Stitch Scores table

The Stitch Scores table contains all scores generated by Stitch, including scores that are not associated with an Amperity ID. Use this table to help understand why records were not associated with an Amperity ID.

Use with Stitch QA

Use the Stitch Scores table to understand why blocking used (or did not use) a foreign key or separation key to block (or unblock) two records.

Compare records

Use a query similar to the following to compare scores for two records:

SELECT * FROM Stitch_Scores
WHERE source1 = 'Table_Name' AND pk1 = '123abc456def'
AND source2 = 'Table_Name' AND pk1 = '789ghi012jkl'

where the values of pk1 and pk2 are the Amperity IDs for the records you want to compare.

Add table

A passthrough table adds a table to the customer 360 database using an existing table without making any changes to its schema.

To add the Stitch Scores table

  1. From the Database Editor, click Add Table.

  2. Name the table “Stitch_Scores”.

  3. Set the build mode to Passthrough, and then select Stitch Scores.

  4. Hide the table from the Segment Editor by verifying that Show in VSE? is unselected.

  5. Click Activate to update the customer 360 database with your changes.

Column reference

The Stitch Scores table contains the following columns:

Column name

Data type

Description

Amperity ID1

String

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 for the first of two compared records.

Note

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:

123e4567-e89b-12d3-a456-426614174000

Amperity ID2

String

The Amperity ID for the second of two compared records.

Match Category

String

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

Description

Exact

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

Excellent

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

High

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

Moderate

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

Weak

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.

Match Type

String

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

PK1

String

PK2

String

Score

Float

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.

Source1

String

Source2

String