Display ads can either fill white space like subpar motel art, or they can be a powerful means of discovering or reaching your target audience. Google’s rollout of the Responsive display ad format (RDAs) in 2018 was an effort to give advertisers more creative options, as well as increase the reach and value of display advertising. If you are late to the party or have been hesitant to test RDAs, here are 3 reasons why every advertiser should give RDAs a try.

#1 Save Time While Increasing Creative Output

Let’s start with the most obvious reason. RDAs save the creative team time, as well as yourself. Image ads are quick and easy to upload, but in most cases, swapping out current image ads with either fresh images or images with new text overlay isn’t an easy process. For example, if you are running display ads for products with frequent price changes, RDAs are going to be 100 times more efficient and effective than image ads.

So how do RDAs work? The short answer: once you upload the necessary assets, Google automatically resizes and formats your assets to create image, native, video, or text ads. This makes your ads eligible for practically any ad space, thus exponentially increasing your creative output. Here is a basic example of the combinations Google created for one of our clients:

Advertisers can upload up to 15 images, 5 logos, 5 videos (more on this feature below), 5 short headlines, 1 long headline, and 5 descriptions. Here’s how this looks in Google Ads’ interface:

I recommend uploading your own images, but there are alternatives if you don’t have images to upload:

  • Scanning websites
  • Stock images (which can be found using words, phrases or URLs)

Additional options include selecting a CTA (11 different CTAs to choose from) and customizing your colors. The custom colors feature allows advertisers to align background colors and CTA buttons with your brand.

#2 Boost Reach While Enhancing Your Brand Message

Advertisers (generally) run display campaigns with the goal of either increasing brand/product awareness to a cold audience or boosting sales/leads by remarketing to site visitors. Because Google can use this ad type to fit nearly any display ad space, your ads will be eligible for significantly more placements vs. uploading five different sizes of the same image ad. This is one reason why testing RDAs is a no brainer.

By combining Google’s ability to adjust your assets (using their machine learning model that makes decisions based on predictions created from historical performance) with your ability as the advertiser to craft ad copy that fits your brand, your brand voice won’t get lost through the automation. Whether you are running RDAs in a prospecting or remarketing campaign, being able to craft ad copy along with quality images (or videos) boosts your reach without sacrificing the ability to easily fine-tune your message. Creating multiple headlines allows Google’s machine learning model to determine the best headline, thus helping the advertiser identify what message their audience responds to the best at each stage of the funnel. Enhancing a brand message across specific target markets/stages of the funnel without having to constantly create and upload new creative asset is a major benefit compared to previous display formats. 

Caution & Recommendations: Every advertiser knows that greater reach capacity leads to an increase in spend. As with any new display campaign, monitor placements and performance closely. If you are running image ads alongside RDAs, you may consider breaking out RDAs into a separate campaign to keep control of any spend spike. If you are running RDAs and image ads in the same campaign, it can be difficult to compare performance since RDAs are likely to take up the majority of the budget due to greater placement opportunity. Account managers may differ on the suggested account structure, but I prefer to break out new ad formats because it increases my control, thus lowering the risk of negatively impacting performance.

When Google announced RDAs, they claimed advertisers, on average, see 10% more conversions at a similar CPA when using multiple headlines, descriptions, and images, versus a single set of assets. Often times, when an advertiser sees “time saver” or reads, “Google’s machine learning will deliver better results”, skepticism can quickly arise. This blog is not a case study on how RSAs will lift display conversions by xxx%; perhaps a future blog. What I am saying, is performance will vary by account, but you won’t know the success of RDAs until you try it. Since RDAs are now the default display ad type, you will have to give them a try eventually.

#3 New Responsive Display Ad Features

Google recently announced three new features for the RDA format. Here’s a brief summary including why I think it will enhance ad performance.

  1. Video Assets: If you are already running RDAs, this may not be news to you because you were eligible for the beta. For the newbies – I consider this new feature a fantastic addition to the RDA asset suite. Yes, video assets will increase reach potential, but the main reason to test video in your RDAs is engagement. Not only is a video more engaging than an image or a line of text, but it also gives advertisers the opportunity to share much more about their brand or a certain product. For example, do you think you would be more apt to visit an airline’s site if you saw an image ad advertising a trip to Paris, or a video ad telling the story of a couple’s “city of love” adventure? I’m not implying that video assets will outperform other display assets every time. You need to craft your ads according to your audience. Video may never engage a cold audience, but it may increase the engagement of an in-market audience. Again, test before making assumptions.
  2. Combinations Tab: Broken out by images, text, video and feed sections, the combinations tab, which can be accessed by clicking “view asset details,” tells you which ad combinations are performing the best. This feature further encourages testing out multiple headlines and images so that advertisers can determine which assets to use going forward. Because this ad type is driven by Google’s machine learning, it’s helpful to see what is working best so you can make more informed decisions when creating the next batch of RDAs.
  3. Ad Scorecard: This straightforward feature guides advertisers through the steps that need to be made in order to achieve an “excellent” ad. Finding the right ad is a trial and error process. The scorecard can point you in the right direction if you are not sure how to improve your ad. Here’s an example:

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Author: Andrew Harder

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