data-diamonds-1.jpg

Identifying incomplete records is critical for data enrichment and purging useless data. Your teams need context for contacts, companies, and deals. Incomplete records rob them of that context and require them to undergo time-consuming manual processes to find the missing data. It also makes your database less filterable and reportable.

Insycle makes it easy to identify incomplete records for updating, enriching, and purging.

With Insycle's Data Validation module, you can identify records that are missing specific fields in just a few clicks.

Process Summary

  1. Analyze incomplete data in the Health Assessment.
  2. Identify incomplete records with specific missing fields.
  3. Use the analysis for purging low-value data or enrichment..

Which Module to Use When

The Customer Data Health Assessment tracks some basic categories of missing data, and can serve as an excellent starting point for analyzing missing data. Look to the Incomplete Data section to identify records that are missing key fields across several record types. 

The Data Validation module allows you to search for records missing specific fields. For instance, you could search for all Contact records missing the Industry field. Then you can export a CSV that can be fed into your data enrichment tools. 

Step 1: Identify Incomplete Records

Your best tool for quickly identifying incomplete records is your Customer Data Health Assessment.

The Customer Data Health Assessment tracks common data issues in your CRM. It comes pre-loaded with templates tracking many of the most common issues. You can also load your custom templates into the Health Assessment to track data issues, including critical missing field data, that are unique to your organization.

You can click on the linked categories on this list or simply scroll down the page. One of these categories is the Incomplete Data category.

The Incomplete Data category comes pre-loaded with templates for identifying records that are missing data in many common fields for Companies, Contacts, and Deals.

By clicking the "Fix" button, you'll be taken to the Data Validation module with the template already loaded for identifying records with incomplete data for your selected field.

Now let's look at how identifying incomplete records in the Data Validation module works, step-by-step.

Step 2: Find Incomplete Records By Field

To identify incomplete records, use the Data Validation module. Navigate there.

First, select the record type—contacts, companies, deals, or comparable record type in your CRM—so that you can purge or enrich records missing critical data. This is set at the top of every module screen. In our example, we will select contacts.

Then select the Incomplete tab.

Tell Insycle what fields to use when looking for missing data. In the example above, the template is looking for contact records that are missing either First Name and Last Name.

You can select any field from your CRM in this step.

With your fields selected, click Analyze, and the Record Viewer at the bottom of the page will be automatically updated. You can also force an update by clicking the Analyze button.

 

You can export these records at any time by clicking the Export button. This will generate a CSV that you can use for reporting, or for data enrichment processes. 

Additionally, you can update records directly on the Data Validation screen by hovering over a record's data field in the Record Viewer and clicking the Edit Button.

Clicking the pencil Edit button will bring up a text box, allowing you to update data in that selected field.

Additional Resources

Related Blog Articles

Related Help Articles

Additional Resources