Google has been releasing new features in the search results more and more recently that can have a big impact on SERP treatment, click-through rate, and potentially traffic. Three of those features are part of Google’s “best answer carousels” and include Q&A, How-to, and FAQ snippets. Q&A has been live for a while already, while How-to and FAQ were just rolled out during Google I/O. Note, you can read my post about How-to snippets to learn more about how they work, what they look like, etc.

I have several clients heavily using these formats, so I’ve been analyzing their performance via Google Search Console (GSC) recently — via the new enhancement reports and the Performance reporting. For example, once you start marking up pages using Q&A, How-to, or FAQ markup, you will see new reports show up under the Enhancements tab in GSC. And those reports can be very helpful for understanding errors, warnings, and valid pages.

How To Analyze Performance In GSC By Search Feature:
From a clicks, impressions, and CTR standpoint, you can check the Performance report to view your data over time. Note, if you have Discover data, then there will be two reports under Performance. The first will say Search Results and the second will be titled Discover.

Once in the Performance report (or the “Performance in search results” report), the Search Appearance tab enables you to drill into data by specific feature. You can see that the site from earlier has both How-to and Q&A results. If you click each category title, then you will be isolating that search feature in the reporting (i.e. the reports will be filtered by that search feature). So, you can view queries, landing pages, etc. for just Q&A or How-to results. This applies to AMP as well.

The 1K Row Limit In GSC. The Bane Of A Site Owner’s Existence
Filtering the reporting by search feature is powerful, but remember, GSC only provides one thousand results by report in the web UI and you can only export those one thousand results. For smaller sites, that should be fine. But for larger-scale sites with thousands, tens of thousands, or more listings, then the reporting can be extremely limiting.

For situations like that, what’s a site owner to do??

Analytics Edge To The Rescue Again. Exporting Beyond 1K Results By Search Feature:
I’ve written several posts about Analytics Edge before, and it’s still my go-to tool for exporting data in bulk from GSC. It’s a powerful Excel plugin that enables you to quickly and efficiently export bulk data from GSC, GA, and more.

Below, I’ll take you step-by-step through exporting your data by Search Appearance from GSC. If you’re a large-scale site that’s using Q&A, How-to, FAQ, and even AMP, then you’re going to dig this. Let’s jump in.

How to use Analytics Edge to bulk export data by Search Appearance:
Note, this will be a two-phase approach. The first run will enable us to pull all Search Appearance codes for the specific property in GSC. Then the second run will enable us to pull all data by that Search Appearance code.

Phase One:

1. Download and install the Analytics Edge free or core add-in. There’s a free trial for the core add-in if you wanted to simply test it out. But the free add-in will work as well (just with less functionality). After installing the add-in, you should register it in Excel.
2. Next, install the Search Console connector by clicking the License/Update button in the menu. You can watch this short video to learn how to install connectors. You can click the Google Search row to pull up the connector details (where you can choose to install that connector).
3. Once you install Analytics Edge and the Search Console connector, access the options in the Analytics Edge menu at the top of Excel. Click the Google Search drop-down and select Accounts. This is where you will connect Analytics Edge with the Google account(s) you want to download data from. Go through the process of connecting the Google account you want to work with. You can also make one account the default, which will save you time in the future.
4. Once you connect your account, click Google Search in the Connectors section, and then Search Analytics.
5. Name your Macro and click OK.
6. Select an account and then a property from GSC.
7. We will use a two-phase approach for exporting data by Search Appearance. First, we are going to view the various options we have under Search Appearance (there will be codes that show up representing each SERP feature available to a property). We will use these codes during our second run to pull all data for each specific search feature (like How-to, Q&A, FAQ, AMP, etc.)
8. Under the Fields tab, select searchAppearance, which will move that option to the Dimensions window.
9. For the Dates tab, you can leave “Last 3 Months” active (which is the default).
10. Leave everything else the same and click “Finish”.
11. Analytics Edge will return all of the possible Search Appearance codes for the site for the time period you selected. For example, in the screenshot below, there were impressions and/or clicks for AMP (article and non-rich results), Q&A, How-To, and others for the property I selected.
12. Copy the codes from the searchAppearance column to a text file so you can reference them in phase two of our tutorial. You will need these codes to export all data by that specific search feature.

Phase Two:

1. Now we are going to use the searchAppearance codes to export data in bulk for a specific search feature. Click Google Search again, and then Search Analytics. Choose an account and a property again. When you get to the options screen, select the dimensions you want to export (in the Fields tab). For this example, let’s select query (to see the queries yielding How-to snippets in the search results).
2. Next, go to the Filters tab and find the Appearance field. In that field, enter TPF_HOWTO, which is the code for How-to snippets. If you want to export data for another search feature, just use that code instead.
3. Next, select the dates you want to run the report for. For this example, I’ll select “Last 28 days”.
4. Then under Sort/Count, select clicks and then descending in the “sort by” dropdown. This will sort the table by the queries with the most clicks over the past 28 days (that yield How-to snippets).
5. Then click “Finish”.
6. Analytics Edge will run and export all of the queries yielding How-to snippets. This can take a bit of time (from a few seconds to a minute or longer) depending on how large the site is and how much data needs to be exported. Note, just a sample of data will be presented in memory in the worksheet (and highlighted in green). You need to “write to worksheet” to show all of the data.
7. To do that click File and then “Write Worksheet”. Name the worksheet and click OK. You will now see a new worksheet containing all of your data. For this example, I see 26K+ queries that have yielded How-to snippets over the past 28 days. Yep, over 26K!
8. Congratulations! You just exported search feature data from GSC and blew by the 1K row limit!

Tracking, Using, and Learning From The Data:
Once you export your data by Search Appearance in bulk, you will have full access to all of the queries yielding Q&A, How-To, FAQ snippets, AMP, and more. You can track their position, double check the SERPs to understand the SERP treatment for each feature, understand the click-through rate for each snippet, and more.

For example, you might find that “list treatment” for How-tos is yielding a higher click through rate than the carousel treatment. Or you might find that a certain How-to has a featured snippet in addition to the How-to snippet (a How-to/featured snippet combo). And then you can check metrics based on that situation. You get the picture!

You can see an example of a How-to/featured snippet combo below:

My recommendation is to export data by each search feature for the past 28 days and start digging into the data. Then regularly export the data (like weekly) to understand the changes over time. E.g. changes in metrics, SERP treatment, and more.

Summary – Free Yourself From the 1K Row Limit In GSC By Exporting SERP Feature Data Via Analytics Edge
Now that more and more features are hitting the SERPs, using a tool like Analytics Edge can help you export all of your data, versus just one thousand rows per report. And when you export all of the queries and landing pages per SERP feature, you can glean more insights from the data. If you are using AMP, How-to, Q&A, or FAQs, then I highly recommend exporting your data via a tool like Analytics Edge. I think you’ll dig it.

GG

Ah, the holidays. Who doesn’t love a festive atmosphere, ugly Christmas sweaters, eggnog, singing Christmas carols, and major performance problems that can take down your site?

Wait, what was that last part??

The holidays are always interesting for me SEO-wise. Every few years, I receive an SOS from a site owner right around Christmas Day based on a weird drop in traffic or rankings from Google. This year, it was on December 27 from a company I helped several years ago. It’s a large-scale site that has seen a lot of volatility historically, but has done a good job at turning things around. They have battled major algorithm updates in the past, and now battle new SERP features from Google itself.

Just two days after Christmas, I received a message from the site owner asking if there was some type of update over the holidays. Traffic dipped sharply on Christmas Day, which it typically wouldn’t do based on their niche, and had gone down more and more since. Traffic typically only goes down by about 20% on Christmas Day and it was down 50% this year. That’s typically not the case from a historical perspective for the site and they were worried that an algorithm update impacted the site again.

So I rushed to check their stats, noticed the drop in traffic, and quickly started checking the sources of traffic that dropped. The first thing I noticed was that the drop wasn’t just from Google… it was from all sources. That’s actually a good thing and we could quickly rule out some type of Google algorithm update.

Then I started checking the top landing pages that dropped and it wasn’t long before I noticed a serious performance problem. Some of the pages simply wouldn’t load. Then I searched Google for queries leading to the pages and tried to click through from the SERPs. I experienced the same issue… the site was simply hourglassing.

I messaged the site owner and explained the major performance problems I was experiencing and that the drop was from all traffic sources, and not just from Google. He took that information to his CTO so they could dig in and start isolating the problem. It wasn’t long before I heard back.

A Holly Jolly Load-Balancer Christmas!
No, that’s not the name of the next Christmas Vacation movie, although it does have a nice ring to it. :) The site owner and CTO uncovered a load balancer issue that was causing the performance problems we were seeing on the site. And that was causing a big drop in traffic as visitors couldn’t load many of the pages. And again, this is a site that people visit during the holidays, and on Christmas day, based on the type of content the site provides.

So, the good news is that it wasn’t some type of evil elf algorithm update. But the bad news was that the load balancer issue was causing many pages not to load for users and Googlebot. My client went to work on resolving the load balancer issue, but they couldn’t help but wonder how Google would treat the site from a rankings perspective.

For example, when Google sees a major performance problem over time, and it knows users cannot load the pages, some important questions come to mind. Will Google drop the site’s rankings, will the site plummet in the short-term, only to come back when the performance problems are corrected, will there be long-term damage SEO-wise, and how will crawling and indexing be impacted?

We’ve heard Google’s John Mueller explain situations related to this in the past. For example, John explained that Google can slow crawling when it comes across many 5XX errors. Here’s a tweet from John about this:

And that goes for 503s as well (a response code sites can return when maintenance is being completed and the site is down). John has explained that if Google sees 503s for an extended period of time, it can start dropping urls from the index. Note, returning 503s for a short period of time is totally fine (and is a good approach to use when you know your site will be down for maintenance). Just make sure you’re not returning 503s for an extended period of time.

Since this was a load balancer issue, and some visitors were able to load pages correctly, my client didn’t take the site offline (and didn’t use 503s). But it’s important to understand how Google would treat a site being down over an extended period of time. Here’s a video where John explains this (at 37:28 in the video):

And here’s John explaining how Google can automatically slow crawling when it sees that urls are temporarily unavailable. He also explains that Google will stop crawling if it sees that happening for a robots.txt file. Then Google will automatically increase crawling when the urls return 200s again. Here’s the video of John explaining this (at 38:43 in the video):

So what would happen in this case? Needless to say, we were eager to find out.

Tracking The SEO Impact Of Major Performance Problems
As you can probably guess, I was ultra-interested in seeing how this played out SEO-wise. So, I began tracking the situation on several levels to see how the load balancer issue was impacting the site from an SEO standpoint. For example, would rankings drop, would crawling slow down, and how would this all look when the performance problems were fixed?

Below, I’ll take you through the timeline, with data and screenshots, to show you how Google treated the problem. Note, every site is different, so this may not apply to all performance problems you run into. But, it should help you understand how those performance problems could impact crawling, indexing, and ranking. It’s also worth noting that the duration of performance problems would surely impact this situation. For this case, the site owner and CTO completely fixed the problem within seven days. But, it wasn’t all fixed at one time. More on that soon. Last, I unfortunately don’t have logs from the site yet. I’m still working on getting them, though, and will update this post if I do.

Blue Christmas – The Timeline of Events (with data and screenshots)
First, here is the drop in traffic when comparing year over year. The site usually doesn’t drop very much during Christmas Day (or week). You can see a seasonal drop of about 20% when compared to normal weeks, where this year yielded a drop of 50%. Yep, something was up…

Crawl Stats in GSC:
Here was the spike in time downloading a page and the drop in pages crawled per day. Pretty amazing to see that graph, right?

And here were the impressions and clicks in GSC (which remained strong). This supports the notion that rankings were not being impacted during the performance problem. Impressions would have dropped if that were the case. I was also checking rankings manually and saw rankings remain strong overall. It seems that Google was pretty cool with understanding there was a performance problem and didn’t quickly impact rankings (even when it knew some users were running into page loading problems).

And here was search visibility trending in SEMrush over the timeframe, which supports the fact that rankings were not impacted in the short-term. Search visibility was stable throughout the performance problem:

And here is Sistrix trending, which is also stable throughout the problem:

Note, the load balancer problem was not fixed all at one time. The situation improved over a five to seven-day period. So here are the crawl stats as the issue started to get resolved. Notice crawling increases, but not back to normal. That’s because the performance problems were still there to some extent. Notice time downloading a page improves, but also not back to normal.

And then once the problem was completely fixed, notice that the crawl stats return to normal. Time downloading a page drops back down to normal levels and pages crawled per day rise to normal levels. Awesome, all is good again in Google Land.

And here is what Google organic traffic looked like from before the load balancer issue to after it was resolved. Notice the drop during Christmas, a further drop, and then traffic returns to normal after the problem was fixed. There was no impact to Google organic traffic, rankings, etc. based on the performance problem. That was great to see.

Key learnings… and Spiked Eggnog:
Needless to say, it was fascinating to watch how Google reacted to the major performance problems over time. Here are some key learnings from the situation:

• Google understands that temporary glitches can happen (like the performance problems this site was experiencing).
• Google can slow crawling, when needed, and check back to see when it can crawl more. The crawl stats in GSC clearly showed that happening.
• For this situation (only a week or so), the site wasn’t impacted SEO-wise. Rankings remained strong, search visibility was stable, and as the problem was fixed, Google returned crawling back to normal levels.
• Google organic traffic then returned to normal levels as the performance problem was fixed completely. There was no impact rankings-wise based on this incident.
• That said, if this problem remained beyond a week or two, it’s hard to say how rankings would be impacted. Google could very well begin to drop rankings as it wouldn’t want to send users to a site or pages that don’t resolve. But, if you have a short-term performance issue, it seems you should be ok. I would just work to fix the problems as quickly as you can.
• This is a reminder that Murphy’s Law for SEO is real. The load balancer problem happened on Christmas Day. You just need to be prepared for Murphy to pay a visit. And then move quickly to rectify the problems he brings along.

Summary – All I want for Christmas is to never deal with a load balancer issue again.
If you run into serious performance problems and are worried about the SEO-impact, know that Google does understand that bad things happen from time to time. As Google’s John Mueller explained, Google can slow crawling while the problems exist and then check back to see when it can return crawling to normal.

For this specific case, that’s exactly what we saw. Rankings and search visibility remained strong, but crawling slowed. Then as the performance problems were fixed, crawling returned back to normal. And all was good again in Google Land.

So, until next holiday season… here’s ho-ho-hoping you don’t run into this type of problem anytime soon. I know everyone involved with this case feels the same way. :)

GG

If you are working on a large-scale site, you need to be very careful that you don’t create infinite spaces. That’s when a site generates a near-endless list of urls that Google can end up crawling. Google does not want to churn through endless urls and it can cause problems on several levels SEO-wise. That’s why they detail infinite spaces in the search console help center and they also wrote a blog post specifically about the problem.

Google can end up wasting resources crawling many urls that are near-identical or low-quality. And that can flood Google’s index with thin and low-quality content.

During a recent audit on a site that has seen massive volatility over the past few years during major algorithm updates, I noticed a certain page type that I thought could be problematic. This was surfaced after the initial crawl (which was just a few hundred thousand urls out of 30+ million indexed). I saw enough of the problematic page type that I flagged it and then decided to dig in further.

The Core Problem: Autogenerating URLs
The core problem with the page type was that the site was autogenerating urls based on site searches, which ended up adding many thin or near-empty pages to the site (that were indexable). And even the urls that did contain some content didn’t really make sense to have on the site since they were so general (and even ridiculous in some cases). This created a near-infinite spaces situation with millions of urls being generated, and many of them with major quality problems.

I sent through initial findings to my client and we decided to get on a call to discuss the issue, along with a number of other important findings from my initial analysis. After speaking with my client and his tech lead, I found out the problem could be impacting up to 10 million urls. And with the site seeing major volatility during multiple major algorithms updates over the past several years, I couldn’t help but think the infinite spaces problem could be heavily contributing to that volatility.

To Infinity and… Behind? The Plan of Attack:
We quickly decided that I should dig into the situation full-blast to learn more about the autogenerated url problem. I literally left the call and started analyzing the pages using a number of tools. This was a process I’ve used a number of times before, so I thought it would be helpful to write a post covering it. It’s a strong way to use a powerful SEO software stack to surface and analyze an infinite spaces problem.

I’ll provide the process below, along with the SEO tools I used (which include both free and paid tools). The combination enabled me to tell a powerful story quickly and efficiently. My hope is that you can use this process, as well, in case you run across a problem that’s creating infinite spaces.

1) Starting with an enterprise crawl via DeepCrawl and Screaming Frog
The first step was running an enterprise crawl. The site has over 30 million pages indexed, but I almost never start by crawling millions of pages at once. You can definitely get a good feel for a site by crawling a few hundred thousand pages to start, and then perform surgical crawls based on problematic areas you surface. It’s a quicker and smarter way to crawl when you’re just starting an engagement.

The initial enterprise crawl helped surface many thin or near-empty pages, and those urls were the problematic page type I mentioned earlier. When digging into those urls, you could clearly see the infinite spaces problem, how the pages were being crafted, and how they were linking to more and more of the autogenerated urls.

I also ran a smaller crawl using Screaming Frog. I crawled 50K urls just to see what our amphibious friend would surface. And again, you could see the autogenerated results rearing its ugly head. So from a crawling perspective, there was a lot of evidence of the page type spawning many low-quality urls. Next up was to check traffic levels to the site for that page type.

Before moving on, I exported a filtered list of the problematic pages from the crawl data. You can do this in both DeepCrawl and Screaming Frog. You’ll need those urls for a step later in the process. More about that soon.

2) Google Analytics for trending and landing page data
My next move was to track trending over time to the problem urls to view how much traffic was being delivered there via Google organic search. I wanted to see how many of the pages were low-quality, how many were driving traffic versus the number indexed, was there serious volatility for the page type during major algorithm updates, and so on.

When checking trending overall, there was a clear drop from the February 7, 2017 update (which was a massive update). I wrote a post detailing that update, based on seeing a lot of volatility on sites across industries and countries. And when I isolated the problematic page type, the drop was even more distinct.

To isolate landing pages from Google organic, you can access Acquisition, All Traffic, Source/Medium, and then click on Google/Organic. Then you can dimension by landing page. But note, Google provides sampled data in this report for larger-scale sites. Just keep in mind that you are not seeing all of the data.

To view unsampled data, you can access Acquisition, All Traffic, Channels, Organic Search, and then dimension by landing page. But just keep in mind this report contains all organic search traffic and not just Google organic (although Google is a majority of organic search traffic for most sites).

When checking landing pages from Google organic to the problematic page type, I found only 7K urls that were driving traffic from Google organic. That’s out of hundreds of thousands indexed in just one area of the site. That’s a huge red flag by the way. Google doesn’t believe the content is strong enough to rank and drive traffic to, yet those pages are clogging up the index with many low quality urls. Remember, this problem could be impacting up to 10 million urls when you take the entire site into account.

Export Time:
Also, it was important for me to gather as many landing pages as possible, so I could trigger a subsequent crawl of those urls. Therefore, I exported all of the problematic landing pages from Google Analytics (from organic search) for further analysis. For larger-scale sites, I use Analytics Edge which enables me to tap into the API and export urls in bulk. It’s an amazing solution that I use heavily. I’ve also written several posts about it over the years.

Optional Step: You can also run a medieval Panda report to see the drop after specific algorithm updates. That will enable you to see the landing pages from organic search seeing the largest drop after the update rolled out. You can often find glaring quality problems on those pages. You can learn more about running a Panda report in my tutorial. And no, it’s not just tied to Panda. It can be used for any traffic drop you are seeing.

3) GSC – The NEW Search Analytics Report (with 16 months of data)
The next step I took was to dig into the new search console reporting. All site owners now have access to the new GSC and it contains some extremely powerful reporting. It’s not complete yet, which is why you also have access to the old GSC at the same time.

First, you now have 16 months of data to analyze in the Performance reporting! That’s a new name for the Search Analytics report from the old GSC. Having 16 months of data is important and can help you view trending over a much longer period of time versus the old GSC (which was limited to just 90 days). You can also compare timeframes over a longer period of time.

If you have an infinite spaces problem, and you can isolate the page type via url structure, then the you can view trending of impressions and clicks over the past 16 months for the page type. That can also help you identify impact during major algorithm updates.

Exporting via the Search Analytics API (Using Analytics Edge):
In addition, you can export ALL of your landing pages for that page type via the GSC API. Remember, we’ll need those urls in order to create a master list of urls. I’ll cover the surgical crawl in a later step. Note, the UI in the Performance Report and Search Analytics report only lets you export one thousand urls, which is limiting for larger-scale sites. But using a solution like Analytics Edge enables you to fully export your landing pages. Again, you can read my tutorial to learn more.

Just understand that the Search Analytics API only goes back 90 days for now. I believe Google is working on extending that to the 16-month timeframe soon. But at least you can get a feel for how many landing pages from Google organic fit under the problematic page type that’s creating infinite spaces.

4) Index Coverage – Excluded and Valid
As part of the new GSC, Google provides one of the most powerful new tools for site owners and SEOs. It’s called Index Coverage and it’s the old Index Status report on steroids. I’m part of the GSC beta group and I’ve been testing this for a while before the official launch. I can tell you, the reporting is packed with actionable data.

For example, you can drill into the pages that are valid and indexed, you can view errors by category, and you can view urls that have been excluded by Google by category. Yes, you are getting a rare view into how Google is treating urls and page types across your site. We have been asking for this type of reporting for a long time and the Index Coverage report delivers – big-time!

For our purposes today, we’ll focus on the Excluded and Valid categories. Since I knew there were many thin and low-quality pages due to the infinite spaces problem, I wanted to see how many were showing as being excluded by Google (essentially letting me know that Google decided to not index the urls for some reason).

It didn’t take long to see the problematic page type showing up in a number of reports. For example, the Soft 404s report had many of the urls in them. That’s because there were many urls being autogenerated without any content.

In addition, there were many showing up in the “submitted, but not indexed” category. Again, the site is providing the urls to Google (via sitemaps and via the internal navigation), yet Google has decided not to index many of them. It’s just more ammunition to take to your client, internal teams, etc. about the infinite spaces problem (if you need more ammunition).

Beyond the Excluded category, you can check the Valid category in the Index Coverage reporting and filter by the problematic page type to see how many of those pages are indexed.

Export Time: You can export urls per category in the new GSC. That’s awesome, but there are limitations you should be aware of. First, you can only export up to one thousand urls per report (unlike the Search Analytics API, which lets you export the whole enchilada). I would have to check with Google again, but I believe they are working on adding API access for the Index Coverage report. I’ll update this post after finding out more.

Second, your filters don’t stick when exporting, and that’s problematic given what we’re trying to do here. Since we are filtering by page type, it would be awesome for the export to isolate those pages. But it doesn’t right now. All of the top one thousand urls are exported per category versus just the problematic page types. I submitted feedback to the GSC product team about this, so we’ll see if the export functionality changes. But for now, the Index Coverage report is for analyzing the page type, while the Search Analytics API can be used for full exports.

5) Deduping landing pages, preparing for the surgical crawl
At this point, you should have analyzed trending for the specific page type and you have exported urls along the way. Now it’s time to create a master list of problematic urls so you can perform a surgical crawl. The surgical crawl will enable you to get a close-up view of the problem, along with any other issues plaguing that page type.

Excel is your friend for this task. Create a new spreadsheet and copy all of the worksheets you exported into that document. For example, you’ll use the Move or Copy functionality to copy the worksheet to our new document. Just right click on a worksheet tab and you’ll see “Move or Copy”.

Then create a new worksheet that contains all of the urls listed together. Since there will be overlap, you want to dedupe that list before crawling the urls. Click Data, and the Remove Duplicates. If you have a header row, make sure to check that box. Once you click OK, Excel will remove any duplicate urls. Now you have your final list for the surgical crawl.

6) Perform a surgical crawl of JUST problematic urls
Depending on how many urls you have, you can choose to run the crawl via an enterprise crawler like DeepCrawl or via a desktop crawler like Screaming Frog. You could also choose to run a large-scale crawl of all the urls via DeepCrawl while crawling a subset of the urls via Screaming Frog (just to get a look at the urls via both tools).

Once the crawls complete, you can dig into the data to surface problems.

For example, you might (and probably will) find massive quality problems, thin content, empty pages, canonical issues, duplication, and more. And remember, this is just a subset of the total pages indexed for the problematic page type! Again, this is more ammo for your conversation with the various teams at your company or with your client.

Next Steps – Preparing for battle and crafting your strategy
At this stage, you should have a boatload of intelligence about your infinite spaces problem. Every step you took will help you document the problem from several angles. And once you convey the situation to your client, dev team, c-level executives, etc., you need to tackle the problem head-on.

That includes deindexing as many of those urls as possible and then stopping the problem from surfacing again. That last part could include multiple steps, including changing functionality on the site and handling the urls via robots.txt. It depends on what you find based on your analysis.

For my situation, there was clearly a problem with the site autogenerating many urls. And only a small fraction of the urls are receiving traffic. Many of those pages are thin or low-quality. And the site can generate a near-endless list of these urls. I’m working with my client now on the final strategy, which will undoubtedly include deindexing many urls, refining functionality on the site that’s creating infinite spaces, and then disallowing urls from being crawled in the future.

But there are some important points to understand about this process. First, watch out for simply disallowing via robots.txt. I know many would move to do that immediately, but that’s not necessarily the best move right out of the gates. If you want to deindex the urls via noindexing or 404s/410s, which you should, then Googlebot wouldn’t be able to see the meta robots tag using noindex (or the 404s/410s) if you disallow via robots.txt.

I recommend keeping the directory open and letting Google deindex them over the long-term. Then you can disallow via robots.txt once they have been removed. That can take a while, so be patient. You can read my case study about removing a rogue subdomain to learn more about that.

Also, if the urls are in specific directories, then you could add those directories to GSC as a property. Then you could use the new Index Coverage and the old Index Status reports to monitor indexation. Many still don’t know that you can add directories as properties in GSC. I recommend doing that.

XML sitemaps can help:
Also, you could submit xml sitemaps with all the problematic urls you collected and then check the new Index Coverage report for indexation, errors, etc. This is another benefit of exporting and deduping all of the problematic pages from DeepCrawl, Screaming Frog, Google Analytics, Search Analytics in GSC, and then Index Coverage in GSC. It’s totally fine to temporarily submit a sitemap that leads to 404s, 410s, or pages being noindexed. That can help Google with discovery and could lead to quicker deindexation.

Clarifying the Remove URLs Tool in GSC:
You can also choose to remove the urls via the Remove URLs Tool in GSC (especially if they are in a specific directory). But be aware that the Remove URLs tool does not work the way that many think it does. It’s a temporary removal (90 days) and only removes the urls from the search results (and not Google’s index).

You still need to actually remove the pages via 404, 410, or the meta robots tag using noindex for the pages to truly be removed. That’s extremely important to know, or you can end up in the same situation you were in when you started if you don’t handle the urls at the root. For an infinite spaces situation, you could temporarily remove the urls via GSC so they don’t show in the search results, while at the same time handle them on the site via 404s, 410s, or by using the meta robots tag using noindex.

Summary – Don’t let infinite spaces get in your way SEO-wise
Again, creating infinite spaces can be a dangerous thing from an SEO perspective, as Google can end up crawling a near-endless list of low quality, thin, or similar urls. It’s important to surface the problem and the urls being generated in order to properly tackle the situation.

Using a powerful SEO software stack, you can identify, analyze, and then address the problem efficiently. If you feel you have an infinite spaces problem (or might have one), I recommend following the process I provided in this post soon. Don’t let infinite spaces negatively impact your site SEO-wise. You can start today by “measuring infinity”. Good luck.

GG