You now know why you should test increasing bids during unseasonably good weather–read the previous post if you don’t know why. However there are local exceptions. Yesterday I caught the middle of an interview on the BBC. The interviewee explained that whenever there is good weather in Iceland, people take time off from work. If this is the case–increasing bids may not help since no one will be online.

Good weather can influence the success of your Google Adwords campaign. However you may have to turn your strategy upside down in Iceland. Photo credit: Martino!

Further proof that localization should be part of your Google Adwords, MSN and YSM ad campaign strategy.

Another great insight from economics guru, Steve Levitt in his book Freakonomics.

With competition growing daily everyone is always looking for ways to improve Adwords performance. Can a bagel man help us here?

Steve describes how Paul Feldman sheds light on human behavior. Feldman sells bagels on the honor system and keeps meticulous records. He knows who pays and who cheats.

Improve your Adwords performance by
studying bagels. Photo credit: bitmask.

By analyzing his records Steve has found lots of good stuff. And I even found something that even Google Adwords Professionals don’t know-”Unseasonably pleasant weather inspires people to pay at a higher rate. (page 49)”

When the weather is unseasonably pleasant try turning up your bids on Adwords and watching the money pour in. Your competition won’t have a clue. And if you really want to rake it in-develop an algorithmic solution that automatically increases bids whenever the weather warrants it-and sell it to all the Google Adwords Professionals.

When analyzing which ads work better you probably don’t break it down by keyword. This means you may come to the wrong conclusions. We recently compared two ads as you can see in the screen shot below (I changed many of the details to protect the privacy of our client).

Google Adwords AB tests must be analyzed by keyword to avoid reaching the wrong conclusions

The ad on the left had a conversion rate of 1.1% as oppose to the ad on the right which had a conversion rate of 1.8%. However when we break it down by keywords we see that Keyword 2 had:

• A much higher click through rate for ad B
  • In order to improve reliability of the test we run two A type ads and make sure they have the same CTR before we stop testing—this accounts for the higher number of visitors for the ad on the left. If the ads were equal the ad on the left should have twice as many visitors.
• A much higher conversion rate than the other keywords
• A much higher conversion rate than the same keyword has for ad A.

This can skew the results. If we take out keyword 2 we may find that the ads are similar, or even that ad A is better

Different Google Ads for Different Keywords

Look at Keyword 4 and you see that the opposite is true—Ad A is best. Therefore Keyword 4 needs ad A. If  you didn’t do this analysis by keyword you would come to the wrong conclusions and think Ad B is best for the ad group.

The results that you need to remember are:

• For one keyword one ad is best and for another keyword the other ad is best.
• The keywords 2 and 4 need to be in different ad groups so the ads can be optimized for them
• You have to eliminate keywords which have results opposite to the overall trend before analyzing AB ad tests. In a perfect world you want have one exact match keyword per ad group—unfortunately this is not practible
• You have to eliminate keywords yielding vastly different results from the overall trend
• You have to look at each significant keyword separately

You may also ask how these two different keywords ended up in the same ad group to begin with. In a world with time restraints it is not practical to give each keyword its own group. Even if each keyword had its own group you would still have to do the above analysis as people will use different modifiers for each keyword if you use phrase or broad match. That is why the above analysis is based on the actual keywords used by the searchers and not the phrase matched keywords in the ad group.

This is what makes it important to compare ads by keyword.

There are lots of additional insights you can get from the above analysis but I will leave that for another post

Many companies are annoyed that competitors advertise with their brand names in their ads in the search engines. This is known as piggybacking. It is different than conquest buys where the advertiser uses trademarked names to trigger their ads but the brand name does not appear in the ad itself.

Most search engines like Google have policies against piggybacking but allow conquest buys in many cases.

Not all systems are perfect but from the example shown in the Wall Street Journal on this subject (June 4, 2008 European Edition) it looks as if the guilty piggybacking ad is using Google’s automatic keyword insertion feature. This is where the advertiser chooses keywords to trigger the ad and the exact keyword used by the searcher is inserted automatically in the ad by Google’s Adwords system.

Wall Street Journal illustration of Piggybacking. Does Adword’s automatic keyword insertion feature violate Google’s piggybacking policy?

So it seems that Google hasn’t been able to get its own automatic feature to abide by its guidelines. A case of the machine not listening to its human masters.

We recently checked to see if the companies (Marriot International Inc, InterContinental Hotels Group PLC, American Airliness and Northwest Airlines) in the piggybacking article still had the same problem. Turns out they do not. Could it be that the Wall Street Journal article somehow convinced the machine to stop the piggybacking?