Sudden DCMA from adsense

Sudden DCMA from adsense
So today i recieved a letter from adsense that my site violated someones DCMA.
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Actually i recieved 2 of those emails about different autoblogs.

So i shut the sites down, emailed google that gues posters put those articles up. And now im hoping i will not get banned from adsense, because these sites didnt earn half as much as other ones.

2 question:
Why do people start sending me these? I have never before recieved any such email. Also i scrape aricles from ezine, so they must've placed them there in the first place.
The other DCMA infridgement is for me using a YOUTUBE Video.
Youtube allows embedding of their videos. And some guys sent a DCMA to adsense that i embedded his video!!!

Will disabling the sites make google spare my account?
I think the Panda update has DMCAs flying every where.
Google only suspends serving ads to the affected pages until the issue is resolved.

Just delete the pages concerned and reply google.

No problem
Please do I really need to reply google and if yes how?
As I hope this post has made clear, to be a PPC superhero, you need to choose your battles wisely. Optimize with discretion, folks.

You’re Doing PPC Ad Tests Wrong – This Script Will Help
Smart recommendations to make Google Ads profitable
Opteo continuously monitors Google Ads accounts for statistically significant patterns. When something comes up, Opteo suggests an improvement backed up by real data. Opteo also helps monitor performance trends, track spending & get alerts when you need them.

Ad testing can be a time-consuming part of the PPC optimization process so it’s an ideal area to address with a Google Ads script.

In this post, I’m sharing a script that helps with the tedious task of preparing data about what historical ad texts have worked well and may be worth deploying in more ad groups.

The script splits all ads into their component parts like headlines and descriptions and totals up the metrics from across the account.

If the premise of this script sounds familiar, it’s because I’ve shared other iterations in the past but this one is different.

I first created this script for Optmyzr’s scripts library, and later shared a version of it called the Ad Component Report on Github.

So what’s different now and why is this latest version worth a look?

Well, I made a big change to the code that addresses a problem I’ve started hearing more about lately…

Why A/B Ad Testing Is Flawed

The problem with ad testing is that advertisers may believe it’s what’s in the ad that’s influencing performance.

But as Martin Roettgerding recently pointed out, an A/B ad test may not be reliable because the difference in text between ad variations is merely one of the many variable elements of an experiment.

The other thing that’s changing is the auctions in which the ad is being shown. And in different auctions, the users are different, the time of day is different, the device is different, and so on.

In fact, there are so many variables in play that it’s not fair to point at ad text differences as the definite reason why A/B ad tests produce winners and losers.

You’re Doing PPC Ad Tests Wrong – This Script Will HelpDue to variables besides the ad text itself, it’s possible to have the same ad be both the winner and loser of an ad text experiment.
Mike Rhodes, founder of AgencySavvy, recenty told me a story about a surprising ad test he ran. Rather than doing an A/B test with two variations of an ad, he ran an A/A test where two ads contained exactly the same text.

Logic would dictate that there should have been no winner and loser in this test, however, he found that ad A won and ad A lost.

The exact same ad both won and lost the experiment!

There couldn’t be a more clear illustration to highlight that there’s more than just the ad text that influences how tests go.

Segment Ad Data for Proper Experiments

The way to solve this problem is to remove as many of the variables as possible when analyzing ad performance data.

By analyzing ads from one ad group at a time, and even one exact match keyword at a time, you remove some of the variability related to differences in queries.

By adding segments for devices, days of week, and ad slot, you can start to really get down to unique scenarios where you have as close as possible to an apples-to-apples comparison of the performance of different ad texts.

When different ads are shown in scenarios that closely resemble one another, you can start to point to the ads as the main driver of differences in performance.

Data Sparsity When Segmenting Ads Data

The more we segment the data, the more granular the data becomes and the harder it is to find a statistically significant winner.

You can try one of the many statistical significance calculators available online (like this one) to see how a decrease in metrics makes it harder to find a meaningful winner.

Trading Off Volume & Similarity of Data

So we have to make tradeoffs and decide how to balance having enough data with having it come from similar auctions. This is where the script comes in.

Previous iterations of it ignored segments. While it would have lots of data for metrics, that data came from every possible scenario where the ad ran.


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