Data Flow Diagram and Field Mapping

Data Flow Diagram

You can import external data to your Organizer account in the form of CSV files. This data includes profile data about individuals and data from outreach efforts such as a phone bank or text message bank. 

Profile Data

When you import profile data to your Organizer account, the system attempts to match your imported data to existing records in the database. This includes existing Atlas by Murmuration data, records from a previous data import, or profiles created via scripts or forms. This is a process called “matching.” For more information on “matching,” please review the help center article on matching logic and minimum and recommended source mapping.

Any additional data you may want to import that is unique to your Organization can be imported as a custom attribute field. You can connect with your Partner Success Manager and Data Success Manager on the best method for importing custom data.

Basic Diagram


 

Outreach Data

You can import the results of Phone Bank or Text Bank outreach interactions from third-party tools directly into Organizer. Once the data is imported, you can use the data for reporting and continuing outreach efforts. Once your data is imported, phone outreach can be used for filtering in Community Builder and is listed in the outreach tab of a single profile.

For more information on importing outreach data, please see the following help center articles:

• Importing phone interactions
• Importing text interactions

Field Mapping Checklist

When gathering and preparing data for import, you should include as much of the following contact information as possible to increase match likelihood.

• First Name
• Last Name
• Zip Code
• State
• Email Address
• Phone Number
• Address
  • Separated out by Address 1, Address 2, City, and County
• Date of Birth
• External ID (if applicable)

You may create a chart like the one below as a checklist as you gather contact information for import.

Data Field	Accepted Formats	Notes	Available to be Imported? Yes, No, Unsure
First Name	Open Text plus hyphens and apostrophes*	*In some cases, apostrophes or hyphens are allowed in specific fields; apostrophes should be formatted as “straight” or “plain” and avoid “smart” or “curly” apostrophes.
Last Name	Open Text plus hyphens and apostrophes*	*In some cases, apostrophes or hyphens are allowed in specific fields; apostrophes should be formatted as “straight” or “plain” and avoid “smart” or “curly” apostrophes.
Zip Code	Five-digit number
State	US State Abbreviation (e.g., PA, NJ, TX)
Email Address	exampleemail@domain
Phone Number	Up to 13 digits
Address 1	Open text
Address 2	Open text
City	Open text
County	Open text
Date of Birth	Any of the following formats: MM/DD/YYYY MM/DD/YY YYYY-MM-DD MM-DD-YYYY Mon DD, YYYY (e.g., Feb 2, 2025) Month DD, YYYY (e.g., February 2, 2025)

For the full list of attributes and valid formatting, see the help center article on preparing your profile data for import.

Deduplication Rules

There are two parallel processes that Organizer goes through when a partner record is ingested into Organizer, either via import or script/form. This includes customer deduplication and entity resolution. The platform uses profile data like name, phone number, email address, physical address, and date of birth to match profiles.

Profile Deduplication

This process has a threshold where a certain amount of conditionals have to be met to match profiles to each other. In this process Organizer goes through the following steps:
 

1. Identifies potential matches
2. First+Last Name+one of phone, email, address 1 (city/county/zip code)
3. Tests the potential matches
   • If three discrepancies are found, the records will not merge
   • If the middle name or suffix exists and they are different
   • If Address 2 or State exists, and they are different
4. This process does not re-evaluate matches

Example match: The system sees two records ingested into the system—one from a partner data import, and another from an external form. The records have the following information:

Since Record 1 and Record 2 match on first name, last name, and address, the system recognizes that this is the same person and creates a deduplicated record with all the information available from both sources.

Example non-match: The system sees two records ingested into the system—one from a partner data import and another from an external form. The records have the following information:
 

Record 1 and Record 2 match on first name and last name, but have no other identifying information in common, so the system is not confident enough to determine that these are the same person. The records will not match and will stay separate in the system.

To learn more about the matching process, please refer to the relevant help center article or ask your Partnership Success Manager

Quality Control Steps Before Organizer Account Activation

Data Managers perform several quality control checks after an Organizer account is provisioned (after Atlas data is added to the account), but before a partner begins working in the account. These checks are designed to target key data fields (including contact information, demographics, and larger civic districts) to ensure that Atlas data added to the account has not been deduplicated or otherwise altered inappropriately during the provisioning process. This is to ensure that the data is as correct and reliable as possible before you begin any organizing and advocacy work in the account. For any specific questions on quality control or account creation, please reach out to your Partnership Success Manager and/or Data Success Manager.

Resources 

View the Organizing and Advocacy Playbook as a PDF

Background Information

Advocacy Action Plan Phase-Learning 

Advocacy Action Plan Phase-Planning

Advocacy Action Plan Phase-Implementation
 
Advocacy Action Plan Phase-Execution

Advocacy Action Plan Phase-Reflection