Google-backed groups criticize Apple's new warnings on user tracking

Re:Google-backed groups criticize Apple's new warnings on us... by mlthoughts2018 on Friday July 03, 2020 @01:43PM (#23725910)

Perhaps for a simpler example: imagine you start an ad campaign on the same exact day the government issues a huge stimulus check. You see a big increase of sales. Is it because the ad did a good job of causally impacting people to choose your brand? Or is it because the world changed underneath your feet and suddenly lots of people with pre-existing demand had more money? Maybe your ad even had a negative effect because more people were willing to spend the stimulus check on your product, but they were turned off by the ad - so your revenue went way up but the ad actually lost you money.

This is about the simplest type of confounding example you’ll see - real world ad attribution is far messier, with 10 or 15 of these issues all intermixing, some of which you have measured data to possibly use as a control, some of which you don’t.

Your client might not even have done any control group at all. They might just say, “we sent this ad to absolutely everyone, how did it perform compared to a hypothetical where we didn’t send it at all?”

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Re:Google-backed groups criticize Apple's new warnings on us... by tareqak on Friday July 03, 2020 @02:04PM (#23726104)

I see what you are saying: that there are too many confounding variables involved and it is not as simple as A implies B. I’d then argue the same thing about attribution then though: a company like Google or Facebook might be measuring many variables for a given user across however many surfaces they can possibly reach, but some set of offline variables that are invisible / unknowable from their vantage point might be the actual cause of a given conversion. If this is indeed the case, then measuring aggregate advertising metrics should be sufficient enough to inform ad spend in the long run.

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