“Google automation is going to end our jobs.” It’s a phrase we heard a few times last year from marketing consultants when we started pushing forward automation options on the Google Ads platform. But, without the knowledge of our concerned colleagues, automation has always been part of the Google Ads platform.
In the past three years, however, this automation has been much more obvious. Historically, it was buried at the back of the platform or hidden from view at the front of things.
In recent years, however, Google has put its algorithms at the front and center of bid strategies at the campaign level. But, in the opinion of many online merchants, these bid automation options brought reduced performance and were not worth trying.
But is this assumption true?
Google channeled a lot of money into its automation and machine learning technology. If Google sees so much value in automation, it’s not worth asking: “Who wins when marketers use Google automation: marketers… or Google?”
Google Ads automation
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When we speak about automation in Google Ads, there are two basic classes to consider: Smart bidding and smart creatives.
Smart Bidding uses Google machine learning to analyze millions of signals in real-time to present an ad to the desired customer at the right time. The machine learning information that Google uses in most cases is a black box for end users and marketers.
This is an important procedure to maintain the privacy of the user’s most intimate information.
Of the millions of signs explained in real-time, some are available as standard bid adjustments, such as device, physical location, time of day, gender, and age.
However, Google’s algorithms make decisions based on tons of data that marketers cannot see for privacy reasons.
For example, we are unable to make bid adjustments based on users’ search history, users’ visit habits to the site, browser and browser attributes, users’ operating systems, site positioning, and behavior – just to name a few.
Google’s algorithms, on the other hand, can use all of this knowledge and more in real-time to make bid adjustments designed to produce the best possible results.
And when Google says “real-time”, they mean it. Bids can be adjusted the second a user performs a search so that the search results provide a more relevant ad that connects to the signals collected and focuses on performance.
Smart creatives use Google machine learning to select and build what they consider the best combination of creative assets for a user in real-time.
As Google continues to show ads, it further optimizes which ads are shown for which signals in order to improve the desired performance of the ad. Examples of smart creatives are responsive display and search ads.
The value of automation
The fact is, it’s impossible to beat the speed and accuracy of Google Smart Bidding. With Google’s ability to adjust bids based on thousands of signs in real-time, a person can’t even begin to compete.
An advertiser cannot be in the system adjusting bids, bid adjustments in locations based on the individual user who clicks.
There is also a level of access to information that Google would never be able to share with marketers. Users’ personal information can be securely analyzed using machine learning, but that same information in the hands of marketers would be serious breaches of privacy and data protection.
As Google puts it:
“The customer journey is more complex than ever, spanning multiple locations and designs. For marketers, it’s important to understand how to interact with users at all times, but doing it manually is a challenge. That’s where automated solutions come in. “
It’s time for marketers to change their minds about automating Google Ads. Since the beginning of 2019, disruptive advertising has seen major improvements in performance as we have adopted automation. It also gave us more time to spend building more sophisticated marketing strategies, instead of adjusting bids indefinitely.
Automating things the right way
If you have decided that you are going to enter the automation movement, you need to make sure that you are prepared to provide the system with the best information possible. After all, automation is as good as the data input we provide.
An example of an entry can be one of the following:
Return on ad spend / CPA goals
Some examples of managing these entries include:
If your goal is to get leads, you should make sure that your Google Ads account is focused on generating lead conversions. If your goal is to earn purchase revenue, you should make sure that your Google Ads account is focused on generating conversion value.
If you don’t have enough leads or conversions, you can try to optimize your campaigns based on some type of micro conversion until you do.
If your return on ad spends goals are too high for your campaigns, Google will limit the size of your audience to find only those users who will reach that limit.
If you don’t create audiences and apply them to your campaigns, you won’t provide Google with more specific audience information for optimization.
If your budgets are too low, you are telling Google that these users may not be as valuable to you and that you are not interested in increasing the volume of those users.
If you’re adding exclusions or negative keywords to your account, you’re telling Google exactly what searches you don’t want to perform.
It is your job to ensure that you are providing information to Google machine learning by adjusting the list above.
Will Google automation “take over our job”? I personally don’t think so, especially not with the automation options that we have available now.
The continued adoption of automation by Google may remove some tactical options available to us on the Google Ads platform, but it increases the need for higher quality strategies, better audience definition, clearer conversion settings, and more realistic ROAS and CPA goals. These are things that only a living, breathing marketer can offer.
And, to be honest, it’s the kind of thing that we marketers should focus on, not adjusting the bidding settings.