example, let's say you want to retire the Mobile Phone Number field and instead use one single Phone Number field.
Navigate to the Transform Data module and in the top menu, make sure you have the right record type selected; for this example, select Contacts.
Under Step 1, configure the Filter to look for contact records that HAVE a Mobile Phone Number value, but do NOT HAVE a Phone Number field value. This way, if a record already has a phone number, it won't be overwritten.
If it makes more sense to overwrite existing data in the Phone Number field, remove the "Phone Number doesn't exist" filter row.
Click the Search button, and a preview of the records that match this filter will load in the Record Viewer at the bottom of the page.
Under Step 2, set up the Function to Move the Mobile Phone Number field data into the Phone Number field. This will apply to all records that matched the filter set in Step 1.
- The Move function takes your data from one field and moves it to another, deleting the data in the source field. When retiring legacy fields, you'll most likely use the Move function and then delete the empty field from the CRM.
- The Copy function copies the data and duplicates it in another field, leaving the data in the source field. If there is a situation where you want the data in a new field, but also want it to remain in the legacy field for archiving or other purposes, you could use Copy.
You may also want to do some cleanup on the value while it is being moved.
Preview Changes in the CSV Report
With the filters and functions set up, you can preview the changes in a CSV file. It's important to verify that your formatting is working as expected before those changes are pushed to your live database.
Under Step 3, click the Review button, then select Preview in the popup.
On the Notify tab, you can select recipients for the emailed CSV report and add additional context to the message. (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 (in most cases this will be All), 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. If the results don't look the way you expected, go back to your filters and functions and try making some adjustments before previewing 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 When tab, you should use Run Now the first time you apply these changes to the CRM.
Once you've moved data from your legacy, Mobile Phone Number field to your active, Phone Number field, you can delete the Mobile Phone Number field from your CRM.
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.
There are quite a few default templates that can be used to format phone numbers. A few popular ones are:
Format Phone Number E. 164
Formats phone numbers to the E. 164 international standard
Format Phone Number US (xxx) xxx-xxxx
Formats USA phone numbers to the (xxx) xxx-xxxx standard
Format Phone Number US +1 (xxx) xxx-xxxx
Formats USA phone numbers to the 1+ (xxx) xxx-xxxx standard
See our blog article on Phone Number Formatting for more.
Tips for Filtering Records
While you can run the Cleanse Data or Transform Data modules without filtering your data, this means Insycle will analyze your entire database. This can cause unnecessary work for the system and be quite slow. Set up the filter to focus only on a relevant segment of records.
You may also want to use a more specific filter if there are a large number of results, slowing you down while you work to get the configuration right. Add a filter to work with a reasonably sized subset until you're ready to apply it to all the results.
Related Help Articles
- Copy or Move Values Between Fields
- Cleanse Data
- Bulk Update Values of Any Field
- Bulk Clear Values from Field
- Map values from one field to another
Related Blog Articles
- Declutter Your CRM By Purging Low-Quality Data Automatically
- Why Effective Customer Segmentation is Critical for Driving Growth
- 5 Steps for CRM Data Standardization
- 6 Critical Reasons to Normalize Data
- How to Become a Customer Data Wizard Using the ‘Transform Data’ Tool
- How to Create a Customer Data Management Plan