But the experiments you run pit one ad type or channel against another. Have you ever run any experiments comparing ads to no ads?

Absolutely. You can give a campaign its own website or URL if you want to test something like the effect of a specific billboard or radio ad.

Or you can do the equivalent of an excess mortality study but for client acquisition or product sales. You take something like the month of January and you say "this is what we expect for web traffic given our standard traffic for that month, and extrapolate it with your average web activity growth". And so long as you have "clean" months to compare it to (with no ads running), you can get a pretty decent back of envelope about what your ad campaign did.

Like, there's so many different ways you can cut the apple, it's patently ridiculous they made those claims.

To give them a bit of credit, there's something to be said for there being a lot of bad ad spending out there. But like the stock market, there's a tacit understanding that it's more or less efficient.

I have. When I run ads, I grow. When I stop running ads, I don’t.

  PPC you only pay if the user actually engaged with the ad

Who defines that "engagement" legitimately occurred? The ad network.

Example: TVguide.com/listings. On most devices, I get a nondismissable audio ad when I'm looking at telecast schedules. I kill the audio immediately.

I never experience the bulk of the ad, and even if I can identify the product being advertised, I'll form a strongly negative impression of them.

I don't count this as "engagement", but it's charged as that.

since you work in the industry - how about your opinion on the Uber case in the original post? that is PPC.

I'm struggling to follow the actual narrative presented in the chopped up Twitter style. It sounds like there were was a third party ad network involved?

One thing we learned a long time ago is never to trust "engagement" data from platforms (be it Google, Facebook, LinkedIn, whatever). There are enough random user behaviors that you generate a ton of noise. You need to build larger, more robust attribution models that tie ad spending directly to revenue sources - new leads, new accounts, purchases, etc. Patting yourself on the back for how many shares or clicks you get is not great.

as a nonexpert its hard for me to say too but perhaps you will benefit from hearing directly from source - the performance marketing guy at Uber who found all this out: https://www.marketingtodaypodcast.com/194-historic-ad-fraud-... honestly i am not sure if he did a good thing by asking all these questions, or was partially to blame for gross incompetence managing a 150mm ad budget, or both. (the chronology of when exactly he took over matters, it seems he was only in the job about a year)

and of course for more detail the full text of the fraud suit is public https://www.adexchanger.com/wp-content/uploads/2019/06/Uberf...