Comparison Match Criteria

Overview

When setting up Comparisons in an account, Match Criteria are critical to aligning tags such that our comparison is correct and we don't have any false positives.

Match Criteria

To set up match criteria, you'll need to go to your Account Settings and select the Tags tab. From here, you can add tags by searching them in the drop down. If you have already added tags, simply click the enable tags for comparison toggle next to the tag.

Note: By default all accounts can enable up to 3 tags for comparison, most of our clients will not need more. However, if you are interested in adding more, reach out to your data governance consultant.

After enabling a tag for comparisons, click the click to expand it and select Comparison Configuration. From here you can add variables to exclude from comparisons and variables use to match comparable tags.

Note: Exclusions can be configured here, but you can also exclude variables in the report.

Recommended Variables for Matching

Not all variables make for good match criteria. If you assign the wrong variables, it could results in false positives in your comparison report.

Match criteria we recommend you choose include  variables that have consistent values between runs, that are unique between tags.

Example: Here we set pev1 and pev2 as match criteria for the Adobe Analytics tag. You can see 3 Adobe Analytics tags were picked up.

If you hover over the fields in the Comparison Results column, you will see a tool tip revealing how the match criteria we selected distinguished the tags from each other. All of which had at least 1 unique value between the variables we chose and we expect the values to be consistent run to run. Where pev1 and pev2 are equal to null, that is a page load tag, and where pev1 and pev2 have unique values, those are different event based tags.

This table shows recommended match criteria variables for the most popular tags to compare:

Technology Recommended Variables to Match Tags
Adobe Analytics pev1, pev2
Google Universal Analytics t, ea, el, ec
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