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Here’s how Google Ads’ new keyword selection preferences work

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With last week’s announcement that it will extend same-meaning close variants to phrase match and broad match modifier, Google said it would be changing keyword selection preferences to help prevent keywords from competing against each other. This doesn’t mean there still aren’t times when keywords compete with each other on Ad Rank. To clarify how Google Ads’ keyword selection preferences are designed to work with same meaning keywords, we’ve mapped out several scenarios.

Existing preferences trump new same-meaning matching. In the initial announcement, Google said of the changes to keyword selection preferences: “If a query currently matches to an exact, phrase, or broad match modifier keyword that exists in your account, we’ll prevent that query from matching to a different phrase or broad match modifier keyword that’s now eligible for the same auction as a result of this update.”

In other words, Google won’t suddenly pick a different phrase or BMM keyword deemed to have the same meaning as a keyword that’s already triggering on a query. This is how the preferences already work for exact match same-meaning close variants.

The example Google gives is that the query lawn mowing service near me will continue matching to the phrase match keyword “lawn mowing service” even though another keyword in your account, “grass cutting service,” could also now match to that query based on same-meaning matching.

Same-meaning exact match keywords. The example above is how the preferences already work for exact match same-meaning close variants. Within exact match, the keywords that are closest to the query generally take precedence over the other eligible exact match keywords. This has not changed.

For example, the query grass cutting services should trigger the exact match [grass cutting services] not [lawn mowing services] if both are active in an account, regardless of Ad Rank.

New keywords with the same meaning as existing keywords. What happens when you add new keywords to your account that may match more closely to queries than your existing keywords?

For example, if the phrase match keyword “lawn mowing service” is matching the query grass cutting service near me in your account and then you add two keywords, “grass cutting service” and +grass +cutting.

They all have the same meaning, but the new keywords are closer word matches to the query than the original keyword. They will prevent “lawn mowing service” from triggering on related grass cutting queries.

However, the two new keywords will compete against each other on Ad Rank to determine which triggers the ad.

In other words, the previous matching preferences will take precedence over same-meaning matching.

[Ad Rank is a calculation of max CPC, quality score (expected CTR, ad relevance, landing page experience), the expected impact of ad extensions and ad formats as well as other contextual factors like location and device. It determines if your ad is eligible to show and where it appears on the page relative to other ads.]

Adding a phrase match or BMM of an existing exact match. Let’s say we have the exact match [lawn mowing service] in our account. Because of same-meaning close variant matching, it triggers on the query grass cutting service. If you add the phrase match “lawn mowing service,” will it compete with the exact match?

Again, it shouldn’t. The exact match and it’s close variants will take precedence because the new phrase match would only eligible based on the new preferences (i.e. same-meaning). Again, the previous matching preferences will supersede the new same-meaning matching for phrase match and BMM.

Adding an exact match of an existing phrase match or BMM keyword. This is the inverse of the previous scenario. If I have the phrase match “grass cutting services” in my account already and add the exact match [grass cutting services], will the exact match trigger for the query grass cutting services. Will it compete against the phrase match?

Since the query is an identical match for the exact match keyword, the exact will be preferred. However, if the keywords are in different ad groups, and the phrase keyword has a lower bid and higher Ad Rank, it can be used instead.

Caveats to note. Keep in mind, these systems aren’t perfect, particularly when it comes to nuances. Don’t expect your idea of “same meaning” and the system’s to always align. Have a routine for monitoring your search terms reports and adding negative keywords.

These factors can also cause same-meaning matching to kick in when it otherwise wouldn’t:

  • Match types in separate ad groups. Given that match type variations of keywords in different ad groups will compete on Ad Rank, that’s something to keep an eye on and consider grouping under one ad group for eaiser management.
  • Paused keywords. All of the scenarios above assume the keywords are enabled. If you pause a keyword in your account, it becomes invisible to the auction system and won’t be included in the keyword selection process. To the system, it’s as if it’s no longer in your account at all. This means if you pause a keyword the other same-meaning keywords in your account could now trigger on the queries the paused keyword had matched to. For example, pausing “lawn mowing services,” will shift lawn mowing services near me queries to trigger “grass cutting services.”
  • Limited budgets. Limited budgets can throw a wrench in your matching. Google says, “While we do our best to match existing traffic to your keywords, there may be infrequent instances where this will not be the case. For example, if a campaign is budget constrained it may not be eligible to show on all queries.

About The Author

Ginny Marvin is Third Door Media’s Editor-in-Chief, managing day-to-day editorial operations across all of our publications. Ginny writes about paid online marketing topics including paid search, paid social, display and retargeting for Search Engine Land, Marketing Land and MarTech Today. With more than 15 years of marketing experience, she has held both in-house and agency management positions. She can be found on Twitter as @ginnymarvin.

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Restaurant app Tobiko goes old school by shunning user reviews

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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.

Tobiko screenshots

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.



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3 Ways to Use XPaths with Large Site Audits

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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.
  • Select Inspect.
  • 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.

2 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

3 setup xpath 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.

4 configure xpath extraction

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

Auditing Ecommerce sites can be one of the more challenging types of SEO auditing. There are many more factors to consider, such as JavaScript rendering and other dynamic elements.

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:

  • Product name
  • Product description
  • Price
  • Review data
  • Image URLs
  • Product Category
  • 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.

Keywords

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:

=ISNUMBER(SEARCH("keyword",A1))

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.

This formula will present a TRUE/FALSE Boolean value. You can use this to quickly identify keyword opportunities and cannibalization in your blogs.

Author

We’ve already covered this example, but it’s worth noting that this is still an important element to pull from your articles.

When you blend your blog export data with performance data from Google Analytics and Search Console, you can start to determine which authors generate the best performance.

To do this, sort your blogs by author and start tracking average data sets including:

  • Impressions – Search Console
  • Clicks – Search Console
  • Sessions – Analytics
  • Bounce Rate – Analytics
  • Conversions – Analytics
  • Assisted Conversions – Analytics

Share Your Creative XPath Tips

Do you have some creative auditing methods that involve XPaths? Share this article on Twitter or tag me @seocounseling and let me know what I missed!

More Resources:


Image Credits

All screenshots taken by author, October 2019



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When parsing ‘Googlespeak’ is a distraction

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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.



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