Machine Learning For PPC: Why You Still Need A Human’s Input

The era of artificial intelligence (AI) is upon us. For marketers, it’s mostly a good thing. AI takes the guesswork out of ad campaigns and automates many previously tedious and time-consuming processes. One branch of AI that’s had a big impact on Pay-Per-Click (PPC) ads and paid search marketing is machine learning.

While machine learning has the potential to be a powerful tool for PPC marketers, it’s not always the right option and won’t replace the human element in many cases. Learn more about how machine learning works with PPC and how your brand can use it to make the most of paid search.

What Is Machine Learning?

Machine learning is part of AI. It’s a field of study that allows computers or other machines to learn without being programmed. Another way to define machine learning is a machine’s ability to imitate human behavior.

If that sounds futuristic and high-tech, it’s worth pointing out that machine learning is all around you. Every time your favorite streaming service recommends a movie, show, or song you love, you’re witnessing machine learning in action. When you get customer service from a chatbot or scroll through your social media feeds, you see the results of machine learning.

Machine learning thrives on data. The more information a machine has to process, the faster it learns and adapts. Modeling is another critical component of machine learning. Once a machine has the data, it needs to know what to do with it or how to process it. When given a model to follow, it determines what to do with the data, and the results are often amazing. Sometimes, though, they’re downright wrong, demonstrating that while machine learning and AI have made great strides in recent years, it’s still got a ways to go.

How Does Machine Learning Work With PPC?

Machine learning plays multiple roles in PPC marketing. It’s behind audience tagging and keyword matching. It also plays a critical role in the Smart Bidding features available through Google. Smart Bidding helps to keep brands from overpaying or underpaying for keywords. Some of the ways you can use machine learning for Smart Bidding include:

• Increasing clicks: If you’re interested in increasing your ad’s click-through rate (CTR), machine learning adjusts your keyword bidding strategy to dramatically increase the number of website visitors and clicks your brand receives.
• Increasing ad impressions: If lead-building is your goal, you can use machine learning and Smart Bidding to boost the number of impressions your ads receive, raising awareness of your brand.
• Increasing conversions: Machine learning uses data about your brand to help you bid on the keywords that will lead to the most conversions. The bidding feature uses your historical data and contextual clues to determine the ad placements that will lead to the greatest conversions.
• Targeting acquisition cost: If you set a target cost for acquisitions, Google’s machine-learning algorithms will aim to get conversions without your costs exceeding your target.
• Targeting return on ad spend: Return on ad spend bidding typically depends on your brand’s historical data. It uses your data to determine a cost per click (CPC) that’s most likely to help you achieve your target. For example, you may want to achieve $5 in revenue for every $1 spent, which is a target of 500%.

Benefits of Machine Learning for PPC

One of the biggest benefits of machine learning for PPC is that it saves you a lot of time. You no longer have to crunch the numbers yourself or spend hours creating if or then scenarios. Google’s algorithms handle that for you. Smart Bidding and other machine learning features also cut down on the time you have to spend maintaining your campaigns. You can essentially set and forget (but don’t actually forget) your PPC strategy without worrying that you’ll drastically over or under-spend.

Thanks to AI and machine learning, the complexities of PPC are accessible to all, even absolute beginners. You can be confident that your campaign will produce the results you want or reach your targets without hiring experts.

Drawbacks of Machine Learning for PPC

While AI and machine learning can be revolutionary, we aren’t quite at the stage where we can hand everything over to machines. Some human intervention is still needed and in some cases, preferable.

When you rely on AI, you’re essentially counting on Google to take on your ad campaigns for you. You have to trust that the machines are using your data in the best way possible. You also give up some control of your budget and ad spending when you use machine learning.

It can also take a few months or campaigns before you have accumulated enough data for machine learning to be effective for your brand. And it might not work as well as it could the first few times you use it.

Should You Always Rely on Machine Learning?

Machine learning complements but doesn’t replace manual PPC processes, particularly for larger brands. Think of it as yet another tool in your digital marketing toolbox. Used along with other resources, it can maximize your conversions, boost revenue, and increase leads. But it’s not the only tool in the box and shouldn’t be treated as such. Reach out to the PPC experts at Zero Gravity to discuss your PPC strategy today!