Best Practices For Constituent Data Entry

Small inconsistencies during data entry may impact matching scores for potential duplicates. For example, the full and incremental duplicate search processes deduct points for differences in spelling, capitalization, and punctuation. For this reason, we recommend that your organization define rules and standards for constituent data entry to prevent issues with duplicate identification. These are a few recommendations:

  • Create relationships for constituents in a family. If relationships are not configured for family members with the same last name and address, they may be misidentified as duplicates.

  • Save constituents as the correct type: Individual, Organization, Household, or Group. The full and incremental duplicate searches cannot match constituents of different types. For example, if a constituent is added twice, as an organization and an individual, the program will not identify these records as duplicates even if their names and addresses are the same. For families, create a household record and then add the individual constituents to that household.

    Note: The SSIS search processes can match constituents of different types. If you have many constituents saved as the wrong type, this may be a good reason to use the SSIS search, at least initially until you have those issues fixed and have consistent data entry procedures in place.

  • Articles: Use articles at the beginning of organization names consistently—either always or never include them. For example, “The Boys and Girls Club” and “Boys and Girls Club” are not identified as duplicates by the full or incremental duplicate search processes due to the phonetic differences of the first word. The duplicate search that runs automatically during data entry will identify “The Boys and Girls Club” and “Boys and Girls Club” as potential duplicates if those records also include a matching address, email address, or phone number. In other words, the program would prevent this duplicate from being added to the database, but will not find this match once the records are saved in the database. If you have organizations in your database that may have an article as the first word of their name, you should manually search for possible duplicates.

  • Abbreviations: The full and incremental search processes do not recognize Street, St. and ST as the same word, so if they are entered differently on matching constituents, it impacts their scores. For addresses, we recommend that you use the address abbreviations used by the U.S. Postal Service.

  • Suffixes and titles: If the constituent has a suffix or title, select it from the code table in the Suffix or Title fields. Do not enter the suffix or title as part of the first or last name.

  • Initials: If the constituent’s name includes an initial, such as Thomas E. Smith, enter the initial in its appropriate name field (in this case, Middle) and include a period. Do not combine the initial with another name, such as entering "Thomas E." in the First name field.

  • Hyphens: If a compound first name is not hyphenated, such as Mary Sue Jones, enter both parts of the first name (Mary and Sue) in the First name field.

The duplicate search that runs automatically during data entry standardizes data before it runs the matching algorithm to ensure that minor differences such as capitalization and punctuation do not prevent the program from finding matches. This duplicate search will identify matches that the full and incremental search process would miss. For more information about the matching standardization process, see Constituent Matching Algorithm.

To promote consistency during constituent data entry, use the Constituent data hygiene settings in Administration to automate data standardization. With these settings turned on, the program automatically standardizes constituent names and addresses during data entry based on rules you define. Standardization can prevent issues caused by human error because users do not have to remember the correct formats for names and addresses. For example, if a user enters "3186 WEST MAIN STREET" in the Address field, the program can automatically update that entry to "3186 W Main St" when the user moves on to the next field.

The program also uses Constituent data hygiene settings to standardize constituent data entered through manual and imported batches. This will help clean up constituent data entered online or imported from vendors that use different data formatting standards.

When using the default settings, the program formats addresses according to the standards set by the U.S. Postal Service except for capitalization. Instead of capitalizing all letters in addresses, the program title cases most words and removes punctuation. For names, the program capitalizes the first letter of every word. It then lowercases all subsequent letters with some exceptions. For detailed information about the Constituent data hygiene settings, see Constituent data hygiene.