Google Ads has made a big push toward automation, with rapid-fire changes to automated bid strategies and ad types in particular.
While the goal of automation is to streamline and simplify, the constant platform updates can cause confusion rather than clarity.
In this guide, we’ll break down every available automated ad type.
You’ll learn the difference between options and naming conventions, as well as when to use each one, so you can confidently make the best decisions for your campaigns.
Google-Created (Auto-Applied) Assets
First on our list of automated ads are those that Google automatically creates on your behalf, without any input from you.
You may not even realize these ads and assets are running, and they may not be compliant with your branding guidelines, so they’re important to review.
When to Use (or Avoid) Auto-Applied Ads & Extensions
You don’t have to do anything for Google-created assets to run (not even approve them!)
If you’re short on time or need some fresh ideas, you can effortlessly run auto-applied ads to test new messaging. Google states that using additional creative may improve your CTR.
However, if you need tight control over your ad messaging (including regulated industries), you may prefer to opt out of auto-applied ads to avoid the risk of non-approved ads slipping through.
Auto-Applied Ad Suggestions
Your account is automatically opted-in to Google Ad suggestions, which you’ll find on the Recommendations page of your account.
Google may add as many as 50 suggested ads per week (though it will likely be fewer).
With Ad suggestions, Google creates new ad variants for you to approve, edit, or dismiss.
If you do nothing, the ads will automatically launch after 14 days.
Ads that are auto-applied (as opposed to manually approved) are marked as “Auto-applied ad suggestion.”
Ad suggestions are based on existing ads and landing pages, and are generated using “a combination of human review and machine learning.”
To opt out of Ad suggestions at the account or MCC level, follow these instructions.
As with auto-applied ad suggestions, your account is opted-in to automated extensions by default.
However, Google doesn’t notify you of their creation and doesn’t seek your approval before they run. In fact, the actual assets that are featured in the ad are never shown in the interface.
Automated extensions are found in their own tab within Ads, and can include call, message, sitelink, structured snippets, location, seller ratings, and callouts.
Unlike Ad suggestions and many manual ad extensions, you can’t measure or compare performance of automated ad extensions.
The metrics shown in the table refer to performance of the entire ad, not the specific extension type. The “this vs other” segment is not available in this view.
Opting out of automated ad extensions is also a bit more involved than opting out of Ad suggestions. Each extension type is managed separately.
You may have noticed from the dropdown list that one of these extensions is not like the others.
“Longer ad headlines” allows description lines that are complete phrases or sentences to be moved to the headline when your ads are served in the top positions on Google.
You can turn off extensions and longer ad headlines by following these instructions.
Think of responsive ads like a “mix and match” game. You enter in multiple headlines, descriptions, and images, and Google picks combinations of those assets to serve across the Google Network.
Responsive ads are so-named because they give Google the assets it needs to “respond” to different audience intent and formatting requirements.
Users are served uniquely assembled ads based on their search queries, device type, or the ad specifications of the site they’re visiting.
When to Use (or Avoid) Responsive Ads
Google is making a clear push towards responsive ad formats, and marketer resistance may be futile. That said, here are some things to consider while responsive ads are still optional.
First, Google’s premise is that through machine learning, it will essentially “personalize” the right message for each user.
But as Richard Beck – BS, MCIS writes of Artificial Intelligence, “it makes no logical sense to claim you can do something very complex… and you’re 20 years away from something rather basic in comparison.”
Consider how frequently Google makes questionable ad serving decisions. For instance, matching a search for “soft suitcase” to the keyword “software.” Or serving irrelevant ads when better matches were available for a keyword.
Whether Google’s machine learning is lacking or their profit motivations aren’t aligned with yours, it’s a stretch to think that either problem will be solved through using an ad type that gives them even more control.
Additionally, no matter which ad assets are used, each ad is allowed only one final URL. It’s hard to experiment with radically different ad ideas if the landing page can’t match the different messages.
And since each asset has to make sense with every other asset, it can be more difficult to create interchangeable “building blocks” than just writing separate, distinct ads.
All that said, responsive ads can still save you time, and may outperform existing ads. We’ll address the specific advantages of responsive ad types below.
Responsive Search Ads (RSA)
Responsive search ads run on the Search Network, and let you enter up to 15 headlines and 4 description lines in a single ad. Google then selects up to 3 headlines and 2 descriptions to run as an expanded text ad.
You can “pin” your text to position to ensure a specific message always runs in a specific spot.
If you have lines of text that must show in an ad (for legal or branding reasons), be sure to pin to H1, H2 or D1, since H3 and D2 don’t always appear.
If you pin more than one headline or description to any one position, they will rotate.
While RSAs allow Google to run multivariate ad testing, Google does not reveal the results of specific combination tests.
In other words, even if the aggregate CTR is higher with a responsive ad, you don’t know which asset combinations contributed to the lift. You’re also in the dark about the impact of specific messages on conversions.
You do have the option to see the top responsive search ad combinations that ran, but these are sorted by impressions, with no details for clicks or any other metrics.
Responsive Display Ads (RDA)
As of late 2018, Responsive Display Ads are the default ad type for the Google Display Network.
All the automated ads mentioned above are practically indistinguishable from their manual counterparts.
RDAs, however, have a distinct look that’s accomplished only through this ad type:
With RDAs, you can add up to:
15 marketing images.
There’s a bit of a learning curve with RDAs, so give yourself some time when you’re first setting them up.
(Pro tip: the call to action text is “automated” by default. Be sure to select an appropriate CTA under “more options” if you don’t want it to rotate through irrelevant CTAs.)
Unlike traditional banner ads, you don’t have to create multiple sizes or dimensions of an RDA. The “responsive” nature of this ad type automatically fits your ad to spec.
And unlike RSAs, you can see an indication of asset performance with RDAs. Just click “view asset details” on your ad. Your assets are given a rating of:
Learning (not enough data)
Select “Combinations,” and you’ll see your top performing “image-text-logo” pairings. But similar to RSAs, this view is not particularly useful, and no actual metrics are revealed.
App Install Ads
App Campaigns (formerly known as Universal App Campaigns) are effectively responsive campaigns, although they don’t share in the “responsive” naming convention.
Ad assets for App Campaigns can include:
Four “mix and match” independent lines of text
Up to 20 each of images, YouTube-hosted videos, and HTML5 creatives
Once your assets are uploaded, they behave very similar to Responsive Display Ads. The performance reporting is similar to RDAs as well.
Our final category of automated ads is known as “dynamic.” Think of dynamic ads like personalized email marketing, or mail merge if you’re old school.
The dynamic ads you create with Google Ads use a “mail merge” type of functionality to pull from a data source (such as keywords, websites, targets or product listings) and customize your ad with unique information, including specific final URLs.
If you’re still not entirely clear on the difference between responsive and dynamic, think of it like this:
Responsive ads get all their content from the assets you create in Google Ads; dynamic ads get their content from external sources.
When to Use (or Avoid) Dynamic Ads
Dynamic ads need more structured data and formatting than other ad types. They can require technical setup, and your data sources must be carefully curated to avoid nonsense ad variations.
Because you’re front-loading additional work, it makes sense to use dynamic ads only if they’ll save you time down the road.
For example, if you were emailing two friends, you wouldn’t create a database – you’d be better off copying and pasting.
Using dynamic ads is a smart choice if you have a large catalog, data feeds, or bulk updates to make. These ads let your messaging stay fresh while keeping your ad set small and edits to a minimum.
Dynamic (Customized) Text
You can use dynamic text in your existing text ads to customize your message without editing or creating multiple new ads.
Keyword insertion includes your matched keyword in the ad text to create an ad that’s specific and relevant to the search. Countdowns build urgency by showing the time remaining on a sale or event.
Ad customizers update your ad’s headline and description with your business data, such as locations, products and pricing. IF functions use “target” inputs like device and audiences to show custom messaging on the Search network.
Dynamic Search Ads (DSA)
Dynamic Search Ads use your website content, rather than a designated keyword list, to identify relevant searches and display your ad.
You select categories or webpages to include and exclude, and create description text. Google then uses your pages to match content and generate headlines and final URLs.
DSAs can be a good solution for large ecommerce sites. You can maintain coverage of your inventory without building keywords and ads for each and every product.
You can also review search term data to find coverage gaps and new keyword opportunities for the ads you’re managing.
DSAs are not right for every business. Daily deal sites, restricted industries, and Flash or image-based sites won’t work with this ad type. Be sure to review the policies and ensure your DSA ad groups are set up for success.
Shopping Ads & Dynamic Remarketing
Although they don’t share the “dynamic” naming convention, all Google Shopping Ads are dynamic by nature. They’re populated from a feed (Merchant Center), and there’s not a 1:1 relationship between a single ad creative and a URL.
Dynamic remarketing ads are actually what you’d expect from the name; they show the specific content your prior visitors viewed on your website. These ads are populated from Merchant Center or your business data.
Dynamic remarketing campaigns can also support dynamic prospecting (scroll down the page for details), which isn’t a separate ad type but which uses machine learning and data feeds to reach new customers.
Phasing Out: Dynamic Display
Google Ads seems to be transitioning away from “Dynamic Display” as a naming convention.
Support information about Dynamic Display ads now redirects to Responsive Display or Dynamic Remarketing articles. The naming difference is subtle, but Dynamic Display (as opposed to Responsive Display) refers to ad templates that are no longer available in the interface.
While the Dynamic display ad feed is still currently supported, the name appears to be in transition. The Google Ads help link “Learn more about dynamic display ads feeds” now redirects to “Create a feed for your responsive ads” instead.
Google’s move toward a more automated platform has pros and cons for advertisers.
Set yourself and your clients up for success by using automated ad formats that save time and bring great results.
While you can stick with manual ad types for simpler campaigns (for now), knowing when and how to use automated ads will give you a marketing edge.
You can think of Tobiko as a kind of anti-Yelp. Launched in 2018 by Rich Skrenta, the restaurant app relies on data and expert reviews (rather than user reviews) to deliver a kind of curated, foodie-insider experience.
A new Rich Skrenta project. Skrenta is a search veteran with several startups behind him. He was one of the founders of DMOZ, a pioneering web directory that was widely used. Most recently Skrenta was the CEO of human-aided search engine Blekko, whose technology was sold to IBM Watson in roughly 2015.
At the highest level, both DMOZ and Blekko sought to combine human editors and search technology. Tobiko is similar; it uses machine learning, crawling and third-party editorial content to offer restaurant recommendations.
Betting on expert opinion. Tobiko is also seeking to build a community, and user input will likely factor into recommendations at some point. However, what’s interesting is that Skrenta has shunned user reviews in favor of “trusted expert reviews” (read: critics).
Those expert reviews are represented by a range of publisher logos on profile pages that, when clicked, take the user to reviews or articles about the particular restaurant on those sites. Where available, users can also book reservations. And the app can be personalized by engaging a menu of preferences. (Yelp recently launched broad, site-wide personalization itself.)
While Skrenta is taking something of a philosophical stand in avoiding user reviews, his approach also made the app easier to launch because expert content on third-party sites already existed. Community content takes much longer to reach critical mass. However, Tobiko also could have presented or “summarized” user reviews from third-party sites as Google does in knowledge panels, with TripAdvisor or Facebook for example.
Tobiko is free and currently appears to have no ads. The company also offers a subscription-based option that has additional features.
Why we should care. It’s too early to tell whether Tobiko will succeed, but it provocatively bucks conventional wisdom about the importance of user reviews in the restaurant vertical (although reading lots of expert reviews can be burdensome). As they have gained importance, reviews have become somewhat less reliable, with review fraud on the rise. Last month, Google disclosed an algorithm change that has resulted in a sharp decrease in rich review results showing in Search.
Putting aside gamesmanship and fraud, reviews have brought transparency to online shopping but can also make purchase decisions more time-consuming. It would be inaccurate to say there’s widespread “review fatigue,” but there’s anecdotal evidence supporting the simplicity of expert reviews in some cases. Influencer marketing can be seen as an interesting hybrid between user and expert reviews, though it’s also susceptible to manipulation.
About The Author
Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.
When used creatively, XPaths can help improve the efficiency of auditing large websites. Consider this another tool in your SEO toolbelt.
There are endless types of information you can unlock with XPaths, which can be used in any category of online business.
Some popular ways to audit large sites with XPaths include:
In this guide, we’ll cover exactly how to perform these audits in detail.
What Are XPaths?
Simply put, XPath is a syntax that uses path expressions to navigate XML documents and identify specified elements.
This is used to find the exact location of any element on a page using the HTML DOM structure.
We can use XPaths to help extract bits of information such as H1 page titles, product descriptions on ecommerce sites, or really anything that’s available on a page.
While this may sound complex to many people, in practice, it’s actually quite easy!
How to Use XPaths in Screaming Frog
In this guide, we’ll be using Screaming Frog to scrape webpages.
Screaming Frog offers custom extraction methods, such as CSS selectors and XPaths.
It’s entirely possible to use other means to scrape webpages, such as Python. However, the Screaming Frog method requires far less coding knowledge.
(Note: I’m not in any way currently affiliated with Screaming Frog, but I highly recommend their software for web scraping.)
Step 1: Identify Your Data Point
Figure out what data point you want to extract.
For example, let’s pretend Search Engine Journal didn’t have author pages and you wanted to extract the author name for each article.
What you’ll do is:
Right-click on the author name.
In the dev tools elements panel, you will see your element already highlighted.
Right-click the highlighted HTML element and go to Copy and select Copy XPath.
At this point, your computer’s clipboard will have the desired XPath copied.
Step 2: Set up Custom Extraction
In this step, you will need to open Screaming Frog and set up the website you want to crawl. In this instance, I would enter the full Search Engine Journal URL.
Go to Configuration > Custom > Extraction
This will bring up the Custom Extraction configuration window. There are a lot of options here, but if you’re looking to simply extract text, match your configuration to the screenshot below.
Step 3: Run Crawl & Export
At this point, you should be all set to run your crawl. You’ll notice that your custom extraction is the second to last column on the right.
When analyzing crawls in bulk, it makes sense to export your crawl into an Excel format. This will allow you to apply a variety of filters, pivot tables, charts, and anything your heart desires.
3 Creative Ways XPaths Help Scale Your Audits
Now that we know how to run an XPath crawl, the possibilities are endless!
We have access to all of the answers, now we just need to find the right questions.
What are some aspects of your audit that could be automated?
Are there common elements in your content silos that can be extracted for auditing?
What are the most important elements on your pages?
The exact problems you’re trying to solve may vary by industry or site type. Below are some unique situations where XPaths can make your SEO life easier.
1. Using XPaths with Redirect Maps
Recently, I had to redesign a site that required a new URL structure. The former pages all had parameters as the URL slug instead of the page name.
This made creating a redirect map for hundreds of pages a complete nightmare!
So I thought to myself, “How can I easily identify each page at scale?”
After analyzing the various page templates, I came to the conclusion that the actual title of the page looked like an H1 but was actually just large paragraph text. This meant that I couldn’t just get the standard H1 data from Screaming Frog.
However, XPaths would allow me to copy the exact location for each page title and extract it in my web scraping report.
In this case I was able to extract the page title for all of the old URLs and match them with the new URLs through the VLOOKUP function in Excel. This automated most of the redirect map work for me.
With any automated work, you may have to perform some spot checking for accuracy.
2. Auditing Ecommerce Sites with XPaths
Sometimes, stakeholders will need product level audits on an ad hoc basis. Sometimes this covers just categories of products, but sometimes it may be the entire site.
Using the XPath extraction method we learned earlier in this article, we can extract all types of data including:
And much more
This can help identify products that may be lacking valuable information within your ecommerce site.
The cool thing about Screaming Frog is that you can extract multiple data points to stretch your audits even further.
3. Auditing Blogs with XPaths
This is a more common method for using XPaths. Screaming Frog allows you to set parameters to crawl specific subfolders of sites, such as blogs.
However, using XPaths, we can go beyond simple meta data and grab valuable insights to help identify content gap opportunities.
Categories & Tags
One of the most common ways SEO professionals use XPaths for blog auditing is scraping categories and tags.
This is important because it helps us group related blogs together, which can help us identify content cannibalization and gaps.
This is typically the first step in any blog audit.
This step is a bit more Excel-focused and advanced. How this works, is you set up an XPath extraction to pull the body copy out of each blog.
Fair warning, this may drastically increase your crawl time.
Whenever you export this crawl into Excel, you will get all of the body text in one cell. I highly recommend that you disable text wrapping, or your spreadsheet will look terrifying.
Next, in the column to the right of your extracted body copy, enter the following formula:
In this formula, A1 equals the cell of the body copy.
To scale your efforts, you can have your “keyword” equal the cell that contains your category or tag. However, you may consider adding multiple columns of keywords to get a more accurate and robust picture of your blogging performance.
Over the almost 16-years of covering search, specifically what Googlers have said in terms of SEO and ranking topics, I have seen my share of contradictory statements. Google’s ranking algorithms are complex, and the way one Googler explains something might sound contradictory to how another Googler talks about it. In reality, they are typically talking about different things or nuances.
Some of it is semantics, some of it is being literal in how one person might explain something while another person speaks figuratively. Some of it is being technically correct versus trying to dumb something down for general practitioners or even non-search marketers to understand. Some of it is that the algorithm can change over the years, so what was true then has evolved.
Does it matter if something is or is not a ranking factor? It can be easy to get wrapped up in details that end up being distractions. Ultimately, SEOs, webmasters, site owners, publishers and those that produce web pages need to care more about providing the best possible web site and web page for the topic. You do not want to chase algorithms and racing after what is or is not a ranking factor. Google’s stated aim is to rank the most relevant results to keep users happy and coming back to the search engine. How Google does that changes over time. It releases core updates, smaller algorithm updates, index updates and more all the time.
For SEOs, the goal is to make sure your pages offer the most authoritative and relevant content for the given query and can be accessed by search crawlers.
When it is and is not a ranking factor. An example of Googlers seeming to contradict themselves popped this week.
Gary Illyes from Google said at Pubcon Thursday that content accuracy is a ranking factor. That raised eyebrows because in past Google has seemed to say content accuracy is not a ranking factor. Last month Google’s Danny Sullivan said, “Machines can’t tell the ‘accuracy’ of content. Our systems rely instead on signals we find align with relevancy of topic and authority.” One could interpret that to mean that if Google cannot tell the accuracy of content, that it would be unable to use accuracy as a ranking factor.
Upon closer look at the context of Illyes comments this week, it’s clear he’s getting at the second part of Sullivan’s comment about using signals to understand “relevancy of topic and authority.” SEO Marie Haynes captured more of the context of Illyes’ comment.
Illyes was talking about YMYL (your money, your life) content. He added that Google goes through “great lengths to surface reputable and trustworthy sources.”
He didn’t outright say Google’s systems are able to tell if a piece of content is factually accurate or not. He implied Google uses multiple signals, like signals that determine reputations and trustworthiness, as a way to infer accuracy.
So is content accuracy a ranking factor? Yes and no. It depends if you are being technical, literal, figurative or explanatory. When I covered the different messaging around content accuracy on my personal site, Sullivan pointed out the difference, he said on Twitter “We don’t know if content is accurate” but “we do look for signals we believe align with that.”
It’s the same with whether there is an E-A-T score. Illyes said there is no E-A-T score. That is correct, technically. But Google has numerous algorithms and ranking signals it uses to figure out E-A-T as an overall theme. Sullivan said on Twitter, “Is E-A-T a ranking factor? Not if you mean there’s some technical thing like with speed that we can measure directly. We do use a variety of signals as a proxy to tell if content seems to match E-A-T as humans would assess it. In that regard, yeah, it’s a ranking factor.”
You can see the dual point Sullivan is making here.
The minutiae. When you have people like me, who for almost 16 years, analyze and scrutinize every word, tweet, blog post or video that Google produces, it can be hard for a Google representative to always convey the exact clear message at every point. Sometimes it is important to step back, look at the bigger picture, and ask yourself, Why is this Googler saying this or not saying that?
Why we should care. It is important to look at long term goals, and as I said above, not chase the algorithm or specific ranking factors but focus on the ultimate goals of your business (money). Produce content and web pages that Google would be proud to rank at the top of the results for a given query and other sites will want to source and link to. And above all, do whatever you can to make the best possible site for users — beyond what your competitors produce.
About The Author
Barry Schwartz is Search Engine Land’s News Editor and owns RustyBrick, a NY based web consulting firm. He also runs Search Engine Roundtable, a popular search blog on SEM topics.