Using Google Search Console for SEO Tasks: 9 Quick Tips for Beginners to Experts
By Ethan Lazuk
Last updated:
Note: This was an early post in my blog. I might revisit it in the future to make it better, and more similar to how I write today. However, I also like the nostalgia of it. I’m sentimental. 😂 It’s not my best writing-wise, but the information about GSC is helpful, I promise. Hope you enjoy! — Ethan
Knowing how your website’s content is appearing in Google Search is fundamental for search engine optimization.
Google Search Console provides helpful information like if your content is indexed and eligible to appear in search, what queries the content is ranking for, whether your pages are trending up or down in visibility, and how much organic traffic you’re driving.
I’ve been a digital marketer since 2015, focusing on content writing initially in support of SEO and later on SEO strategies and tactics exclusively. In that time, the most important SEO tool I’ve used (and sometimes seen misapplied) has been Google Search Console.
If you’re new to using Google Search Console, it’s a free tool that marketers and SEOs can use to monitor how Google crawls and indexes a website’s content and how that website appears in Google Search, including its organic traffic, keyword performance, and any indexing issues that may be limiting or preventing the content’s visibility in search engine results pages (SERPs).
There are plenty of in-depth guides on Google Search Console available. A few I’d recommend include:
- Get started with Search Console – Google Search Central
- A Complete Google Search Console Guide For SEO Pros – Roger Montti, SJE
- How to use Google Search Console: a beginner’s guide – Yoast
- Google Search Console For Keyword Research – Olga Zarr, Seosly
- The SEO’s guide to Google Search Console – Anna Crowe, SEL
This article isn’t a comprehensive guide like those above. Rather, this is an overview of a few specific ways that I use GSC for SEO most commonly, as well as feedback on the ways that I have seen it misused the most.
Table of contents
In case you’re looking for specific sections, here are the tips I’ll cover:
- Filtering Traffic by Country
- Setting Accurate Date Comparisons
- Looking at Average Position and Clickthrough Rate
- Filtering by Device
- Identifying Striking Distance Keywords
- Finding New Content Topics
- Analyzing Groups of Pages
- Finding Indexing Issues
- Filtering Out Branded Keywords
1. Filtering traffic by country
A common oversight when first using Google Search Console is analyzing site traffic or keyword rankings globally instead of filtering for the specific country/countries the website targets.
The Performance tab is where you go in Google Search Console to look at organic website traffic and keyword performance on Google Search.
On the left hand side of the GSC interface, Performance is either its own tab below the Overview tab, or if your site gets Discover traffic, Performance will be its own section below URL inspection, in which case you’ll want to click on Search Results.
When you click into Performance (Search results), it will have two filters set by default:
- Search type: Web
- Date: Last 3 months
The next step should be to click “+ New”, then select “Country…”, and then choose the country you want to analyze traffic for. I’m U.S. based, so I select United States by default.
If you don’t typically filter by country, try scrolling down below the graph and clicking on the “COUNTRIES” tab. There, you’ll see how much of the website’s traffic comes from countries outside of your target market. It may surprise you.
Reporting on global traffic isn’t an issue if your website is truly international. But if it’s, say, a U.S.-based e-commerce retailer that only ships domestically, reporting on data from France or the Philippines may not give you an accurate representation of your “qualified” traffic or “meaningful” keyword rankings.
Here’s an example of a U.S.-based website. When it comes to reporting on traffic, there’s a 25% difference between having the United States filter enabled or not.
In actual terms, 18k is the site’s level of traffic. However, if we’re talking about traffic to help them meet their business goals, 13.5k is a more honest representation.
2. Setting accurate date comparisons
The GSC Date range filter allows you to filter by a single time period or set a comparison between two time periods.
Tip: Download the Easy Custom Comparison Chrome extension, as this allows you to quickly set custom comparison timeframes for period over period or year over year.
Comparison timeframes are especially helpful for analyzing changes in traffic levels or keyword rankings. I typically start with “Compare last 28 days to previous period” and then go more specific or broader from there.
One consideration when setting comparison time periods in GSC is factoring in variables like the day of the week, holidays, or other events that could influence traffic beyond just how the website appears on the SERPs.
For example, Google Analytics 4 has the ability to match the day of the week when doing, say, month-over-month comparisons. This is an important consideration when using GSC for reporting as well.
It’s common to report on month-over-month metrics for SEO. However, months often have different numbers of days or weekdays versus weekends. It’s helpful to consider this when looking at comparison dates data.
Another important consideration is official and unofficial Google algorithm updates. Core algorithm updates, for example, may take around two weeks to complete. (The March 2024 core update took 45 days.)
If you’re analyzing your performance data before and after a core algorithm update, consider having the starting period be at least on the day after the update is rolled out, and end the previous comparison period before the update started. I typically like to have two weeks’ of data (at least) before and after a core update.
3. Looking at average position and clickthrough rate
Google Search Console data can have a lot of nuance. One aspect where this is important is when reporting on Average Position or Clickthrough Rate. I’ve seen these added to reports at a site-wide level, with conclusions drawn such as, “average position was up 1% this month, implying our rankings are improving.”
The trouble is that these metrics have a lot of nuance. Say a website has five pages, and each ranks for 200 queries. Some of those queries might be relevant and rank in the top ten or five positions. Other queries might be loosely relevant and rank in position 50 or higher. If the SERPs change and fewer of the irrelevant queries appear, or if they move from position 50 to position 60, the average position will change. But in reality, the main queries for the page may have stayed in the same position or even improved.
Looking at position at a query vs. site-wide level can certainly be better, but again, say a website has three pages that rank for the same general query. If one of those pages, which drives all the traffic for the query, remains unchanged in position, but the other two pages move up or down, the average position changes at a query level, but that may not indicate what happened to traffic itself.
In light of these nuances, it can be helpful to look at average position first based on an individual query for a page, or a cluster of semantically synonymous queries for a page. And then additional or broader analysis can be done from there.
These results are shown for different queries for a particular URL filtered by country and device type:
Next we can set a date comparison and analyze whether CTR or position changed, based on the top traffic queries to the page:
The date range can be changed to week over week, month over month, or whatever period we’re reporting on or analyzing.
The same process is true for clickthrough rate (CTR). If a page suddenly starts ranking for more queries in position 20+, for example, that will likely lower the CTR with more impressions for results that aren’t likely driving clicks. However, core traffic to the page’s main queries could have remained steady, or the top-ranking queries may have even improved in position and driven more traffic, having a better CTR themselves. So, CTR, like position, should typically be looked at first on a query and page level, and then broadened from there.
4. Filtering by device
Keyword rankings can vary dramatically between device types. Mobile and desktop SERPs can have different layouts and features for the same queries, and results can change as well.
When looking at the average position or CTR for a query, it can be insightful to compare the desktop and mobile results.
For example, this query has an average position of 4.3 and a CTR of 0.5% for its main page. However, we see interesting data at the device level: the page ranks higher for the query on mobile than on desktop, and the traffic levels are considerably higher, implying mobile analysis is likely more valuable in this instance.
If you need to view a mobile SERP on your desktop while doing research, one quick way is to right-click and inspect the SERP, then use the toggle device setting in the dev tools and click refresh. I like to do this while signed in on Chrome as well as in an incognito window to compare results.
5. Identifying striking distance keywords
Today’s on-page SEO involves optimizing page content for topical clusters of semantically relevant keywords and related entities rather than targeting a single keyword.
To get a sense of this, use the page filter in the Performance report to filter by Exact URL and enter one of your best pages for traffic. Then scroll down to the queries and look at what drives traffic. You’ll likely see queries specific to the theme of the page (whether it’s a service, product, or blog post), as well as other queries that are either variations on that theme or perhaps even subtopics within the article that Google has chosen to rank the page for.
The position of a query that a page appears for can have a sizable impact on the clickthrough rate and level of traffic. For example, going from position 5 to 2 for one of the page’s most popular keywords can result in a dramatically improved level of clicks.
That’s where optimizing for striking-distance keywords comes into play.
Striking distance keywords are potentially valuable and relevant queries that a page ranks for currently but in slightly higher positions than desired; let’s say positions 5 through 15.
These are queries that a page could potentially rank better for if it was optimized for them, whether through higher quality or more relevant on-page content, headings, or structure, more incoming internal links with relevant anchor text, adding the key terms to the page title tag, or other SEO tactics.
To find striking-distance keyword opportunities in Google Search Console, filter the performance report for a particular page using the Exact URL filter. Next, scroll down to the QUERIES report, click the inverted pyramid in the top right, and select Position.
On the left hand side, change the Equals dropdown to say Smaller than, and then enter 15 (or whatever the top of your striking-distance range is). Then filter by position and identify your most valuable queries ranking in positions 5 to 15 (or whatever your range is) and focus on those for optimizations. (You can also set the range as greater than 5 (or whatever your starting point is) and find opportunities that way.)
6. Finding new content topics
How much content to include in an informational blog post or other webpage can be a difficult balance to find. The content should be helpful to the user above all else, so it should holistically answer their question or satisfy their core search intent.
While going too thin could leave your page to be outranked by more detailed content from competitors, adding too much information could also make a page cumbersome and less helpful or relevant to the user’s main intent. In such cases, finding opportunities to write content dedicated to niche or specific topics can be valuable to your users and overall content strategy. (Related reading: 11x content for SEO, a new take on 10x content.)
To find additional content opportunities in GSC, use a similar process as in the previous tip: filter the QUERIES report by the Exact URL of a popular page (or use “URLs containing” to group together a topic cluster of pages based on their similar URL patterns — we’ll dive into how to analyze pages with dissimilar URL patterns together in the next tip), then analyze the queries the page ranks for in higher positions, say anything above 20. (You can also use the Position filter for Greater than.)
You can also add filters for queries containing key terms more likely to correlate with desirable content topics for an audience, like “who, how, why, when, where,” etc.
Look for queries that are relevant to your audience (and ideally on their buyer’s journey for your product or service) but that are not the core topic of any content you have created thus far.
If you’re not sure if you have a page targeting the query, swap the Page filter for the Query filter and enter the query you’ve found, either searching for it exactly or for queries containing, then scroll down and look at pages ranking for that query.
If you have a page to target that query, consider optimizing it again (if it’s not ranking well). If you don’t have a page for the query, consider creating a new page for it. In either case, search the query on Google and see what types of results come up. Based on the intent and nature of the content you see ranking for the query (but not copying those results), create new, original content that you think will be a good match for the SERP but that distinguishes your website based on the quality, expertise, and helpfulness of your content.
7. Analyzing groups of pages
Let’s say we have a group of pages that we want to analyze together in Google Search Console’s Performance Report. Maybe the pages comprise a topic cluster, or maybe they’re grouped for a different reason based on a shared attribute.
If the pages all have a commonality in their URLs, like they share a subfolder or a word in the slug, then they can easily be filtered using the “URLs containing” setting in the Page filter in the Performance Report. (They could reversely be excluded using the “URLs not containing” filter.)
However, if the pages don’t share a commonality in their URLs, then the best solution is to use the Custom (regex) filter for pages. This can be used to look at pages that match or don’t match.
The quick way is to input each of the URLs with a pipe (“|”) between them to search for those URLs. (This can also be used for queries.) Alternatively, I like to use ChatGPT for this.
Add this or a similar prompt into ChatGPT: “Please create a regex for Google Search Console to only return results for these URLs:,” and then paste your list of URLs. (Remember to say please!) 😉
Next, paste the regex from ChatGPT into the Page filter and presto, you can analyze the traffic and rankings for a specific group of pages.
8. Finding indexing issues
Until now the tips have been focused on the Performance Report in Google Search Console. But traffic and rankings data isn’t all that useful if your content isn’t indexed by Google to begin with! 😉
To identify issues related to indexing, one place to start is the Coverage Report, now referred to as the Pages report. This can be found by clicking on Pages under Indexing on the lefthand side of the interface.
The Page indexing report first shows the number of Indexed and Not Indexed pages. You can look for trends in the number of pages. It looks like this:
Below that will be a list of reasons why pages aren’t indexed. Some of these can be perfectly valid like the page is a Not Found (404), or you’ve excluded it with a noindex tag. Of course, it helps to confirm things like that those pages should be 404s, or whether some need redirects.
The two sections I want to call out in particular are Discovered – currently not indexed and Crawled – currently not indexed. Neither group of pages are indexed on Google (it helps to check the dates, though, as sometimes pages may have since been indexed after being reported as not indexed). However, there are some nuances.
Discovered but not indexed pages could be pages that will eventually be indexed once crawled (or manually crawl requested), or they could be pages that Google suspects aren’t worth indexing based on similarities to other low-quality pages that it interprets based on URL structures, for example.
Crawled but not indexed pages could be a little more concerning, in some cases, as this means the page has been crawled and Google chose not to index it, either due to its quality or for other reasons.
I recommend going through these reports and identifying any pages that you’d expect to be indexed and served in search results. If a page is only discovered, try manually crawl requesting it, or pointing some relevant internal links at it to get it crawled and indexed.
If it’s a not-indexed page that’s been crawled already, look for any content improvement opportunities. If you’re still not getting it indexed, try updating the URL if necessary.
9. Filtering out branded keywords to see non-brand keyword growth
Often branded searches are controlled by external marketing and brand factors that SEOs can’t necessarily control. Although we can help maximize the value of branded traffic, it’s really growth in non-brand traffic that we’re often after in SEO campaigns.
Sustainably growing non-brand traffic to a website means increasing its audience, growing its brand awareness, and, ultimately, earning more sales or conversions.
We’ve seen in the above examples the importance of using filters (like for country) as well as regex filters for pages.
The same regex filters can be applied to remove branded queries to highlight non-brand keyword growth.
Here’s an example of a site that gets predominantly branded traffic. You can observe how spikes happen for clicks that correspond to external events, like going viral on social media.
Using the same custom regex filters as in step 7, we can this time set the regex for “Doesn’t match” and then enter all variations of the brand name as well as the names of products or services that include a brand name.
The best way to learn of all those variations is to look at a large timeframe of performance data, such as 16 months even, and enter all possible variations.
Again, you can use ChatGPT to create the regex for you if it’s helpful, and even ask it to come up with other possible variations (including misspellings) of branded queries to filter out.
The result are non-brand keywords, illustrating how the net-visibility of the website is growing with target audiences.
In this case, I also removed informational pages (using the regex from step 7), and used the country filter to hone in on traffic that was the most qualified.
Ultimately, the growth in the bottom chart represents the value this particular website was looking for, so it’s more relevant to report on than, say, site-wide numbers.
Takeaways
These tips are only scratching the surface of the many amazing things you can do in Google Search Console.
I’ll add more tips to this article as I have time (or learn them, as I’m still learning new uses for GSC with every passing day). I also hope to do a similar article for Bing Webmaster Tools, which has some cool features of its own.
In the meantime, feel free to check out those GSC resources linked in the intro to this article, as well as my other article on AI chatbot uses for SEO or visit my full blog.
If you have specific questions, feel free to DM me on X (Twitter) @EthanLazuk (same on LinkedIn) or send me an email ethan.lazuk@gmail.com.
Thanks for reading. Happy optimizing! 🙂
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