Machine Learning in Marketing? There’s nothing to worry about.

BY: Level Agency
July 11, 2022

These days when people hear the words automation or machine learning, they might think robots are here to take over their jobs.  

But after Level Agency sat down with Google to discuss all things automation and machine learning in a recent webinar, rest assured there is room for both humans and machines in the marketing world.  

If you’re open to it or not, it looks like machine learning is here to stay at least when it comes to automated bidding across Google channels. 80% of Google advertisers are currently using automated bidding strategies, with some seeing a 31% lift in conversions at the same cost per acquisition. 

But again, fear not, there will always be room for both humans and machines. There can be a good balance between both.  


Finding the Middle Ground Between Humans and Machines 

Smart Bidding in Google is part of the daily lives of Level’s media analysts. But that hasn’t always been the case. For many years, media buying was done the old-fashioned way: manually pulling spend levers. A few years ago, Tim Fitzgerald Level’s eCommerce Team Lead started an annual human vs. Machine bidding competition. And for many years, the humans won. But recently, the machines started to win easily.  

The way Tim sees it, smart bidding isn’t taking away control. It’s just giving media analysts better levers to pull. By using smart bidding, media analysts are making smarter, more efficient decisions instead of sitting at their desks making manual micro-changes throughout the day.  

Leaning on smart bidding also gives media analysts the brain space to think about strategy more, which ultimately benefits campaign results. Analysts can pivot quickly and put forth more effort into other strategic and tactical approaches.  


Machine Learning in Practice 

What does working alongside machine learning look like? Well, for us at Level it looks a lot like our philosophy of Test. Learn. Grow. Abby Young, media manager on Level’s eCommerce team looks at machine learning to test different strategies based on machine learning results.  

For example, based on how Google’s Smart Shopping or Performance Max campaigns are pushing a particular product in the eCommerce space, Abby can use this data to inform other campaign efforts. That product that is being pushed by machine learning will now become the focus of a social media campaign or an email sequence. Once a test is in the market, her next steps are to pay close attention to what changes need to be made for successful results.  


Smart Bidding Considerations 

If you're just getting started with Google’s smart bidding strategies, there are a few things advertisers need to keep in mind. 

  • Timeline: Wait at least 4 weeks before you evaluate data. There’s a 2-week learning period and a 2-week optimization period. Also, consider your sales cycle in your timeline. 

  • Volume: Evaluate conversions at 50 conversions per month.  
  • Budgets: If you're aiming at a ROAs target, uncap budgets to drive incremental value. If you’re using max conversion value keep budgets in line with daily spending goals.  
  • Cadence: Make sure values are uploaded/tracked daily.  
  • Targets: Use the ROAs recommendations at the time of opt-in or historical performance of your conversion value.  
  • Campaigns: Reduce additional campaign changes whenever possible. 


Google’s Performance Max 

Another way to take advantage of automation and machine learning with Google is their new campaign type Performance Max. Performance Max was built with a machine learning focus and so far, it is achieving optimal machine learning across all Google properties.  

Some benefits of performance max include: 

  1. Find more converting customers for your goals. 

  1. Drive more value from your budget. 

  1. Get rich and transparent insights.  

  1. Use the best of Google Ads Automation. 


Convincing the Skeptics of Automation and Machine Learning 

What happens if you’re receiving pushback on the use of automation and machine learning in your advertising campaigns?  

The best place to start is by testing it. Let the data and algorithm show the results. And continue to adjust as you learn more.  

It’s important to keep in mind that smart bidding isn’t only for eCommerce marketing. Even if your industry is heavily regulated, Google has options with enhanced conversions. They are also working on a Google API project that will serve companies with privacy and regulatory concerns in the future.  

In the meantime, Level is here to help you test a smart bidding strategy or conduct a campaign audit to see if smart bidding is right for you. If you’d like to learn more about automation, set up a time to speak with us.

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