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I'd bet just about anything that Google uses machine learning to decide whether or not to trust a site for ads. It seems like the only solution that would work at a large enough scale to handle that kind of demand (versus more defined but more labor- and resource-intensive malware/fraud detections). I think that also explains why the review process seems so arbitrary and ineffective - in essence, not even Google knows why Google decided your site was bad. I used to help people with hacked websites, but eventually I had to refuse to work on projects where the only symptom was a Google Ads denial because it was such nonsense. In one case a guy completely removed his site and replaced it with a 0-byte page, and even after we saw Google-owned IP addresses doing a crawl in the site access logs, they still told him there was malware (including a list of infected URLs that no longer existed).

If I'm correct, changing your domain might help in that machine learning algorithms consume tons of signals and maybe altering that particular one would push your site under the "bad" threshold. But it might not do anything. It's a super frustrating problem. I hope you can stumble onto a solution or find someone at Google willing to help.




> It seems like the only solution that would work at a large enough scale to handle that kind of demand

It doesn’t work. These automated systems are flagging a (presumably) benign site and an article yesterday regarding their $5M lawsuit for running a scam ad on their SERP for “Coinbase support” suggest the automated systems can be bypassed too.

I’m not saying automated detection can’t be a part of it, but we shouldn’t accept companies automating away decision making as if computer-derived errors are acceptable.

The larger point is that Google isn’t exactly strapped for cash. They could hire an army of reviewers. They just don’t.


Point taken; it "works" for certain values of "work."

> They could hire an army of reviewers. They just don’t.

They may actually do that too, but perhaps there are thresholds that must be met for something to reach a reviewer. I have some sympathy for Google here as I work on email security in a high-volume environment. ML is one tool in the box, and human reviewers are another. Everything is a tradeoff between resources, false positives, and false negatives.

At least my organization's customers can contact support if something is going wrong, but for people trying to legitimately use Google Ads, it can be an extremely frustrating situation of shouting into the void. (And getting boilerplate support answers back from the void.)




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