workingwithdata_ebook_april21_awc2op 4
TREATING DATA AS A PRODUCTUNENFORCED EVENT DICTIONARIESThe status quo: unenforced event dictionariesTo explore why these two issues occur, it’s important to look at how mostcompanies implement tracking. Often, an unenforced event dictionarycreated by the tracking designer is at the center of the trackingimplementation.For this to work well, the creator/owner of the unenforced event dictionarymust clearly communicate the design intent. For example, that a searchevent should fire with these properties on search results being displayed –rather than the search button being clicked. The design intent must bemade clear to both key stakeholders: the front-end developers and thedata consumers.33
TREATING DATA AS A PRODUCTThis approach does sometimes work, particularly when the dictionary owneris invested in its long term success, perhaps as one of the data consumers.However, the dictionary is often created by a specialist consultant andongoing ownership is unclear.This results in long Slack threads with both sets of stakeholders asking whatrows in the sprawling event dictionary mean:1 Devs can’t interpret the event dictionary and their goals and incentivesoften don’t line up with ensuring tracking matches intent exactly,instead they are focused on getting “good-enough” live on time.2 Data consumers either can’t interpret the event dictionary oraren’t sure if the values loading in the database match the datadictionary intent.34
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TREATING DATA AS A PRODUCT
This approach does sometimes work, particularly when the dictionary owner
is invested in its long term success, perhaps as one of the data consumers.
However, the dictionary is often created by a specialist consultant and
ongoing ownership is unclear.
This results in long Slack threads with both sets of stakeholders asking what
rows in the sprawling event dictionary mean:
1 Devs can’t interpret the event dictionary and their goals and incentives
often don’t line up with ensuring tracking matches intent exactly,
instead they are focused on getting “good-enough” live on time.
2 Data consumers either can’t interpret the event dictionary or
aren’t sure if the values loading in the database match the data
dictionary intent.
34
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