Sally's historically spent a lot of time in Google Ads making small changes to her campaigns,instead of focusing on higher level marketing strategy.What are two ways machine learning helps reduce the time she'll spend in her Google App campaign?(Choose two.)

Machine learning helps reduce the time Sally spends in her Google App campaign in two key ways.Firstly,machine learning can analyze many signals to determine the right audience for her ad.Instead of manually sifting through data to identify the most relevant audience segments,machine learning algorithms can efficiently process vast amounts of user data in real-time to pinpoint the audience demographics,interests,and behaviors that are most likely to respond positively to Sally'sads. This automation saves Sally time and effort,allowing her to focus on higher-level marketing strategy rather than audience targeting minutiae.Secondly,machine learning can create combinations of assets to deliver a relevant ad to the right user.Insteadof manually creating and testing different ad variations,machine learning algorithms can dynamically generate ad combinations using various assets such as text,images,and videos to tailor the ad content to individual user preferences and behaviors.By automating the ad creation process,machine learning enables Sally to quickly iterate and optimize her ad creatives,ultimately improving campaign performance and driving better results without the need for extensive manual intervention.Therefore,by leveraging machine learning capabilities,Sally can streamline her campaign management work flow,freeing up time to focus on over arching marketing strategy and objectives.