Aaarg. You have never run a business, have you? At 45 cents per clicks, my total revenue is too small and not worth the effort. If my competitors can make a good profit while I can’t, then good for them, they are smarter, but at that point the correct decision is likely to abandon the game. If they are stupid or purposedly running campaigns with negative ROI (one way to eliminate competitors if you have deep pockets), then I exit the game and try other, more effective marketing strategy. If they are stupidly burning money, I can just wait until they are gone, then I enter at a better price. A bit like people waiting 2008 to buy a new house. Makes sense?

You’re absolutely right. And if ClickFacts provides that service, as I said before, and as ClickFacts seems to confirm, then I think that is actually valuable to the clients. Yes, I agree that that is valuable.

The thing is, figuring out which keywords are best and at which times, etc, doesn’t really need to identify what is “click fraud” per se to be useful. For example, in analysis you might discover that clicks during 12pm EST don’t convert into sales (or w/e makes the real dough on your site). Or your analysis shows that clicks that you pay for for the keyword “platypus” don’t convert into sales either. It doesn’t really matter if the clicks are “click fraud” or if the clicks are simply legitimate users who don’t find your content interesting at that time of day/search term.

All that matters is, I’m paying $3/click, and 10 clicks/sale, $1/ sale, means costs > benefits, gotta change my strategy. This analysis is what you Should Be Doing(R) even if click fraud were 0%. I’ll repeat, even if Click Fraud were actually 0% you would still act exactly the same way. It’s the basic idea of, looking at how much actual real net profit you make as a ratio of clicks over all possible dimensions (time, keyword, website, etc.).

Now, my final point, and I’m done, is that this kind of analysis is not necessarily easy, especially with a large number of terms. Yes, the auction should ensure that nobody underpays, but the advertisers must accurately measure the utility of every click. That can be hard, as I said.

ClickFacts said above that they do this analysis for clients. That’s valuable. I’m glad that ClickFacts does this.

For simplicity, let’s assume the break-even of $.50 includes “normal profit”, that’s an economic term, look it up if you don’t know it: http://en.wikip...org/wiki/Profit .

If you bid less than $.50, say, $.40, then someone else, who sells the exact same thing as you do (this is the Internet, right?) will pay $.41 and place above you. In fact, someone will even pay more than him, and more than him…… until the auction goes up to your break-even of $.50. If you’re not willing to pay more than the $.40 (you should though since your break-even with normal profit is $.50), then you’re booted off of adwords since others are willing to pay that much.

Now, the real world doesn’t have such exact value metrics where we have infinite competitors with identical utility. Nevertheless, there are a lot, and they are spread out on a continuum. This ensures that the valuable top adwords space goes to those who value it most, and they pay Google as much as that space is worth (otherwise, someone will swoop in — remember that, subject to small second price differences of course). You can go look up more auction theory if you want to learn why.

It’s only cheating if there’s collusion. Otherwise, everyone wins.

Wrong argument. If your break-even point is at 50 cents per click, it means you lose money when you pay 51 cents per click. However you make money when you pay 49 cents per click. Now if your profit per click is 0.5 cents per click when you pay 49 cents per click, it could be around 9.5 cents per click when you pay 40 cents per click, and around 39.5 cents per click when you pay 10 cents per click.

If you get 1000 clicks when you pay 49 cents/click, 500 clicks when you pay 40 cents per click, and 10 clicks when you pay 10 cents per click, your TOTAL profit is:

negative if above 50 cents per click
$0.00 at 50 cents per click
$5.00 at 49 cents per click
$47.50 at 40 cents per click
$3.95 at 10 cents per click

Even if you take into account that cheaper clicks have lower conversion rates, you’ll still see an optimum bid somewhere between 10 cents and 49 cents per click. And bidding above the optimum might increase your ROI but decrease your total revenue. And of course, bidding above the break-even point (50 cents in this example) will lead you to bankruptcy.

This is exactly what is going on with bad clicks. As an advertiser, I hope I can pick up the good clicks cheaply and leave bad ones to less savvy competitors. For instance, I eliminate sources of bad traffic (sometimes difficult to detect, e.g. low frequency botnets) using Google levers. Indeed, my main competitor is spending 5x more money on PPC, and gets less than me (I get more for much cheaper in part because I’ve bought 50 times more keywords, efficient keywords in terms of return, but also I know better how to optimize campaigns and eliminate fraud).

Clearly, ClickFraud is not low and unimportant, and we do provide all sorts of Advertiser Analytics in addition to ferreting out ClickFraud. ClickFraud was emphasized in this thread as that’s the context of the Techcrunch post. Nonetheless, if you look it strictly from an economic basis (and yes, I did major in Economics), ClickFraud generates money for the search engines and ad networks (and there are many in addition to Google), distributing it away from legitimate advertisers, and by crunching the data with our proprietary tests, we can clearly patterns of traffic which are not beneficial (and in some cases are fraudulent), which can successfully be worked around, thus increasing the advertisers’ ROI.

As you say, “There’s money on the table, so someone will obviously take it.” But the conclusion that folks taking money through ClickFraud is “balanced fairness, it’s perfect” only works if you’re on the side of the fraudsters.

Basically, simplifying for effect, you’re paying Google X dollars a month to be in position Y. If you pay less than X, then your position will be lower than Y or even dropped, which means that you get (more or less) proportionately fewer clicks/actions. If you try to “cheat”, you pay less, your position goes down, you get fewer actions, which means less revenue/profit. You pay less, you get less revenue. Then you just try to figure out how much you pay to maximize profit, not to minimize costs. Perfect. The auction ensures that you maximize utility not only for yourself, but for Google, and the economic systems!

Now, proof of no collusion: 1. It is difficult to collude considering the wide swath of people around the world who advertise on Google. 2. even if somehow somebody got every advertiser in the world colluding on a single message board, there would be a strong incentive to cheat since if you pay a penny more then you would get on the top of Google ads, then everyone else would cheat, and you’d get back to paying the max real value you’re willing to pay.

Economics should be mandatory. The great thing about auctions is that there is no flawed theories about mass social interaction to screw it up. It’s just: there’s money on the table, so someone will obviously take it. This leads to balanced fairness, it’s perfect.

I feel bad for you. You work at the company, so I know that there is no chance of convincing you. The cognitive dissonance is too great. I write the following for others who might otherwise pay you for snakeoil:

Of course different industry, keywords, etc. get different amounts of click fraud. But, for any one term, everyone bidding in the auction for that term is going to be bidding for the same value of a click. So, “mortgage” click fraud might be 50% because people who run sites where mortgage ads run get paid big bucks for clicking on their own ads. That means, every advertiser will pay 50% lower for that keyword. They might also run ads on the keyword “pottery”, which has just 1% click fraud. So, they’ll pay almost full value for every click.

The auction is Google’s brilliance. It literally means that you cannot overpay. (It also means that you cannot underpay!)

Back to ClickFacts. Instead of measuring clickfraud, which is low and unimportant, you should provide other metrics that will be useful for the clients. Specifically, you can gather data about click-throughs, amount of time staying on the site, etc, combine that with the estimated value of all these actions, and generate a recommended bid for the clients. Doing so correctly, and in a statistically coherent way, is not necessarily easy for most clients. The client wants to focus on her product, not auction theory and statistics.

I wish TechCrunch would practice a bit of due diligence and stop covering turds like this.

Really? And how did you come to that conclusion?

As for the statistic minded post before that, what he says would have more validity if ClickFraud were entirely balanced. It is clearly not true that “Every advertiser gets equally distributed click fraud”. ClickFraud varies widely by industry, advertiser, type of ad buy, and other factors. And ClickFacts’ focus is on the largest advertisers, those that suffer from the greatest amount of fraud.

Since different advertisers, publishers, keywords, and networks have different levels of fraud attached, by using ClickFacts’ services, you can take proactive actions to reduce fraud before it continues to occur, thus dramatically improving your company’s ROI.

All these click-fraud companies are praying on fear.