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How to Do an SEO Log File Analysis [Template Included]

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How to Do an SEO Log File Analysis [Template Included]

Log files have been receiving increasing recognition from technical SEOs over the past five years, and for a good reason.

They’re the most trustworthy source of information to understand the URLs that search engines have crawled, which can be critical information to help diagnose problems with technical SEO.

Google itself recognizes their importance, releasing new features in Google Search Console and making it easy to see samples of data that would previously only be available by analyzing logs.

Crawl stats report; key data above and line graph showing trend of crawl requests below

In addition, Google Search Advocate John Mueller has publicly stated how much good information log files hold.

With all this hype around the data in log files, you may want to understand logs better, how to analyze them, and whether the sites you’re working on will benefit from them.

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This article will answer all of that and more. Here’s what we’ll be discussing:

First, what is a server log file?

A server log file is a file created and updated by a server that records the activities it has performed. A popular server log file is an access log file, which holds a history of HTTP requests to the server (by both users and bots).

When a non-developer mentions a log file, access logs are the ones they’ll usually be referring to.

Developers, however, find themselves spending more time looking at error logs, which report issues encountered by the server.

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The above is important: If you request logs from a developer, the first thing they’ll ask is, “Which ones?”

Therefore, always be specific with log file requests. If you want logs to analyze crawling, ask for access logs.

Access log files contain lots of information about each request made to the server, such as the following:

  • IP addresses
  • User agents
  • URL path
  • Timestamps (when the bot/browser made the request)
  • Request type (GET or POST)
  • HTTP status codes

What servers include in access logs varies by the server type and sometimes what developers have configured the server to store in log files. Common formats for log files include the following:

  • Apache format – This is used by Nginx and Apache servers.
  • W3C format – This is used by Microsoft IIS servers.
  • ELB format – This is used by Amazon Elastic Load Balancing.
  • Custom formats – Many servers support outputting a custom log format.

Other forms exist, but these are the main ones you’ll encounter.

How log files benefit SEO

Now that we’ve got a basic understanding of log files, let’s see how they benefit SEO.

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Here are some key ways:

  • Crawl monitoring – You can see the URLs search engines crawl and use this to spot crawler traps, look out for crawl budget wastage, or better understand how quickly content changes are picked up.
  • Status code reporting – This is particularly useful for prioritizing fixing errors. Rather than knowing you’ve got a 404, you can see precisely how many times a user/search engine is visiting the 404 URL.
  • Trends analysis – By monitoring crawling over time to a URL, page type/site section, or your entire site, you can spot changes and investigate potential causes.
  • Orphan page discovery – You can cross-analyze data from log files and a site crawl you run yourself to discover orphan pages.

All sites will benefit from log file analysis to some degree, but the amount of benefit varies massively depending on site size.

This is as log files primarily benefit sites by helping you better manage crawling. Google itself states managing the crawl budget is something larger-scale or frequently changing sites will benefit from.

Excerpt of Google article

The same is true for log file analysis.

For example, smaller sites can likely use the “Crawl stats” data provided in Google Search Console and receive all of the benefits mentioned above—without ever needing to touch a log file.

Gif of Crawl stats report being scrolled down gradually

Yes, Google won’t provide you with all URLs crawled (like with log files), and the trends analysis is limited to three months of data.

However, smaller sites that change infrequently also need less ongoing technical SEO. It’ll likely suffice to have a site auditor discover and diagnose issues.

For example, a cross-analysis from a site crawler, XML sitemaps, Google Analytics, and Google Search Console will likely discover all orphan pages.

You can also use a site auditor to discover error status codes from internal links.

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There are a few key reasons I’m pointing this out:

  • Access log files aren’t easy to get a hold of (more on this next).
  • For small sites that change infrequently, the benefit of log files isn’t as much, meaning SEO focuses will likely go elsewhere.

How to access your log files

In most cases, to analyze log files, you’ll first have to request access to log files from a developer.

The developer is then likely going to have a few issues, which they’ll bring to your attention. These include:

  • Partial data – Log files can include partial data scattered across multiple servers. This usually happens when developers use various servers, such as an origin server, load balancers, and a CDN. Getting an accurate picture of all logs will likely mean compiling the access logs from all servers.
  • File size – Access log files for high-traffic sites can end up in terabytes, if not petabytes, making them hard to transfer.
  • Privacy/compliance – Log files include user IP addresses that are personally identifiable information (PII). User information may need removing before it can be shared with you.
  • Storage history – Due to file size, developers may have configured access logs to be stored for a few days only, making them not useful for spotting trends and issues.

These issues will bring to question whether storing, merging, filtering, and transferring log files are worth the dev effort, especially if developers already have a long list of priorities (which is often the case).

Developers will likely put the onus on the SEO to explain/build a case for why developers should invest time in this, which you will need to prioritize among other SEO focuses.

These issues are precisely why log file analysis doesn’t happen frequently.

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Log files you receive from developers are also often formatted in unsupported ways by popular log file analysis tools, making analysis more difficult.

Thankfully, there are software solutions that simplify this process. My favorite is Logflare, a Cloudflare app that can store log files in a BigQuery database that you own.

How to analyze your log files

Now it’s time to start analyzing your logs.

I’m going to show you how to do this in the context of Logflare specifically; however, the tips on how to use log data will work with any logs.

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The template I’ll share shortly also works with any logs. You’ll just need to make sure the columns in the data sheets match up.

1. Start by setting up Logflare (optional)

Logflare is simple to set up. And with the BigQuery integration, it stores data long term. You’ll own the data, making it easily accessible for everyone.

There’s one difficulty. You need to swap out your domain name servers to use Cloudflare ones and manage your DNS there.

For most, this is fine. However, if you’re working with a more enterprise-level site, it’s unlikely you can convince the server infrastructure team to change the name servers to simplify log analysis.

I won’t go through every step on how to get Logflare working. But to get started, all you need to do is head to the Cloudflare Apps part of your dashboard.

"Apps" in a sidebar

And then search for Logflare.

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"Logflare" appearing in search field on top-right corner, and the app appearing below in the results

The setup past this point is self-explanatory (create an account, give your project a name, choose the data to send, etc.). The only extra part I recommend following is Logflare’s guide to setting up BigQuery.

Bear in mind, however, that BigQuery does have a cost that’s based on the queries you do and the amount of data you store.

Sidenote.

 It’s worth noting that one significant advantage of the BigQuery backend is that you own the data. That means you can circumvent PII issues by configuring Logflare not to send PII like IP addresses and delete PII from BigQuery using an SQL query.

2. Verify Googlebot

We’ve now stored log files (via Logflare or an alternative method). Next, we need to extract logs precisely from the user agents we want to analyze. For most, this will be Googlebot.

Before we do that, we have another hurdle to jump across.

Many bots pretend to be Googlebot to get past firewalls (if you have one). In addition, some auditing tools do the same to get an accurate reflection of the content your site returns for the user agent, which is essential if your server returns different HTML for Googlebot, e.g., if you’ve set up dynamic rendering.

I’m not using Logflare

If you aren’t using Logflare, identifying Googlebot will require a reverse DNS lookup to verify the request did come from Google.

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Google has a handy guide on validating Googlebot manually here.

Excerpt of Google article

You can do this on a one-off basis, using a reverse IP lookup tool and checking the domain name returned.

However, we need to do this in bulk for all rows in our log files. This also requires you to match IP addresses from a list provided by Google.

The easiest way to do this is by using server firewall rule sets maintained by third parties that block fake bots (resulting in fewer/no fake Googlebots in your log files). A popular one for Nginx is “Nginx Ultimate Bad Bot Blocker.”

Alternatively, something you’ll note on the list of Googlebot IPs is the IPV4 addresses all begin with “66.”

List of IPV4 addresses

While it won’t be 100% accurate, you can also check for Googlebot by filtering for IP addresses starting with “6” when analyzing the data within your logs.

I’m using Cloudflare/Logflare

Cloudflare’s pro plan (currently $20/month) has built-in firewall features that can block fake Googlebot requests from accessing your site.

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Cloudflare pricing

Cloudflare disables these features by default, but you can find them by heading to Firewall > Managed Rules > enabling Cloudflare Specials> select Advanced”:

Webpage showing "Managed Rules"

Next, change the search type from “Description” to “ID” and search for “100035.”

List of description IDs

Cloudflare will now present you with a list of options to block fake search bots. Set the relevant ones to “Block,” and Cloudflare will check all requests from search bot user agents are legitimate, keeping your log files clean.

3. Extract data from log files

Finally, we now have access to log files, and we know the log files accurately reflect genuine Googlebot requests.

I recommend analyzing your log files within Google Sheets/Excel to start with because you’ll likely be used to spreadsheets, and it’s simple to cross-analyze log files with other sources like a site crawl.

There is no one right way to do this. You can use the following:

You can also do this within a Data Studio report. I find Data Studio helpful for monitoring data over time, and Google Sheets/Excel is better for a one-off analysis when technical auditing.

Open BigQuery and head to your project/dataset.

Sidebar showing project dataset

Select the “Query” dropdown and open it in a new tab.

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"Query" dropdown showing 2 options: new tab or split tab

Next, you’ll need to write some SQL to extract the data you’ll be analyzing. To make this easier, first copy the contents of the FROM part of the query.

FROM part of the query

And then you can add that within the query I’ve written for you below:

SELECT DATE(timestamp) AS Date, req.url AS URL, req_headers.cf_connecting_ip AS IP, req_headers.user_agent AS User_Agent, resp.status_code AS Status_Code, resp.origin_time AS Origin_Time, resp_headers.cf_cache_status AS Cache_Status, resp_headers.content_type AS Content_Type

FROM `[Add Your from address here]`,

UNNEST(metadata) m,

UNNEST(m.request) req,

UNNEST(req.headers) req_headers,

UNNEST(m.response) resp,

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UNNEST(resp.headers) resp_headers

WHERE DATE(timestamp) >= "2022-01-03" AND (req_headers.user_agent LIKE '%Googlebot%' OR req_headers.user_agent LIKE '%bingbot%')

ORDER BY timestamp DESC

This query selects all the columns of data that are useful for log file analysis for SEO purposes. It also only pulls data for Googlebot and Bingbot.

Sidenote.

If there are other bots you want to analyze, just add another OR req_headers.user_agent LIKE ‘%bot_name%’ within the WHERE statement. You can also easily change the start date by updating the WHERE DATE(timestamp) >= “2022–03-03” line.

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Select “Run” at the top. Then choose to save the results.

Button to "save results"

Next, save the data to a CSV in Google Drive (this is the best option due to the larger file size).

And then, once BigQuery has run the job and saved the file, open the file with Google Sheets.

4. Add to Google Sheets

We’re now going to start with some analysis. I recommend using my Google Sheets template. But I’ll explain what I’m doing, and you can build the report yourself if you want.

Here is my template.

The template consists of two data tabs to copy and paste your data into, which I then use for all other tabs using the Google Sheets QUERY function.

Sidenote.

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If you want to see how I’ve completed the reports that we’ll run through after setting up, select the first cell in each table.

To start with, copy and paste the output of your export from BigQuery into the “Data — Log files” tab.

Output from BigQuery

Note that there are multiple columns added to the end of the sheet (in darker grey) to make analysis a little easier (like the bot name and first URL directory).

5. Add Ahrefs data

If you have a site auditor, I recommend adding more data to the Google Sheet. Mainly, you should add these:

  • Organic traffic
  • Status codes
  • Crawl depth
  • Indexability
  • Number of internal links

To get this data out of Ahrefs’ Site Audit, head to Page Explorer and select “Manage Columns.”

I then recommend adding the columns shown below:

Columns to add

Then export all of that data.

Options to export to CSV

And copy and paste into the “Data — Ahrefs” sheet.

6. Check for status codes

The first thing we’ll analyze is status codes. This data will answer whether search bots are wasting crawl budget on non-200 URLs.

Note that this doesn’t always point toward an issue.

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Sometimes, Google can crawl old 301s for many years. However, it can highlight an issue if you’re internally linking to many non-200 status codes.

The “Status Codes — Overview” tab has a QUERY function that summarizes the log file data and displays the results in a chart.

Pie chart showing summary of log file data for status codes

There is also a dropdown to filter by bot type and see which ones are hitting non-200 status codes the most.

Table showing status codes and corresponding hits; above, dropdown to filter results by bot type

Of course, this report alone doesn’t help us solve the issue, so I’ve added another tab, “URLs — Overview.”

List of URLs with corresponding data like status codes, organic traffic, etc

You can use this to filter for URLs that return non-200 status codes. As I’ve also included data from Ahrefs’ Site Audit, you can see whether you’re internally linking to any of those non-200 URLs in the “Inlinks” column.

If you see a lot of internal links to the URL, you can then use the Internal link opportunities report to spot these incorrect internal links by simply copying and pasting the URL in the search bar with “Target page” selected.

Excerpt of Internal link opportunities report results

7. Detect crawl budget wastage

The best way to highlight crawl budget wastage from log files that isn’t due to crawling non-200 status codes is to find frequently crawled non-indexable URLs (e.g., they’re canonicalized or noindexed).

Since we’ve added data from our log files and Ahrefs’ Site Audit, spotting these URLs is straightforward.

Head to the “Crawl budget wastage” tab, and you’ll find highly crawled HTML files that return a 200 but are non-indexable.

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List of URLs with corresponding data like hits, etc

Now that you have this data, you’ll want to investigate why the bot is crawling the URL. Here are some common reasons:

  • It’s internally linked to.
  • It’s incorrectly included in XML sitemaps.
  • It has links from external sites.

It’s common for larger sites, especially those with faceted navigation, to link to many non-indexable URLs internally.

If the hit numbers in this report are very high and you believe you’re wasting your crawl budget, you’ll likely need to remove internal links to the URLs or block crawling with the robots.txt.

8. Monitor important URLs

If you have specific URLs on your site that are incredibly important to you, you may want to watch how often search engines crawl them.

The “URL monitor” tab does just that, plotting the daily trend of hits for up to five URLs that you can add.

Line graph showing daily trend of hits for 4 URLs

You can also filter by bot type, making it easy to monitor how often Bing or Google crawls a URL.

URL monitoring with dropdown option to filter by bot type

Sidenote.

You can also use this report to check URLs you’ve recently redirected. Simply add the old URL and new URL in the dropdown and see how quickly Googlebot notices the change.

Often, the advice here is that it’s a bad thing if Google doesn’t crawl a URL frequently. That simply isn’t the case.

While Google tends to crawl popular URLs more frequently, it will likely crawl a URL less if it doesn’t change often.

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Excerpt of Google article

Still, it’s helpful to monitor URLs like this if you need content changes picked up quickly, such as on a news site’s homepage.

In fact, if you notice Google is recrawling a URL too frequently, I’ll advocate for trying to help it better manage crawl rate by doing things like adding <lastmod> to XML sitemaps. Here’s what it looks like:

<?xml version="1.0" encoding="UTF-8"?>

<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">

  <url>

    <loc>https://www.logexample.com/example</loc>

    <lastmod>2022-10-04</lastmod>

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  </url>

</urlset>

You can then update the <lastmod> attribute whenever the content of the page changes, signaling Google to recrawl.

9. Find orphan URLs

Another way to use log files is to discover orphan URLs, i.e., URLs that you want search engines to crawl and index but haven’t internally linked to.

We can do this by checking for 200 status code HTML URLs with no internal links found by Ahrefs’ Site Audit.

You can see the report I’ve created for this named “Orphan URLs.”

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List of URLs with corresponding data like hits, etc

There is one caveat here. As Ahrefs hasn’t discovered these URLs but Googlebot has, these URLs may not be URLs we want to link to because they’re non-indexable.

I recommend copying and pasting these URLs using the “Custom URL list” functionality when setting up crawl sources for your Ahrefs project.

Page to set up crawl sources; text field to enter custom URLs

This way, Ahrefs will now consider these orphan URLs found in your log files and report any issues to you in your next crawl:

List of issues

10. Monitor crawling by directory

Suppose you’ve implemented structured URLs that indicate how you’ve organized your site (e.g., /features/feature-page/).

In that case, you can also analyze log files based on the directory to see if Googlebot is crawling certain sections of the site more than others.

I’ve implemented this kind of analysis in the “Directories — Overview” tab of the Google Sheet.

Table showing list of directories with corresponding data like organic traffic, inlinks, etc

You can see I’ve also included data on the number of internal links to the directories, as well as total organic traffic.

You can use this to see whether Googlebot is spending more time crawling low-traffic directories than high-value ones.

But again, bear in mind this may occur, as some URLs within specific directories change more often than others. Still, it’s worth further investigating if you spot an odd trend.

In addition to this report, there is also a “Directories — Crawl trend” report if you want to see the crawl trend per directory for your site.

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Line graph showing crawl trend per directory

11. View Cloudflare cache ratios

Head to the “CF cache status” tab, and you’ll see a summary of how often Cloudflare is caching your files on the edge servers.

Bar chart showing how often Cloudflare is caching files on the edge servers

When Cloudflare caches content (HIT in the above chart), the request no longer goes to your origin server and is served directly from its global CDN. This results in better Core Web Vitals, especially for global sites.

Sidenote.

 It’s also worth having a caching setup on your origin server (such as Varnish, Nginx FastCGI, or Redis full-page cache). This is so that even when Cloudflare hasn’t cached a URL, you’ll still benefit from some caching.

If you see a large amount of “Miss” or “Dynamic” responses, I recommend investigating further to understand why Cloudflare isn’t caching content. Common causes can be:

  • You’re linking to URLs with parameters in them – Cloudflare, by default, passes these requests to your origin server, as they’re likely dynamic.
  • Your cache expiry times are too low – If you set short cache lifespans, it’s likely more users will receive uncached content.
  • You aren’t preloading your cache – If you need your cache to expire often (as content changes frequently), rather than letting users hit uncached URLs, use a preloader bot that will prime the cache, such as Optimus Cache Preloader.

Sidenote.

 I thoroughly recommend setting up HTML edge-caching via Cloudflare, which significantly reduces TTFB. You can do this easily with WordPress and Cloudflare’s Automatic Platform Optimization.

12. Check which bots crawl your site the most

The final report (found in the “Bots — Overview” tab) shows you which bots crawl your site the most:

Pie chart showing Googlebot crawls site the most, as compared to Bingbot

In the “Bots — Crawl trend” report, you can see how that trend has changed over time.

Stacked bar chart showing how crawl trend changes over time

This report can help check if there’s an increase in bot activity on your site. It’s also helpful when you’ve recently made a significant change, such as a URL migration, and want to see if bots have increased their crawling to collect new data.

Final thoughts

You should now have a good idea of the analysis you can do with your log files when auditing a site. Hopefully, you’ll find it easy to use my template and do this analysis yourself.

Anything unique you’re doing with your log files that I haven’t mentioned? Tweet me.

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Top Priorities, Challenges, And Opportunities

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Top Priorities, Challenges, And Opportunities

The world of search has seen massive change recently. Whether you’re still in the planning stages for this year or underway with your 2024 strategy, you need to know the new SEO trends to stay ahead of seismic search industry shifts.

It’s time to chart a course for SEO success in this changing landscape.

Watch this on-demand webinar as we explore exclusive survey data from today’s top SEO professionals and digital marketers to inform your strategy this year. You’ll also learn how to navigate SEO in the era of AI, and how to gain an advantage with these new tools.

You’ll hear:

  • The top SEO priorities and challenges for 2024.
  • The role of AI in SEO – how to get ahead of the anticipated disruption of SGE and AI overall, plus SGE-specific SEO priorities.
  • Winning SEO resourcing strategies and reporting insights to fuel success.

With Shannon Vize and Ryan Maloney, we’ll take a deep dive into the top trends, priorities, and challenges shaping the future of SEO.

Discover timely insights and unlock new SEO growth potential in 2024.

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View the slides below or check out the full webinar for all the details.

Join Us For Our Next Webinar!

10 Successful Ways To Improve Your SERP Rankings [With Ahrefs]

Reserve your spot and discover 10 quick and easy SEO wins to boost your site’s rankings.

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E-E-A-T’s Google Ranking Influence Decoded

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E-E-A-T's Google Ranking Influence Decoded

The idea that something is not a ranking factor that nevertheless plays a role in ranking websites seems to be logically irreconcilable. Despite seeming like a paradox that cancels itself out, SearchLiaison recently tweeted some comments that go a long way to understanding how to think about E-E-A-T and apply it to SEO.

What A Googler Said About E-E-A-T

Marie Haynes published a video excerpt on YouTube from an event at which a Googler spoke, essentially doubling down on the importance of E-A-T.

This is what he said:

“You know this hasn’t always been there in Google and it’s something that we developed about ten to twelve or thirteen years ago. And it really is there to make sure that along the lines of what we talked about earlier is that it really is there to ensure that the content that people consume is going to be… it’s not going to be harmful and it’s going to be useful to the user. These are principles that we live by every single day.

And E-A-T, that template of how we rate an individual site based off of Expertise, Authoritativeness and Trustworthiness, we do it to every single query and every single result. So it’s actually very pervasive throughout everything that we do .

I will say that the YMYL queries, the Your Money or Your Life Queries, such as you know when I’m looking for a mortgage or when I’m looking for the local ER,  those we have a particular eye on and we pay a bit more attention to those queries because clearly they’re some of the most important decisions that people can make.

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So I would say that E-A-T has a bit more of an impact there but again, I will say that E-A-T applies to everything, every single query that we actually look at.”

How can something be a part of every single search query and not be a ranking factor, right?

Background, Experience & Expertise In Google Circa 2012

Something to consider is that in 2012 Google’s senior engineer at the time, Matt Cutts, said that experience and expertise brings a measure of quality to content and makes it worthy of ranking.

Matt Cutts’ remarks on experience and expertise were made in an interview with Eric Enge.

Discussing whether the website of a hypothetical person named “Jane” deserves to rank with articles that are original variations of what’s already in the SERPs.

Matt Cutts observed:

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“While they’re not duplicates they bring nothing new to the table.

Google would seek to detect that there is no real differentiation between these results and show only one of them so we could offer users different types of sites in the other search results.

They need to ask themselves what really is their value add? …they need to figure out what… makes them special.

…if Jane is just churning out 500 words about a topic where she doesn’t have any background, experience or expertise, a searcher might not be as interested in her opinion.”

Matt then cites the example of Pulitzer Prize-Winning movie reviewer Roger Ebert as a person with the background, experience and expertise that makes his opinion valuable to readers and the content worthy of ranking.

Matt didn’t say that a webpage author’s background, experience and expertise were ranking factors. But he did say that these are the kinds of things that can differentiate one webpage from another and align it to what Google wants to rank.

He specifically said that Google’s algorithm detects if there is something different about it that makes it stand out. That was in 2012 but not much has changed because Google’s John Mueller says the same thing.

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For example, in 2020 John Mueller said that differentiation and being compelling is important for getting Google to notice and rank a webpage.

“So with that in mind, if you’re focused on kind of this small amount of content that is the same as everyone else then I would try to find ways to significantly differentiate yourselves to really make it clear that what you have on your website is significantly different than all of those other millions of ringtone websites that have kind of the same content.

…And that’s the same recommendation I would have for any kind of website that offers essentially the same thing as lots of other web sites do.

You really need to make sure that what you’re providing is unique and compelling and high quality so that our systems and users in general will say, I want to go to this particular website because they offer me something that is unique on the web and I don’t just want to go to any random other website.”

In 2021, in regard to getting Google to index a webpage, Mueller also said:

“Is it something the web has been waiting for? Or is it just another red widget?”

This thing about being compelling and different than other sites, it’s something that’s been a part of Google’s algorithm awhile, just like the Googler in the video said, just like Matt Cutts said and exactly like what Mueller has said as well.

Are they talking about signals?

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E-EA-T Algorithm Signals

We know there’s something in the algorithm that relates to someone’s expertise and background that Google’s looking for. The table is set and we can dig into the next step of what it all means.

A while back back I remember reading something that Marie Haynes said about E-A-T, she called it a framework. And I thought, now that’s an interesting thing she just did, she’s conceptualizing E-A-T.

When SEOs discussed E-A-T it was always in the context of what to do in order to demonstrate E-A-T. So they looked at the Quality Raters Guide for guidance, which kind of makes sense since it’s a guide, right?

But what I’m proposing is that the answer isn’t really in the guidelines or anything that the quality raters are looking for.

The best way to explain it is to ask you to think about the biggest part of Google’s algorithm, relevance.

What’s relevance? Is it something you have to do? It used to be about keywords and that’s easy for SEOs to understand. But it’s not about keywords anymore because Google’s algorithm has natural language understanding (NLU). NLU is what enables machines to understand language in the way that it’s actually spoken (natural language).

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So, relevance is just something that’s related or connected to something else. So, if I ask, how do I satiate my thirst? The answer can be water, because water quenches the thirst.

How is a site relevant to the search query: “how do I satiate my thirst?”

An SEO would answer the problem of relevance by saying that the webpage has to have the keywords that match the search query, which would be the words “satiate” and “thirst.”

The next step the SEO would take is to extract the related entities for “satiate” and “thirst” because every SEO “knows” they need to do entity research to understand how to make a webpage that answers the search query, “How do I satiate my thirst?”

Hypothetical Related entities:

  • Thirst: Water, dehydration, drink,
  • Satiate: Food, satisfaction, quench, fulfillment, appease

Now that the SEO has their entities and their keywords they put it all together and write a 600 word essay that uses all their keywords and entities so that their webpage is relevant for the search query, “How do I satiate my thirst?”

I think we can stop now and see how silly that is, right? If someone asked you, “How do I satiate my thirst?” You’d answer, “With water” or “a cold refreshing beer” because that’s what it means to be relevant.

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Relevance is just a concept. It doesn’t have anything to do with entities or keywords in today’s search algorithms because the machine is understanding search queries as natural language, even more so with AI search engines.

Similarly, E-E-A-T is also just a concept. It doesn’t have anything to do with author bios, LinkedIn profiles, it doesn’t have anything at all to do with making your content say that you handled the product that’s being reviewed.

Here’s what SearchLiaison recently said about an E-E-A-T, SEO and Ranking:

“….just making a claim and talking about a ‘rigorous testing process’ and following an ‘E-E-A-T checklist’ doesn’t guarantee a top ranking or somehow automatically cause a page to do better.”

Here’s the part where SearchLiaison ties a bow around the gift of E-E-A-T knowledge:

“We talk about E-E-A-T because it’s a concept that aligns with how we try to rank good content.”

E-E-A-T Can’t Be Itemized On A Checklist

Remember how we established that relevance is a concept and not a bunch of keywords and entities? Relevance is just answering the question.

E-E-A-T is the same thing. It’s not something that you do. It’s closer to something that you are.

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SearchLiaison elaborated:

“…our automated systems don’t look at a page and see a claim like “I tested this!” and think it’s better just because of that. Rather, the things we talk about with E-E-A-T are related to what people find useful in content. Doing things generally for people is what our automated systems seek to reward, using different signals.”

A Better Understanding Of E-E-A-T

I think it’s clear now how E-E-A-T isn’t something that’s added to a webpage or is something that is demonstrated on the webpage. It’s a concept, just like relevance.

A good way to think o fit is if someone asks you a question about your family and you answer it. Most people are pretty expert and experienced enough to answer that question. That’s what E-E-A-T is and how it should be treated when publishing content, regardless if it’s YMYL content or a product review, the expertise is just like answering a question about your family, it’s just a concept.

Featured Image by Shutterstock/Roman Samborskyi

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Google Announces A New Carousel Rich Result

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Google Announces A New Carousel Rich Result

Google announced a new carousel rich result that can be used for local businesses, products, and events which will show a scrolling horizontal carousel displaying all of the items in the list. It’s very flexible and can even be used to create a top things to do in a city list that combines hotels, restaurants, and events. This new feature is in beta, which means it’s being tested.

The new carousel rich result is for displaying lists in a carousel format. According to the announcement the rich results is limited to the following types:

LocalBusiness and its subtypes, for example:
– Restaurant
– Hotel
– VacationRental
– Product
– Event

An example of subtypes is Lodgings, which is a subset of LocalBusiness.

Here is the Schema.org hierarchical structure that shows the LodgingBusiness type as being a subset of the LocalBusiness type.

  • Thing > Organization > LocalBusiness > LodgingBusiness
  • Thing > Place > LocalBusiness > LodgingBusiness

ItemList Structured Data

The carousel displays “tiles” that contain information from the webpage that’s about the price, ratings and images. The order of what’s in the ItemList structured data is the order that they will be displayed in the carousel.

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Publishers must use the ItemList structured data in order to become eligible for the new rich result

All information in the ItemList structured data must be on the webpage. Just like any other structured data, you can’t stuff the structured data with information that is not visible on the webpage itself.

There are two important rules when using this structured data:

  1. 1. The ItemList type must be the top level container for the structured data.
  2. 2. All the URLs of in the list must point to different webpages on the same domain.

The part about the ItemList being the top level container means that the structured data cannot be merged together with another structured data where the top-level container is something other than ItemList.

For example, the structured data must begin like this:

<script type="application/ld+json"> { "@context": "https://schema.org", "@type": "ItemList", "itemListElement": [ { "@type": "ListItem", "position": 1,

A useful quality of this new carousel rich result is that publishers can mix and match the different entities as long as they’re within the eligible structured data types.

Eligible Structured Data Types

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  • LocalBusiness and its subtypes
  • Product
  • Event

Google’s announcement explains how to mix and match the different structured data types:

“You can mix and match different types of entities (for example, hotels, restaurants), if needed for your scenario. For example, if you have a page that has both local events and local businesses.”

Here is an example of a ListItem structured data that can be used in a webpage about Things To Do In Paris.

The following structured data is for two events and a local business (the Eiffel Tower):

<script type="application/ld+json"> { "@context": "https://schema.org", "@type": "ItemList", "itemListElement": [ { "@type": "ListItem", "position": 1, "item": { "@type": "Event", "name": "Paris Seine River Dinner Cruise", "image": [ "https://example.com/photos/1x1/photo.jpg", "https://example.com/photos/4x3/photo.jpg", "https://example.com/photos/16x9/photo.jpg" ], "offers": { "@type": "Offer", "price": 45.00, "priceCurrency": "EUR" }, "aggregateRating": { "@type": "AggregateRating", "ratingValue": 4.2, "reviewCount": 690 }, "url": "https://www.example.com/event-location1" } }, { "@type": "ListItem", "position": 2, "item": { "@type": "LocalBusiness", "name": "Notre-Dame Cathedral", "image": [ "https://example.com/photos/1x1/photo.jpg", "https://example.com/photos/4x3/photo.jpg", "https://example.com/photos/16x9/photo.jpg" ], "priceRange": "$", "aggregateRating": { "@type": "AggregateRating", "ratingValue": 4.8, "reviewCount": 4220 }, "url": "https://www.example.com/localbusiness-location" } }, { "@type": "ListItem", "position": 3, "item": { "@type": "Event", "name": "Eiffel Tower With Host Summit Tour", "image": [ "https://example.com/photos/1x1/photo.jpg", "https://example.com/photos/4x3/photo.jpg", "https://example.com/photos/16x9/photo.jpg" ], "offers": { "@type": "Offer", "price": 59.00, "priceCurrency": "EUR" }, "aggregateRating": { "@type": "AggregateRating", "ratingValue": 4.9, "reviewCount": 652 }, "url": "https://www.example.com/event-location2" } } ] } </script>

Be As Specific As Possible

Google’s guidelines recommends being as specific as possible but that if there isn’t a structured data type that closely matches with the type of business then it’s okay to use the more generic LocalBusiness structured data type.

“Depending on your scenario, you may choose the best type to use. For example, if you have a list of hotels and vacation rentals on your page, use both Hotel and VacationRental types. While it’s ideal to use the type that’s closest to your scenario, you can choose to use a more generic type (for example, LocalBusiness).”

Can Be Used For Products

A super interesting use case for this structured data is for displaying a list of products in a carousel rich result.

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The structured data for that begins as a ItemList structured data type like this:

<script type="application/ld+json"> { "@context": "https://schema.org", "@type": "ItemList", "itemListElement": [ { "@type": "ListItem", "position": 1, "item": { "@type": "Product",

The structured data can list images, ratings, reviewCount, and currency just like any other product listing, but doing it like this will make the webpage eligible for the carousel rich results.

Google has a list of recommended recommended properties that can be used with the Products version, such as offers, offers.highPrice, and offers.lowPrice.

Good For Local Businesses and Merchants

This new structured data is a good opportunity for local businesses and publishers that list events, restaurants and lodgings to get in on a new kind of rich result.

Using this structured data doesn’t guarantee that it will display as a rich result, it only makes it eligible for it.

This new feature is in beta, meaning that it’s a test.

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Read the new developer page for this new rich result type:

Structured data carousels (beta)

Featured Image by Shutterstock/RYO Alexandre

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