1.Machine learning: Automated bidding uses machine learning to algorithmically help you set the appropriate bid for each and every auction. This takes much of the heavy lifting and guesswork out of setting bids, so you can meet your performance goals more efficiently and accurately.
2. Save Time: Cross-referencing audience data with context to establish intent and set the appropriate bid is a complex and time-consuming task. Automation offers a way to alleviate this strain on marketing resources.
3. Auction Time bidding: Bidding algorithms tailor bids to each user’s unique context, using relevant signals present at auction time. This is a unique capability in the market, as it allows for bid differentiation, with a high degree of precision based on the conversion opportunity of each auction.
4. Depth of Signals used and cross analysis: Google algorithms integrate a large variety of signals and consider new ones to evaluate user intent. They also go a step beyond traditional signal analysis by recognizing and adjusting for meaningful interactions between combinations of signals while constantly considering new ones.