Outsmarting Google Ads? Why Automated Bidding is Your Secret Weapon

Let me start this by saying - you're not smarter than Google.

The company processes over 8.5 billion searches per day, has access to more data than most of us can fathom, and generally speaking has some of the most competent engineering in the world building out new features and algorithmic changes.

However, despite the fact that most people would readily agree with the above, I see time and time again marketing agencies advocating against the use of automated strategies - particularly when it comes to bidding. Reasons I've heard from vary ranging from we get better performance from manual bidding to we don't trust Google and everything in between.

In this blog, I want to discuss some thoughts on this and why I think automated bidding gives marketers a serious advantage when used correctly.

The Shifting Landscape of Bidding in Google Ads

Manual bidding was once a standard practice in Google Ads. It involves manually setting bids for specific keywords or ad groups. While it does provide a more granular level of control, it has and continues to become an increasingly less efficient and less effective approach due to:

• The time consuming nature
• Potential for change frequency errors (too many/too few)
• Potential for change size errors (wrong amount/size)

In contrast, automated bidding strategies leverage Google's machine learning and advanced algorithms to analyze massive datasets make instantaneous bid optimizations based on various factors, including user behavior, search intent, and historical performance data - all of this with zero manual input required.

Benefits of Automated Bidding: The Power of AI

By analyzing vast amounts of data, including historical campaign performance, user behavior, and contextual signals, automated bidding strategies offer a pretty powerful way for you to optimize bids in real time - with relatively minimal effort I might add.

This can help you get the best possible results whether your goal is maximizing clicks, conversions, or return on ad spend (ROAS).

Other key advantages of automated bidding include:

• Enhanced Efficiency: Eliminates the time-consuming and labor-intensive task of manual bid adjustments, freeing up resources for other strategic initiatives such as asset creation or campaign strategy.
• Data-Driven Accuracy: Real-time insights, and contextual understanding of each search allows for more informed and precise bidding decisions, i.e. reduced change size and frequency errors.
• Scalability: Easy to adapt and optimize with large-scale campaigns that have numerous keywords and ad-groups.

If Automated Bidding is So Great - Why Do Some Agencies Fight It?

Based on my experience, there are a couple reasons why people fight for using manual bidding versus automate bidding strategies including:

• Perception of Control: Manual bidding gives a sense of direct control over campaigns. Many people feel they can leverage their expertise to make better decisions than an algorithm but this is really just overconfidence and neglects the fact that Google's AI processes far more data than any human can.
• Justification for Fees: Unfortunately, many use manual bidding as a way to demonstrate value and justify fees arguing that expertise in manual bidding is a premium service that warrants a higher price, even if automated strategies consistently outperform manual efforts.
• Niche Scenarios: There may be specific situations where manual bidding could be marginally beneficial compared to automated bidding, such as in very small campaigns with limited data or for highly specialized targeting strategies. However, these are the exceptions rather than the rule and usually will go away as a campaign grows.
• Resistance to Change: Some agencies might be resistant to change and prefer to stick with what they know, even if it's less efficient or effective. They might fear the learning curve associated with automated bidding or be hesitant to relinquish control.
• Mistrust in Google's Algorithm: Some people are skeptical of fully trusting Google's black-box algorithms due to potential conflicts between Google's goal (profit for Google) and their clients' objectives (profit for client). I hear this often but personally feel it is strange because results for clients will translate to profit for Google in the long term.

However, these concerns are mostly unfounded. While Google may try to drive up spend at times or there may be some extremely rare situations where manual bidding provides an incremental improvement, their main goal is to get you better results!

Better results, mean you spend more money with them and the fact is that automated bidding consistently outperforms manual - in addition to providing a range of other efficiency-related benefits.

Automated Bidding Success: Training Google's Algorithm

Ok so if we aren't using manual bidding then what are marketers supposed to do?

The key to unlocking the full potential of automated bidding lies in training Google's algorithm to understand your business objectives and target audience. This involves providing clear signals through conversion tracking, audience targeting, and ad creative optimization. In other words, your job is to train Google's algorithm and machine learning.

The better, more relevant data you fee the algorithm the more quickly it optimized which means better performance.

Actionable Tips for Improving Automated Bidding

1. Ensure Tracking is Set Up Properly: Make sure the Google Tag is correctly implemented on every page of your website and working as expected. Accurate conversion tracking is the what allows automated bidding strategies to optimize so be sure to trouble shoot any issues using Google Tag Assistant. 
2. Define Clear Goals for Campaign: Make sure you have a clear goal or conversion for each campaign and optimize the entire campaign around that. Try not to mix conversions in the same campaign (i.e. leads and purchases).
3.  Choose the Right Strategy: Select the automated bidding strategy that aligns best with your business goals and account stage. Some common automated strategies include maximize conversions, maximize conversion values, and tROAS however the best strategy will be individual to you.
4. Use Broad Match Keywords + RSAs: Use broad match keywords and RSAs (responsive search ads) to give Google the most flexibility to optimize itself. Being too restrictive with your targeting, especially early on can prevent or delay optimization.
5. Monitor and Refine: Early on, you will need to be monitoring your campaign pretty closely and filtering out and using negative keywords to guide optimization. Once you are getting consistent conversions, you should review your campaigns regularly and make small adjustments.
6. Trust the Algorithm: Allow Google's AI to do its job and optimize your bids for maximum results. Don't make big large scale changes to budgets or keywords but rather watch the data and make smart, small adjustments.

Interested in more? Here are some additional tips to boost your Google Ads campaigns.

Would You Use Google Ads AI Copy Software?

At the moment, I don't and wouldn't recommend the use of Google Ads AI ad generator. It hasn't really gotten to the level that a good copywriter/creative could produce. In my opinion, it tends to just push out overgeneralized keywords that I feel fall flat as compelling ads.

The difference between using AI in copy creation versus bidding is there is an emotional element to creating compelling ads/copy that I feel AI struggles to create. When it comes to bidding, things are much less nuanced and emotion based. This makes it far easier for an algorithm to find you the best possible bidding opportunities for whatever your goals are.

Embracing Automated Bidding

It's undeniable that Google processes far more data than most people can comprehend. While manual bidding might offer a sense of control, automated strategies that leverage Google's AI provide a significant advantage in terms of efficiency, accuracy, and overall performance.

In the end, the choice between manual and automated bidding comes down to this: Do you want to spend your time and resources on repetitive tasks that an algorithm can do better, or instead focus on strategic and higher level initiatives that will truly help drive business growth?