Automated bidding should be used when a campaign benefits from machine learning optimizing bids in real-time based on performance data, saving time and improving results. It is particularly useful for campaigns with clear goals such as maximizing conversions, maximizing clicks, or achieving a target return on ad spend (ROAS). Automated bidding works best when there is enough historical data for accurate predictions, for high-volume campaigns, fluctuating market competition, or when manual bid management is too time- consuming. Experts also recommend waiting about 30 days after campaign launch before switching to automated bidding to gather sufficient data. However, ongoing monitoring and goal-setting are still necessary to ensure the best outcomes with automated bidding.
Key Situations to Use Automated Bidding
- When you want to save time and reduce manual bid adjustments.
- When campaign goals are focused on conversions, clicks, or ROAS.
- For large or complex campaigns with many keywords.
- In dynamic markets where bid adjustments need to be fast and responsive.
- When there is sufficient historical conversion data for machine learning to optimize effectively.
- After an initial period (e.g., 30 days) of manual data collection to train models.
Benefits of Automated Bidding
- Optimizes bids based on campaign goals in real-time using AI.
- Reduces guesswork and human error with data-driven decisions.
- Increases efficiency by managing bids across multiple campaigns or ad groups.
- Adapts to changes quickly in audience behavior or competitive landscape.
- Produces faster campaign optimizations compared to manual bidding.
Considerations
- Automated bidding requires proper goal setup and conversion tracking.
- It doesn't replace the need for regular performance monitoring.
- May not be ideal if precise manual bid control is a priority.
Overall, automated bidding is best used as a strategic tool when advertisers seek to leverage Google's machine learning to optimize bids for better performance and efficiency.
