If you're training to get Google Ads Display Certification, then it's possible that you've already encountered the question "How Do Responsive Display Ads Use Automation?"
In fact, you might actually be searching online for the correct answer to this question, which is why you landed on this page! However, if you really want to be an expert in providing marketing services to your company or for a client, then you have to understand the answer to this question more than the verbatim answer for the quiz.
So in this article, we won't just tell you the answer to that question; we'll even go deeper and discuss the answer so you'll understand more than just the concept.
What are Responsive Display Ads?
Responsive Display Ads (RDA) have developed from being web-based ads that automatically resize and fit your screen to those that change not just the size but also the elements of the ad.
RDAs are the newest form of advertisements on websites and apps. The assets that appear within an ad space can be manipulated based on user behavior. These ads use machine learning to streamline the process of delivering high-converting ads, allowing them to target specific demographics better.
Google Ads uses assets that advertisers provide when creating their marketing campaigns. For more information on creating a responsive detail ad and the benefits of using it, check our article on The Power of Responsive Display Ads.
So How Exactly Do Responsive Display Ads Use Automation?
Everything online right now is powered by machine learning, and that's what responsive display ads are taking advantage of.
The Google Display Network (GDN) is an advertising network that allows advertisers to show ads on partner sites, within Google products like YouTube and Gmail, and external partners such as publishing websites. But since it's powered by machine learning, this means that the advertisements created are not just used for targeting specific demographics, like on Facebook or Twitter. Instead, it actually predicts the performance of each ad based on past data—including the content of an ad, who it's targeting, and more.
While humans tend to be biased on what types of ads will work based on a specific demographic, machines or AI don't. The AI analyzes the performance of the ads themselves, the performance of individual elements of the ads, and the performance of these ads on specific demographics. After that, it combines the best elements for the particular audience demographic and placement to create the ad that will most likely generate clicks or conversions (based on the advertiser's goals).
But the process is more complicated than that. Google's Display Ad Network has an automated bidding system that can shift budgets based on performance predictions of each impression of an ad, if you so choose.
Should You Use Responsive Ads for Your Marketing?
If you don't want to waste your time creating several variations of a single promotion, then yes. It's time to let Google decide what will work best for you.
However, if you're not comfortable with the idea of giving control of your ads to AI—and taking a bit of risk that it might choose a less-than-ideal ad type—then there are other options available.
Creating several variations of a single promotion can be both time-consuming and expensive, which is why it's best to let Google or another automated system do the work for you.
It does not just minimize the time you need to spend creating ads, but it also reduces the amount of time you spend analyzing the results of your campaigns. Doing the latter is so much more time-consuming and tedious, especially since you don't do it just once but regularly for the entire time your ads are running.
Furthermore, machine-learning analyzes the performance of individual elements of the ad as well—the ad title, description, images, call to action, and more! You will not be able to do that with individually created ads unless you create multiple variations of a single ad and change only specific elements (such as creating four ads, all of which have the same description, image, etc., but all with different ad titles).
What About the Answer to the Google Ads Display Certification Question?
If you understood what we discussed above, you would be able to choose the correct option in the quiz. But if you still haven't, then it's this:
source: AnswerOut
What about the other options? Why were they considered wrong?
If you have chosen any of the other three options and feel confused about why they were wrong, we'll help clear things up for you by discussing them one by one.
Wrong Choice #1
source: AnswerOut
You saw the words machine-learning, and you automatically thought that this must be it! However, as you can see, this option states that RDA uses machine-learning to create REPORTS, which is not true.
RDA uses machine learning to predict which ad will work best with the current audience. It happens in the split-second before the ad is delivered.
Reports, on the other hand, are the results of the ad campaign. They don't have an impact on the performance of the ad itself.
Wrong Choice #2
source: AnswerOut
Responsive Display Ads can be used on static and dynamic display ads on both desktop and mobile devices. This is the primary reason why it's called responsive ads, after all; it's because it can be used on almost any platform as the ad adjusts to the placement!
Wrong Choice #3
source: AnswerOut
RDA indeed displays an ad that is a combination of assets that have shown exemplary performance in the past, but that does not mean RDA will create new assets. It makes ads based on a combination of assets that the advertiser has created and uploaded.
More Than Just for Certification
More than just answering the quiz in order to get certified, it is crucial to deeply understand the methodologies of Google Advertising because it can help you create better ads (or widen your use of possible assets).
It is impossible to talk about every scenario where knowing the methodologies will benefit your campaigns, but here are some examples:
- You may need to change an ad that has already been submitted because this will affect its performance. Knowledge of these types of methodological changes could be invaluable if they would change the outcome of your campaign.
- An advertiser often needs to put together their own assets for an ad format, which can be time-consuming and tedious. The more knowledge one has on how RDA selects among all display advertisements when displaying a given slot; the better one can plan their assets to have the highest chance of achieving the advertising goals.
- Understanding how RDA works allows you to explain these complicated mechanics so that your clients will be able to comprehend them better as well, which may reduce any misunderstandings or confusion. This is incredibly important since they are the ones who need to see initial results in order to continue using Google Ads.
- How does machine learning work in ad creation? You can also explain the answer to your clients or managers in simple terms if you know the answer.
- Understanding how RDA works will let you better understand the campaigns that are already running (if any). This knowledge can be used when communicating with the client or with your boss. This can help them better understand how assets are selected by the AI and why specific results arise.
Do You Need Help in Using Responsive Display Ads?
Even with automation and machine learning, if you have no idea what you are doing, you will not be able to achieve the results you expect. If you need assistance in running RDAs, we can help!
Please send us a message through our contact form, or better yet, book a demo of Brax so we can show you how your online ads can be managed better.
