1. http://ppcadsthatsell.com/bad-data-poor- decisions-careful-watch/ Bad Data, Poor Decisions. Be Careful What You Watch

2. Nobody in their right mind wants to do shoot in the dark advertising. There is simply too much chance of poor figures and wasted money to arbitrarily post an advertisement and see what happens. It is why ad testing is done; to narrow the probability of poor sales figures and increase the chances of strong revenue the same time. When advertising manager must keep in mind is that ad testing is like any other statistical tests. Data problems can cause nightmares. 3. Google allows for some very sophisticated testing of ads that can uncover a great deal of information. However, the old adage of garbage in, garbage out will apply to any ad testing. It is how the data is gathered and then interpreted. Here are some externalities that can affect the data collected in any ad testing 4. Campaigns 5. The types of campaigns are going to produce different figures in order to prevent data problems from happening. The type of campaign first has to be identified. It can be either remarketing, nonremarketing display, branded, or non- branded search. The type of campaign is going to set the parameters for the data that has to be kept in mind. Mixing campaign results can result in statistical confusion as the numbers are searched for answers. 6. The Sample Used For the Test This is a standard component for any type of test whether it is marketing or biology. That being said, there has to be sufficient data to draw realistic conclusions. A sample size which is too small will register nothing of value. 7. Check the Time 8. Marketing has traditionally looked at the seasons of the year, such as Christmas or Easter. It is also quite possible that data will drop off after the peak season for particular product or service is past. That is important. It comes to ad testing because it can establish the high points (E. G. the season) and low points (the off-season) of the ad testing. 9. This attention to time can even extend to hours of a day. Evening users could react in a way that is different to somebody who is more active in the afternoon. Checking the time of day can give an idea of when is the best time slot to run the ad. 10. The Art of the Deal This involves the wording of the ad and its attraction. It isnt just the catchy phrases to attract a certain demographic, but also the actual enticement that is offered (e.g. sizable discount or other consideration to convince a person to make a purchase). It is a situation where the results may be influenced heavily by the deal itself. That has to be factored in to any test evaluation. 11. The Mobile Devices 12. These provide a lot of exposure, but will vary from device to device. A Smartphone may give different data then what is given by a tablet. By having idea of the performance registered by the separate devices, which ones are bad and which ones give excellent results, can prevent a situation where mobile devices as a group prejudices the data collected one way or the other. 13. Confusion among Ad Extensions 14. Its possible there may be different phrases used. The ad extensions might by themselves be interpreted as a reason for one ad standing out from all the rest. While the wording is important, no single ad extension should be used as the crucial determinant of success. 15. Be Careful of Search Partners That Are Used search partners can have different objectives then those of the main search. Be sure that the search partner (or partners) is a variable taken into consideration when the data is reviewed. 16. Never Let Position Be Misguiding 17. It stands to reason that a higher click through rate will occur if the ads come in at position is higher than average. An aggressive campaign is capable of producing good results, but that doesnt mean that it is the ads alone creating this. Dont be blinded by where your ad stands. These are all caveats and qualifiers that are intended to keep the data of an ad test from being contaminated. 18. Outside factors such as the season or the deal inherent in the advertisement can skew the statistics. If they are not accounted for the wrong information can result. That can defeat the entire purpose of doing ad tests. While some people may think its a little tedious to watch out for all of these things, it can be devastating if all the tests can produce is data that cant truly measure the effectiveness of a given task. 19. Thank You