Product: MergeOmatic
Description: This solution describes the duplicate criteria
Environment: All
Version: All
Answer:
Omatic Software has nearly a decade of experience in matching records in Raisers Edge. With that experience we've developed a sophisticated algorithm to evaluate whether records are possible duplicates. We wanted to allow users the flexibility to adjust and make their own refinements in MergeOmatic.
There are four different parts of the matching and duplicate criteria that can be adjusted:
Duplicate Criteria
You can determine what information is considered in the duplicate matching process:
Option to look for non-constituent records as potential duplicates
Option to use name variations for duplicate searching (example: Robert, Bob, Bobby, Rob, Robby, etc would be treated as duplicates)
Option to compare specific address types beyond the Preferred Address
Survivor Record
You can assign priority to what information should be considered when determining which record should be deemed the “Survivor”. The Survivor Score determines which record “survives” the merge as the other record is removed.
Assign points (weighting) based on which record was added first, added last or modified last
Assign points to different types of records to be considered: constituent, address, gifts, event registrations, memberships or highest total giving
Assign points based on any criteria that is important to your organization through the use of Queries (example: constituent codes)
Similarity Score
MergeOmatic finds potential duplicates based on a similarity score – the higher the score, the more likely the records are duplicates.
You can adjust the factors that are considered in the calculation of the similarity score (examples: first initial, first name, nickname, maiden name, suffix, gender, etc) when there are differences between the duplicate records.
You can also assign different priority or weighting to various fields. For example, matching email addresses has a much larger impact on whether records are considered duplicates than matching ZIP codes would, so email is given a larger weight than ZIP code. You can adjust the priority so that it is specific to your organization’s needs.
Processing
You can control the similarity score threshold for processing duplicates. The higher the threshold is set, the more accurate potential duplicates will be returned.
For additional information, please refer to the MergeOmatic User Guide.
Description: This solution describes the duplicate criteria
Environment: All
Version: All
Answer:
Omatic Software has nearly a decade of experience in matching records in Raisers Edge. With that experience we've developed a sophisticated algorithm to evaluate whether records are possible duplicates. We wanted to allow users the flexibility to adjust and make their own refinements in MergeOmatic.
There are four different parts of the matching and duplicate criteria that can be adjusted:
Duplicate Criteria
You can determine what information is considered in the duplicate matching process:
Option to look for non-constituent records as potential duplicates
Option to use name variations for duplicate searching (example: Robert, Bob, Bobby, Rob, Robby, etc would be treated as duplicates)
Option to compare specific address types beyond the Preferred Address
Survivor Record
You can assign priority to what information should be considered when determining which record should be deemed the “Survivor”. The Survivor Score determines which record “survives” the merge as the other record is removed.
Assign points (weighting) based on which record was added first, added last or modified last
Assign points to different types of records to be considered: constituent, address, gifts, event registrations, memberships or highest total giving
Assign points based on any criteria that is important to your organization through the use of Queries (example: constituent codes)
Similarity Score
MergeOmatic finds potential duplicates based on a similarity score – the higher the score, the more likely the records are duplicates.
You can adjust the factors that are considered in the calculation of the similarity score (examples: first initial, first name, nickname, maiden name, suffix, gender, etc) when there are differences between the duplicate records.
You can also assign different priority or weighting to various fields. For example, matching email addresses has a much larger impact on whether records are considered duplicates than matching ZIP codes would, so email is given a larger weight than ZIP code. You can adjust the priority so that it is specific to your organization’s needs.
Processing
You can control the similarity score threshold for processing duplicates. The higher the threshold is set, the more accurate potential duplicates will be returned.
For additional information, please refer to the MergeOmatic User Guide.