Introduction to Smart Bidding with Google Ads

“Smart Bidding” is a subset of Google’s “Automated Bidding,” which is a machine-learning feature. Smart bidding focuses on Google Ad conversions, whereas Automated Bidding is broader, including functionality to increase the value of impressions and clicks, which would typically be earlier in the customer conversion path (also known as a sales funnel).

The basic intent of Automated Bidding and Smart Bidding is to not only reduce some of the repetitive labor involved with managing Google Ads but to actually inform better decisions.


The application of machine learning and artificial intelligence is a rising tide that will not subside.

As useful as this functionality is, an inherent liability is the potential for an ad manager to become so reliant on the machine learning that he or she may relegate their own analysis to a lesser role, when sometimes a more scrutinizing eye may see automated pricing anomalies that don’t make sense and require adjustment action.

For example, in other areas of Google machine learning support, such as keyword suggestions, if you just immediately activate all recommendations, you can sometimes see ad performance decline. This is in spite of the fact that a majority of the automated recommendations are useful. The trick is to eliminate those that are non-productive.

I do not doubt that all their machine learning recommendations will improve over time, but I do wonder whether such will supplant an alert human management intelligence, at least in terms of overall strategic implementation and responding to competitive changes in the real world.

An interesting future competition would be a human Google Ads Manager using the full suite of Google’s machine learning and functionality versus some type of fully automated Google Ads Management Artificial Intelligence.

The competition would be based upon both contestants beginning with a duplicate and identical website along with a marketing brief to generate as many leads or sales for a given product or service. If both the human and AI contestants were only able to rely on the website and their wits along with all Google Ads tools, I wouldn’t be surprised if the AI might win due to its ability to analyze more data faster. However, it would be a more realistic competition if the human could also use the data that Google’s machine learning was providing to then also make changes to the website in real-time, which would provide a significant advantage to the human.

Of course, it could be argued, “Why not allow the AI to make website changes, too?” It might be instructive to see what happens, but I could envision an AI instructed to generate the most sales might also incrementally reduce the price of the product or service to zero to achieve that goal, whereas the human would have the wisdom to know that would lead to business failure.

It could then be argued that the AI could be programmed with limiting parameters, such as low-price restrictions. But how can every conceivable real-world scenario be anticipated? For instance, a price restriction would be rendered immediately useless in the real world if something unusual (such as a global pandemic), might influence real-world wide price swings. Perhaps there exists AI programming automation to account for pandemics, as well.

Regardless, I’m bullish on the use of machine learning and AI to help with pay-per-click and advertising purchase decisions and improved ad performance. And although a lower need for less experienced human ad managers may ultimately be a result, I can also conceive that the need for more experienced human oversight might rise.

Anyway, I’m diverting from the topic at hand. Let’s return to Smart Bidding strategies.


There are four smart bidding strategies.

1. Maximize Conversions

  • This auto-sets bids to generate the most conversions while maintaining ad spending within your indicated campaign budget. In other words, some bids would be higher than a manager might manually indicate, but this could be auto-balanced by lower-bids at different times.

2. Maximize Conversion Value

  • This auto-sets bids to help generate maximum conversion value. The key difference here is you would need to establish conversion tracking value in conjunction with basic conversion tracking.

3. Target CPA

  • This auto-sets bids to generate the most conversions possible at the designated target cost-per-action (CPA). This is best for campaigns that are not budget constrained.

4. Target ROAS

  • This auto-sets bids to generate the most conversions possible at your indicated target return on ad spend (ROAS). Once again, you would need to track conversion value in conjunction with basic conversion tracking for this to function. Furthermore, the campaign would need 15 conversions in the prior 30 days. A risk here is that if you set your desired ROAS target outside the range of present competitive reality, you’ll miss out on conversions.


Strategically, it’s best to start with Maximize Conversions or Maximize Conversion Value and then switch to Target CPA and Target ROAS, once you’ve refined your goal.

Google also provides auto recommendations for anticipated best strategies, which can help inform what strategy to start with and when to consider switching.

It’s worth emphasizing that you must have conversion tracking previously established. However, even without the utilization of Smart Bidding, your Google Ads account is at an important disadvantage if you’re not already using conversion tracking.

A unique aspect to these current Smart Bidding strategies is that they don’t require a conversion history. This means the strategies can be implemented on a new account or new campaign.

And like any machine learning or artificial intelligence application, you don’t want to evaluate performance too early. These strategies need to acquire sufficient data to become useful. It can take 1-2 weeks for the data to begin to create a meaningful performance impact, but such really depends on the volume of conversions.