Unified Scores table

The Unified Scores table records all of the pairwise comparison scores and match categories for all groups of records, and then for each group of records all of the pairwise scores that are present between records within that group.

The Unified Scores table is added to databases in the Customer 360 page when:

  1. The Stitch QA database is added using the “Stitch QA” database template.

  2. A customer 360 database is added using the “Customer 360” database template.

  3. A table is added to a custom database using the Unified Scores table as a passthrough table.

Use with Stitch QA

The Unified Scores table is the foundation for the Detailed Examples table in the Stitch QA database, which is the starting point for any quality review of Stitch output and is an important part of the Stitch QA workflow.

Use with Customer 360

The Unified Scores table enables using the Amperity ID to discover information about how groups of records were scored and to verify those scores against other data points.


The Unified Scores table should not be used outside of the Customer 360 page. It should not be used to build queries or segments or be configured to send data to downstream workflows.

Column reference

The Unified Scores table contains the following columns:

Column Name

Data type



Amperity ID


The unique identifier that is assigned to clusters of customer records that all represent the same individual. The Amperity ID does not replace primary and foreign keys, but exists alongside them within unified profiles.


The Amperity ID is a universally unique identifier (UUID) that is represented by 36 characters spread across five groups separated by hyphens: 8-4-4-4-12.

For example:












A score contains a value from 0.0 to 5.0 that represents the combined score assigned to the record pair by Stitch. There are two components of the score: the score itself, and then its strength.

The record pair score correlates to the match category, which is a classifier that is applied by Amperity to individual record pairs. The record pair score corresponds to the classification: 5 for exact matches, 4 for excellent matches, 3 for high matches, 2 for moderate matches, 1 for weak matches, and 0 for no matches.

The record pair strength represents the strength of the record pair score. It is a two digit number. For example: .31 is a lower strength and .93 is a very high strength.


Scores are shown for records that end up in the same cluster, including any scores that are below threshold. Scores are not shown for records that do not end up in the same cluster.

Also in: Detailed Examples

Match Category


A match category is a classifier that is applied by Amperity to an individual record-pair within a cluster of record-pairs. The match category is the result of this classification.

Match Category



Amperity has the highest confidence that these records represent the same person because all profile data exactly matches.


Amperity has near perfect confidence that these records belong to the same person, despite select types of profile data not matching.


Using deductive reasoning, Amperity has very high confidence that these records match, despite some profile data not matching.


Amperity has moderate confidence that these records match, due to weak or fuzzy matches between highly unique customer attributes (email, phone, address).


Amperity lacks confidence, but if asked to guess, Amperity would assert these records do belong to the same individual, because they match on non-unique customer attributes (name, state, zip code).

No conflict

Amperity has high confidence that these records do NOT match, because core profile data is in conflict.

Also in: Detailed Examples

Match Type


The type of score being applied. Possible values are as follows: “scored”, “scored_transitive”, and “trivial_duplicate”.

A match is assigned “scored_transitive” when that match was not identified during blocking. For example: three records (A, B, and C). If records A and B and records B and C were identified as matching during blocking, all three records will end up in the same group of records for pairwise comparison. Records A and C have a transitive connection.