How to Leverage Machine Learning to Improve AdWords Efficiency

Recent issues surrounding racial inequality in the United States have led to direct action in the digital marketing world as well. More and more companies are pausing their Facebook ad campaigns because of the social network’s inaction on discrimination and hate speech.

But this doesn’t mean these tech giants are going to stop advertising, right? How could they without harming themselves? Many of these businesses are instead shifting more advertising towards Google AdWords, which is Google's advertising system in which advertisers bid on certain keywords in order for their clickable ads to appear in Google's search results.

While AdWords gives brands (big and small) the opportunity to put its business in front of people from across the globe, not all AdWords campaigns are created equal.

While it’s true that elements such as keyword selection and copywriting play a major role in the effectiveness of these campaigns, new tech advances such as machine learning, are allowing these processes to become more automated than ever before.

Through machine learning, you can improve the efficiency of your AdWords campaigns to achieve greater customer acquisition results than ever before.

Improving Creative Output With Responsive Search Ads

Regardless of keyword selection, the copy and headlines you select for an AdWords campaign will have a major influence on whether someone actually clicks on your ad or not.

The problem, of course, is that it can be tricky to deliver the right message at the right time to the right person. A headline and copy that work perfectly in one situation, could fall flat if the same person saw it after a slightly different search query.

Responsive Search Ads

This is where Responsive Search Ads come in. Jerry Dischler, Vice President of Product Management for AdWords, leads the product team for Google's search ads business, the product and engineering teams for YouTube advertising, and the product and engineering teams for Google's home-grown sales and support tools.

According to Dischler:

“Simply provide up to 15 headlines and 4 description lines, and Google will do the rest. By testing different combinations, Google learns which ad creative performs best for any search query. So people searching for the same thing might see different ads based on context. We know this kind of optimization works: on average, advertisers who use Google’s machine learning to test multiple creative see up to 15 percent more clicks."

Backed by machine learning, a user's AdWords content will be optimized for a variety of search queries using your target keyword. The result is more clicks and more conversions.

Optimizing Your Budget With Smart Bidding

Balancing a budget that delivers results without spending too much money is a big challenge for many AdWords campaigns, but machine learning now lets marketers optimize their budgets through Smart Bidding.

As long as your account has sufficient historical data and conversion tracking set up, you can use Smart Bidding to optimize keyword bids based on your campaign goals. The machine learning algorithm analyzes customer patterns based on prior searches to put greater priority on bids for searches when customers are likely to take your campaign’s desired action.

I spoke with Chris Gonzalez, who recently published his case study on KlientBoost about the power of leveraging machine learning with respect of expediting client accounts through Smart Bidding:

“Leveraging machine learning not only helped us to speed
up the technical optimization of [our clients’ accounts]; it also helped us clear up time for more aggressive optimization tactics. And these are the ones that ended up driving the biggest leaps forward in performance (and PPC mastery) for us,” a move that helped one client achieve “… a 40.81 percent decrease in Cost/Conv and 107.32 percent boost in Conversion Rate.”

With Smart Bidding, you can have Google’s machine learning algorithm prioritize a target cost per acquisition, return on ad spend, impressions share, or maximize conversions or clicks. You can also set bid limits to ensure that bidding never goes over your allotted budget.

Stopping Underperforming Ads

Not all marketing campaigns are a hit. Sometimes, ads miss the mark and fail to generate any type of meaningful return on investment. In such situations, machine learning can prove vital for helping you identify these poor performers and stop spending money on them. This way, you can divert your budget to ads or campaigns that actually deliver the results
you want.

A single poorly performing ad can hurt an overall AdWords campaign by lowering your quality score, which Google uses to determine the ad’s relevance. If left unchecked, the low-quality ad will hurt future marketing efforts.

To counteract this, some marketers have begun using AI tools that help them identify and stop these ads early on in a campaign.

In this approach, Search Engine Watch (SEW) presented a more in-depth explanation:

“The model must not be so sensitive that it abandons ads before they have a chance to show ROI. It must use statistical inference to estimate potential losses and gains based on previous performance. Rather than pausing the full ad outright, the model should factor in individual segments that can be paused, such as traffic from mobile devices, certain browsers that are not producing revenue, times of day or days of the week that repeatedly do poorly, or ad variations that aren’t performing well," SEW author Manish Dudharejia suggests.

By pausing ads or underlying traffic segments that are contributing to poor campaign performance, you can divert bids to higher-performing ads and achieve a higher quality score for your campaign.

Let Machine Learning Do the Work For Stronger AdWords Results

Marketers often have a tendency to want to control each tiny aspect of their campaign. This can make the transition to machine learning — in which you give up much of your control to an algorithm — a bit of an adjustment.

However, this is one attitude shift that can make a big difference in the long run. By using machine learning to better understand what will appeal to your audience and optimize the way you run your campaigns, you will save time and be more likely to reach your startup’s KPIs.