Machine learning for large-scale SEM accounts
Can machine learning be applied to your PPC accounts to make them more efficient? Columnist David Fothergill describes how he utilized machine learning to find new keywords for his campaigns.
A key challenge when working on what we could term “large-scale” PPC accounts is efficiency. There will always be more that you could do if given an unlimited amount of time to build out and optimize an AdWords campaign; therefore, the trick is managing priorities and being efficient with your time.
In this post, I will talk about how concepts from machine learning could potentially be applied to help with the efficiency part. I’ll use keyword categorization as an example.
To paraphrase Steve Jobs, a computer is like “a bicycle for the mind.” The generally understood meaning of this statement is that, in the same way a bike can increase the efficiency of human-powered locomotion, computers can increase human mental productivity and output.
With the existentialism out of the way, let’s get to something tangible — We’ll explore here how relevant/valuable it could be to try and automate the process of placing new key phrases into an existing campaign.
What do we mean by machine learning?
As a definition of sorts that ties into our objectives, let’s consider the following to be true:
Machine learning is a method used to devise models/algorithms that allow prediction. These models allow users to produce reliable, repeatable decisions and results by learning from historical relationships and trends in data.
The benefit of “reliable, repeatable decisions” is the exact value that we’re interested in achieving in this case.
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