Hiroko's manager asks why Hiroko spends time working on her new Google App campaign. The manager believes that machine learning is doing everything. What are three ways in which Hiroko can help guide the machine-learning-powered campaign?

Provide a lot of good data.

Set boundaries.

Evolve the strategy.

Update campaign settings daily.

Adjust bids regularly.


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

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Explanation: Hiroko’s manager asks why Hiroko spends time working on her new Google App campaign. The manager believes that machine learning is doing everything. What are three ways in which Hiroko can help guide the machine-learning-powered campaign?


Explanation: Hiroko can play a crucial role in guiding her new Google App campaign, despite machine learning automating many aspects of it, in three key ways. Firstly, she should **provide a lot of good data**. Machine learning relies on data to make informed decisions and optimize campaign performance, so providing ample, meaningful data enables the algorithms to learn and improve over time. Secondly, Hiroko should **set boundaries**. By defining clear constraints and parameters within which the machine learning algorithms operate, such as setting a thoughtful bid and budget, Hiroko can ensure that the campaign stays aligned with business objectives and avoids unnecessary spending or inefficient resource allocation. Finally, Hiroko should **evolve the strategy**. Markets, consumer behavior, and competitive landscapes are constantly changing, so Hiroko should monitor campaign performance closely, analyze data insights, and adapt the campaign strategy as needed to capitalize on emerging opportunities and address evolving challenges effectively. By actively engaging with these three guiding principles, Hiroko can effectively steer her machine-learning-powered campaign towards success and achieve desired outcomes efficiently within the dynamic digital advertising landscape.

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