Google automation is going to take our jobs. It’s a phrase I’ve heard a few times over the last year from marketing consultants as we’ve started pushing front-facing automation options in the Google Ads platform. But, unbeknownst to my worrisome colleagues, automation has always been a part of the Google Ads platform.
Over the last three years, however, that automation has been much more obvious. Historically, it was buried in the back-end of the platform, or hidden in plain sight on the front-end side of things.
In recent years, however, Google has put their algorithms front and center with campaign-level bid strategies. But in many online marketer’s opinions, these bid automation options brought reduced performance and weren’t worth trying. But is that assumption true?
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Google has funneled a lot of money into their machine learning and automation tech. If Google sees that much value in automation, isn’t it worth it to ask, “Who really wins when marketers use Google automation: the marketers…or Google?”
Google Ads Automation
When we talk about automation in Google Ads, there are two basic categories to consider: Smart Bidding and Smart Creatives.
Smart Bidding uses Google’s machine learning to analyze millions of signals in real-time to present an advertisement to the desired customer at the right moment. The machine learning information that Google uses in most cases is a black box for end-users and marketing professionals. This is an important procedure to keep user’s more intimate information private.
Of the millions of signals analyzed in real-time, some are available as manual bid adjustments like device, physical location, time of the day, gender and age. However, Google’s algorithms make decisions based on tons of data that marketers can’t see for privacy reasons.
For example, we can’t make bid adjustments based on users’ search histories, users’ site visiting habits, browser and browser attributes, users’ operating systems, placement and site behavior—just to name a few. Google’s algorithms, on the other hand, can use all of this information and more in real-time to make bid adjustments designed to produce the best possible results.
And when Google says “real-time”, they really mean it. Bids can literally be adjusted the second in which a user performs a search so that the search results provide a more highly relevant ad that connects with collected signals, and focuses on performance.
Smart Creatives use Google’s machine learning to select and build what it deems is the best combination of creative assets for a user in real-time.
As Google continues to display ads, it further optimizes which ads show to which signals in order to improve the desired performance of the ad. Examples of smart creatives are responsive search and display ads.
The Value of Automation
The fact is that it’s impossible to beat Google’s Smart Bidding speed and accuracy. With Google’s ability to adjust bids based on thousands of signals in real-time, a human can’t even begin to compete.
An advertiser can’t be in the system adjusting bids, bid adjustments on locations based on the individual user making the click.
There’s also a level of access to information that Google would never be able to share with marketers. Users’ personal information can be securely combed through using machine learning, but that same information in the hands of marketers would be serious data protection and privacy violations.
“The customer journey is more complex than ever, spanning multiple sites and devices. For marketers, it’s important to understand how to engage with users in all of these moments, but doing that manually is a challenge. That’s where automated solutions come in.”
It’s time for marketers to change their mindset around Google Ads Automation. Since early 2019, Disruptive Advertising has seen great improvements in performance as we’ve adopted automation. It has also given us more time to spend building more sophisticated marketing strategies instead of adjusting bids endlessly.
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Automating Things the Right Way
If you’ve decided you’re going to hop on the automation bandwagon, you need to make sure you’re set up to provide the system with the best information possible. After all, automation is only as good as the data inputs we give it.
An example of input might be one of the following:
- Conversion Value
- Return on Ad Spend/CPA Targets
- Negative Keywords/exclusions
Some examples of managing these inputs include:
- If your goal is to get leads, you must make sure your Google Ads account is focused on generating lead conversions. If your goal is to get purchase revenue, you must make sure your Google Ads account is focused on generating conversion value. If you don’t have enough volume of leads or conversions, you can try optimizing your campaigns based on some sort of micro-conversion until you do.
- If your return on ad spends targets are too high for your campaigns, Google will limit your audience size to only find you users that will get to that threshold.
- If you don’t create audiences and apply them to your campaigns, you aren’t giving Google more specific audience information to optimize off of.
- If your budgets are too low, you’re telling Google that those users may not be as high of value to you and that you are not interested in increasing that volume of those users.
- If you’re adding in exclusions or negative keywords in the account, you’ll be telling Google exactly what searches you don’t want coming through.
It’s your job to make sure that you are providing Google’s machine learning with information by adjusting the list above.