Question: 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?
- Update campaign settings daily.
- Adjust bids regularly.
- Set boundaries.
- Provide a lot of good data.
- Evolve the strategy.
Explanation
App campaigns use Google’s machine learning to optimize ad delivery across Google properties, but the system depends on advertiser-provided inputs. Campaign goals, budget, bid strategy, locations, languages, and creative assets define the operating limits for automation. Accurate conversion tracking and meaningful in-app event data help the system optimize toward valuable users. Ongoing strategic changes should reflect business priorities such as installs, in-app actions, or value-based goals.
Why the other options are incorrect
Update campaign settings daily is incorrect because frequent manual changes can disrupt machine learning from collecting stable performance signals.
Adjust bids regularly is incorrect because App campaigns use automated bidding based on the selected goal and performance data.
Source for verification
https://support.google.com/google-ads/answer/6247380
https://developers.google.com/google-ads/api/docs/app-campaigns/overview
The answer(s) to the question is highlighted in the BOLD text above. You can also find more questions and answers related to the exams on the "Google Ads Apps Assessment" page.