Automated Bidding Strategy
Using machine learning algorithms to automatically adjust PPC bids based on likelihood of achieving specific campaign objectives.
Definition
Automated bidding strategies use artificial intelligence to automatically set bids for ads based on the probability of achieving campaign goals like conversions, target CPA, or maximize clicks. These strategies analyze vast amounts of data in real-time.
The algorithms consider factors like device, location, time of day, user behavior, and competitive landscape to make bid adjustments faster and more accurately than manual management allows.
Why It Matters
Automated bidding can significantly improve campaign performance by making thousands of micro-adjustments based on real-time data that would be impossible for humans to process and act upon manually.
These strategies free up advertiser time for strategic planning and creative development while often delivering better results through more sophisticated optimization than traditional manual bidding approaches.
Examples in Practice
E-commerce retailer uses Target ROAS automated bidding to maintain 4:1 return on ad spend across thousands of products, letting algorithms adjust bids based on real-time conversion data.
Lead generation company implements Target CPA bidding to maintain consistent cost per lead while Google's algorithm optimizes for users most likely to convert based on behavioral signals.
SaaS platform uses Maximize Conversions strategy during product launches, allowing algorithms to find optimal bids for new keywords without historical performance data to guide manual decisions.