What are two ways that marketers can benefit from machine learning in Google Ads? (Choose two)

Machine learning produces results that align with defined campaign goals.

Machine learning saves time by analysing hundreds of signals automatically.

Machine learning sets campaign bids and budgets automatically.

Machine learning evolves campaign goals automatically, without input.


Choose an option to see if it’s correct. Check the explanation below. Learn Smarter, not Harder.

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Explanation: What are two ways that marketers can benefit from machine learning in Google Ads? (Choose two)


Explanation: Marketers can benefit from machine learning in Google Ads in two primary ways: firstly, machine learning produces results that align with defined campaign goals, and secondly, machine learning saves time by analyzing hundreds of signals automatically. The first option is correct because machine learning algorithms in Google Ads are designed to optimize campaign performance based on predefined objectives such as maximizing conversions, increasing website traffic, or improving return on ad spend. By continuously analyzing data and adjusting campaign parameters, machine learning ensures that ad campaigns are tailored to meet specific goals, leading to more efficient and effective outcomes. The second option is also correct because machine learning automates the process of analyzing vast amounts of data and identifying patterns or trends that would be impractical or impossible for human marketers to analyze manually. By automating tasks such as audience segmentation, keyword selection, and bidding optimization, machine learning frees up marketers' time to focus on strategic decision-making and creative tasks, ultimately improving campaign performance and driving better results. Therefore, these two options highlight the tangible benefits that marketers can derive from leveraging machine learning capabilities within Google Ads to optimize campaign performance and streamline workflow processes.
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