Which marketing behavior can benefit from AI? (Choose three.)

Analysis of Correct Answer(s)

• Reviewing marketing best practice checklists: AI can analyze vast amounts of marketing data, including successful past campaigns, industry benchmarks, and user engagement metrics. This allows it to identify emerging best practices, tailor recommendations to specific campaign goals, and even automate the generation or intelligent curation of checklists, providing more dynamic and data-driven insights than static reviews.
• Creative-level testing and rotation: AI excels at dynamic creative optimization (DCO). It can simultaneously test multiple variations of ad creatives (e.g., headlines, images, calls-to-action), analyze their performance in real-time, and automatically rotate the most effective creatives to specific audience segments. This maximizes engagement and conversion rates by continuously serving the most impactful ad versions.
• Adjusting bids during seasonal events: AI-powered bidding strategies leverage machine learning algorithms to analyze historical performance, predict market fluctuations (like those during seasonal events), and dynamically adjust bid amounts in real-time. This ensures that campaigns remain competitive and cost-effective, capturing maximum value during peak periods and optimizing spend during troughs, leading to a better return on ad spend (ROAS).

Analysis of Incorrect Options

• Product-level testing and rotation: While AI can inform product strategy by analyzing market trends and user feedback, "product-level testing and rotation" primarily relates to product development and lifecycle management, rather than direct marketing behaviors that AI automates or optimizes in the same way as ad creatives or bidding. AI's role here is more indirect, supporting market research rather than direct ad deployment.
• Keeping bids consistent during seasonal events: This option runs counter to the core strength of AI in marketing. AI's value lies in its ability to dynamically adapt and optimize based on changing conditions. Keeping bids consistent during seasonal events, when competition and demand fluctuate significantly, would neglect the opportunity for AI to make intelligent, real-time adjustments that could drastically improve campaign performance and efficiency. This is a static approach, not an AI-driven one.