[ww520]

Way back when I work in an ad based company, click fraud handling was under my overseeing. We caught about 20 percent of clicks as fraudulent and filtered them out before billing the ad placing vendors. It was a constant battle with the sales team to relax the rules, as any clicks filtered out cut into the sales revenue. Sometimes we got the customers on our side as they ran their own analysis on the billed click report and came back demanding refund as they found a bunch of fraudulent clicks.

[VBprogrammer]

Yeah, the incentives there are obviously misaligned. I wonder if there is a potential way of making advertising click through tracking following the "I cut the cake, you chose the slice" model.

Some countries have property taxes where you declare the value and the government retains the right to purchase the property for that value for example.

My first thought was to make the advertising cost driven by revenue on the site. But that just reverses the incentive.

[renewiltord]

People will just pull ads if the ROAS isn't there. Performance marketing teams aren't fools.

Altering data would mess with everything. Why is unverified traffic increasing? What's wrong with new marketing efforts? Marketing just requires fixed definitions. e.g. if you have 97% bots but it remains constant that's okay. I know I am spending $x to get $y conversions. I can plan over time, increase or decrease and I can plan. I won't be willing to pay as much as with 0% bots (will pay far far less) but I can set my strategy on this.

It's not that it's x% bots that is the problem. Growth team doesn't adjust strategy on percentage-bot. Growth team adjusts strategy based on return on ad spend. If 0% bots but no return, way worse than 5x ROAS with 99% bots.

[dredmorbius]

I cut / you choose works in some situations.

In others you'd want, say, auditing or independent third-party verification.

In this case, perhaps an audit involving the deliberate injection of a mix of legitimate and bot traffic to see how much of the bot traffic was accurately detected by the ad platform. Rates on total traffic could be adjusted accordingly.

This of course leads to more complications, including detection of trial interactions, see e.g., the 2010 VW diesel emissions scandal: <https://en.wikipedia.org/wiki/Volkswagen_emissions_scandal>, or current AIs which can successfully identify when they're being tested.

[dredmorbius]

On further reflection: I'd thought of raising the question of which situations cut/choose does work. Generally it seems to be where an allocation-division decision is being made, and the allocation is largely simultaneous with the division, with both parties having equal information as to value. Or so it seems to me, though I think the question's worth thinking about more thoroughly.

That's a subset of multi-party decisionmaking situations, though it's a useful one to keep in mind.

[VBprogrammer]

I vaguely remember someone winning a noble prize for economics for coming up with ways to apply cut/choose in financial transactions but I couldn't find it in a quick Google. It may have been nearly 20 years ago though.

[x0x0]

It's not that misaligned.

Basic ad ops has ad buyers buy ads from different vendors, track which converts (attribution, which has flaws, but generally is decent signal), and allocate spend via return on ad spend. So it hurts the vendor at least as much as the buyer by inflating the cost per action / damaging roas.

[dcsan]

I've seen people but cpc campaigns and only place ads that don't convert. So they get the benefit of the branding instead. I guess more modern auction algorithms factor this in