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What Can Be Learned From Google SafeSearch About Doing Better PPC



Do you think that Google’s SafeSearch can teach you something to enhance your knowledge so that you can perform better as a digital marketer?


If your answer is no, then you need to think again, it can actually teach so many things as it perfectly illustrates how algorithms are used to automate search and those same principles used by Google can help PPC pros improve their game.


You need to use the automation layering to stay in sync with the Google updates as it automates nearly every aspect of the search marketing. You cannot expect to get a good result while you are sitting alongside.


SafeSearch: Algorithms + Humans


Although the algorithms are good at calculating similarities between things, it sometimes fails to determine where the shift has been taking place and where it should be the threshold, and that us where it needs a human.


The algorithm can rank the search result and a number can be assigned to each keyword, and then a human can look at the ranked list to determine a reasonable threshold that fits the business criteria of what the SafeSearch feature was intended to do.


Thresholds in PPC


It then dawned on me that Google uses thresholds in hundreds of places. There is a threshold for when an ad’s quality score is high enough to make it eligible to appear above organic results. There is a threshold for when ad experiments can be concluded. There are thresholds for when a query is similar enough to a keyword to show an ad. And so forth.


Now that we know that Google uses many types of thresholds in their algorithm, as a digital marketer, we need to set our threshold to get a good result. Algorithm ranking happens in many forms, but let’s understand the concept in terms of keyword matching.

Google has recently expanded its “close variants,” and now the exact match of the keywords are not necessarily exact, it can be something that has a similar or close meaning.


For example, when a user searches for something and if the keywords are not exact as that of the advertiser, then Google uses its machine learning tools to find the similarity between the two keywords.


A score is provided to each keyword and google has a threshold score for evert other keywords. Therefore, only the keywords that have got the score higher than that of the threshold will be shown to the user in the advertisement.


This is something that has immensely decreased the workload of the advertisers as they now do not have to find every keyword that is similar to the one they have used, rather they can go with the keywords that might have the score well above the threshold in most of the cases. However, this cannot be predicted exactly as no one is aware of the fact that how google actually sets the threshold score of the keywords but still, it is quite useful.


Automation Layering to Set Your Own Thresholds


Although it a general perception that advertiser does not have any control over the automation, in reality, they have some control. For example, the advertiser can add negative keywords when they find Google is showing their ads for a close variant that they don’t like it.


But the problem is that manual monitoring of automation is incredibly tedious and time-consuming, and the advertiser has to find the score of their keywords and combine them with Google’s automation. This is what can be called as automation layering.


The advertiser can use a rule engine or a script that identifies close variant search terms and applies an algorithm to rank these. They can even use a Levenshtein distance score to calculate how different a search term is from the other keyword.


Levenshtein distances of 2 or 3 are usually typos, but if the distances are more than that, then it is something that is needed to take care of: Either as an idea for a new keyword. Or possibly something to exclude by adding a negative keyword.


Now that the advertiser has its own numerical score, it is easy to draw the line and set a threshold as per their expectations and scope of their business. When the two automated thresholds, the one of Google and that of the advertiser, are combined, the advertiser will get benefited as their ad will be shown even for the search term which does not have the exact meaning as of the keywords searched by the user.


When the two automated thresholds, the one of Google and that of the advertiser, are combined, the advertiser will get benefited as their ad will be shown even for the search term which does not have the exact meaning as of the keywords searched by the user.

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