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?

Hiroko can guide her machine learning-powered campaign in three key ways: by setting clear boundaries, supplying ample quality data, and continuously evolving the strategy. Setting boundaries means defining goals, budgets, and

• Update campaign settings daily.
• Adjust bids regularly.
• Set boundaries.
• Provide a lot of good data.
• Evolve the strategy.

Explanation:
Even though machine learning powers Google App campaigns, Hiroko’s role is essential for driving success. Think of machine learning as a powerful engine—it still needs human direction and high-quality input to run effectively.

• Set boundaries: Hiroko provides clear limits by establishing realistic bids and budgets. These boundaries help the system optimize efficiently without overspending or focusing on irrelevant conversions.
• Provide quality data: Machine learning relies heavily on good data. By ensuring accurate conversion tracking, maintaining high conversion volumes, and supplying varied ad creatives (images, videos, text), Hiroko feeds the system the insights it needs to learn and improve.
• Evolve the strategy: As business goals shift, Hiroko adjusts the campaign focus—such as moving from maximizing installs to targeting high-value in-app actions. While the system can optimize, only Hiroko can redefine strategic priorities over time.