Every marketer knows the value of having Google Search Ads. Consumers are out there looking for products and services, and using Google Ads puts you right in front of customers when their interest is high. Recently, Google unveiled Google Responsive Search Ads—a new way to approach these ads that uses machine learning technology to take extra work off your plate.
The rollout of Google Responsive Search Ads has taken a tremendous work burden off the shoulders of businesses and marketing teams. Now, marketers can utilize hundreds or thousands of combinations of headlines and descriptions without doing any heavy lifting.
By mastering this new approach to paid search, you have the potential to improve your Google Ad capabilities by turning over the testing and optimizing of search ads to machine learning technology.
What are Google Responsive Ads?
Google Responsive Ads are a strategic way to upgrade your Google PPC ads. Marketers will come up with multiple headlines and descriptions for their ads, then Google tests different combinations of these headlines and descriptions to see which ones are most effective.
Furthermore, Google adjusts these tests depending on user history, meaning different users could get varying ad messages if Google algorithms believe they are more likely to respond to them.
Marketers begin by submitting between 3 to 15 headlines and 2 to 4 descriptions to Google Ads. Out of these multiple options, Google will use machine learning to attempt different combinations.
If you submit the maximum of 15 headlines and 4 descriptions, this means that there are literally tens of thousands of potential combinations. While this could seem overwhelming to a marketing team of any size, the incredible number of variations is the key benefit of using Google Responsive Ads. In fact, there are many advantages, and a few drawbacks, for businesses using responsive ads.
The Pros and Cons of Google Responsive Ads
Why is having so many combinations so valuable? Because while thirty-thousand ad varieties could drive the average marketer mad, it is a treasure trove of value when used with Google machine learning.
Implementing Google Responsive Ads means that Google is testing these many varieties, and then using certain ones more when they are found to be effective. So once an ad is being run multiple times, that means that it’s one of the best out of thousands. These combinations can also be applied differently depending on the user, meaning there often won’t be one “winning” message but a number of effective Google Ads for multiple audiences.
All this testing and optimizing is also done by Google for free—you still just only need to pay per click like you would with regular Google Ads. It’s clear to see why so many marketers are eager to use Google Responsive Ads.
While there are many clear benefits to using responsive ads through Google, there are also a few disadvantages that are worth mentioning. For example, because all the optimization of Google Responsive Ads is automated, there is no human oversight, which may not sit right with some. While examples of machine learning algorithms going horribly wrong are few, it may be seen as risky to some.
Another drawback is that there is little transparency with responsive ads on Google. While marketers can submit their preferred headlines and descriptions, there is no reporting on which combinations were most successful. Marketers will only know the success rate of their campaigns as a whole—there is no attribution data for individual combinations of headlines and descriptions. Some marketers may prefer the knowledge that comes from A/B testing results.
So, for some traditional marketers, or those who like having their own data to review, Google Responsive Ads have some drawbacks. But overall, these ads offer a tremendous opportunity to let machine learning present prospects with optimized ad messages that appeal directly to them.