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A Complete Guide for SEOs



URL parameters or query strings are the part of a URL that typically comes after a question mark (?) and are used to pass data along with the URL. They can be active parameters that modify page content or passive parameters that are mostly used for tracking and do not change the content.

They are made up of key-value pairs, where the key tells you what data is being passed and the value is the data you’re passing, such as an identifier. They look like ?key=value but may be separated by ampersands (&) like ?key=value&key2=value2 if there is more than one pair. 

Parts of a URL parameter
Explanation of URL parameter parts.

In this guide, we’ll be covering what you need to know about URL parameters.

How parameters are used

As I mentioned in the intro, parameters can be active or passive. Let’s look at some examples of each.

Active parameters

Active parameters modify the content of the page in some way. 

Filter. Removes some of the content, leaving more specific content on the page that a user wants to see. An example of this is faceted navigation in e-commerce. 


Sort. Reorders the content in some way, such as by price or rating.


Paginate. Divides content into a series of related pages.


Translate. Changes the language of the content.


Search. Queries a website for information that a user is looking for.

On our search engine,, we use the key “q” for the query, and the value contains info about the user query.


Passive parameters

Passive parameters do not change the content. They are typically used for tracking. Let’s look at some examples of each.

Affiliate IDs. Passes an identifier used to track where sales and signups come from.


Advertising tags. Tracks advertising campaigns.


Session IDs. Identifies a particular user. It’s not common on modern websites to use session IDs to track users.


Video timestamps. Jumps to the designated timestamp in a video.


SEO implications

URL parameters can cause a number of different issues when it comes to SEO, especially in cases where multiple parameters are used. Here are some of the problems you may encounter.

Passive parameters can cause issues with duplicate content. Typically, you want them to be crawled, and each page should have a canonical set to the main version. 

There may be times where you want to block these parameters from being crawled completely using robots.txt—but only in situations where you may have issues with crawl budget. We’ll cover this more later.

Google will choose a version of the page to index in a process called canonicalization, and signals such as links will consolidate to that indexed version.

Active parameters may create pages with near-duplicate content or content that is very similar to other content. They may also be completely different content. You’ll need to check what your parameters are actually used for.

Internal links

You should avoid passive parameters like those used for tracking on internal links (links from one page on your site to another). 

This is still an all-too-common practice on larger sites, but I want to emphasize that this is an old and outdated practice that you should not be doing. 

Most analytics systems have event tracking you can use instead that still records the data without adding parameters to your URLs.

It’s fine to use active parameters on internal links in most cases.


Infinite URL paths with parameters or tons of different combinations can cause issues with crawling. Keep a consistent order, and don’t have paths that allow for adding additional parameters.

You can easily find potentially infinite paths using the Depth report under the Structure Explorer tool in Site Audit. It’s not common for websites to have 9+ levels, so this is a strong indicator that there may, in fact, be infinite paths or some other issue.

Structure Explorer's Depth report
Depth report in Structure Explorer.

Google will make adjustments as it recognizes infinite paths or certain patterns when crawling. It will try to limit the crawling of URLs that it thinks won’t be useful or are repetitive.


URL parameters are sometimes used for international websites. These are listed as an option for locale-specific URLs. But even Google says it’s not recommended. It adds another layer of complexity where more things can go wrong. You also won’t be able to geo-target these URLs in Google Search Console.


Parameters are commonly used in e-commerce for everything—from tracking, to pagination, to faceted navigation. These topics can be pretty complex, so I recommend reading through the blog posts I linked to better understand them.


There’s a growing trend where people are using # instead of ? as the fragment identifier, especially for passive parameters like those used for tracking. This is generally not a good idea. But in specific cases, it may be OK to do this to replace unnecessary parameters. I tend to recommend against it because of all of the issues.

The problem is anything after a # is ignored by servers, and a lot of systems simply will not or cannot recognize parameters using a #.

Additionally, # already has a designated use case, which is to scroll to a part of the page. This is done on the client side, and JavaScript devs may also use it for “routing” to a page with different content.


It’s a good idea to check what parameters are used on your site. In Site Audit’s Page Explorer tool, you can search for URLs that contain a question mark (?).

Searching for parameters in Page Explorer
Searching for parameters in Page Explorer.

You can use the advanced filters to find pages with multiple parameters or to start excluding parameters to help you identify all the various parameters used on your website.

Once you know what parameters are used, I recommend checking a few of the pages to see what the parameters actually do.

You can also check the Duplicates report for exact or near-duplicates. The visual makes it easy to see if you have a lot of versions of the same or similar pages and whether or not they have matching canonical tags to choose a preferred version. You can click into each cluster to get more information.

Duplicate content tree map
Duplicate content tree map view to show clusters.

There’s also an option under “Bulk export” that lets you export all of the duplicate content at once. I find this option easier to use for larger sets of data.

Controlling parameters

In the past, Google had a URL parameter tool in Google Search Console where you could choose how to treat different parameters based on whether or not it changed the page content. The tool was deprecated in early 2022. Here’s what Google had to say about it:

When the URL Parameters tool launched in 2009 in Search Console’s predecessor, Webmaster Tools, the internet was a much wilder place than it is today. SessionID parameters were very common, CMSes had trouble organizing parameters, and browsers often broke links. With the URL Parameters tool, site owners had granular control over how Google crawled their site by specifying how certain parameters affect the content on their site.

Over the years, Google became much better at guessing which parameters are useful on a site and which are —plainly put— useless. In fact, only about 1% of the parameter configurations currently specified in the URL Parameters tool are useful for crawling. Due to the low value of the tool both for Google and Search Console users, we’re deprecating the URL Parameters tool in 1 month.

While not mentioned, I suspect that some users might have been hurting themselves with the tool. I ran into this in the past where someone put in a wrong setting that said the content did not change, but it did. This knocked a few hundred thousand pages out of the index for that site. Whoops!

You can let Google crawl and figure out how to handle the parameters for you, but you also have some controls you can leverage. Let’s look at your options.

Canonical tags

A canonical tag can help consolidate signals to a chosen URL but requires each additional version of a page to be crawled. As I mentioned earlier, Google may make adjustments as it recognizes patterns, and these canonicalized URLs may be crawled less over time. 

This is what I’d opt for by default. But if a site has a ton of issues and parameters are out of control, I may look at some of the other options.


A noindex meta robots tag removes a page from the index. This requires a page to be crawled. But again, it may be crawled less over time. If you need signals to consolidate to other pages, I’ll avoid using noindex.

Blocking in robots.txt

Blocking parameters in robots.txt means that the pages may still get indexed. They’re not likely to show in normal searches.

The problem is that these pages won’t be crawled and won’t consolidate signals. If you want to consolidate signals, avoid blocking the parameters.

Site Audit

When setting up a project in Site Audit, there’s a toggle in the crawl settings called “Remove URL Parameters” that you can use to ignore any URLs with parameters.

You can also exclude parameterized URLs in the crawl setup using pattern matching.

Blocking a parameter in the crawl setup
Blocking a parameter in Site Audit.


Fun fact: We only count the canonicalized version of pages toward your crawl credits.

Final thoughts

Just to summarize, URL parameters have a lot of different use cases, and they may or may not cause issues for your site. Everything is situational.

Message me on Twitter if you have any questions.

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Google’s AI Overviews Shake Up Ecommerce Search Visibility




Google's AI Overviews Shake Up Ecommerce Search Visibility

An analysis of 25,000 ecommerce queries by Bartosz Góralewicz, founder of Onely, reveals the impact of Google’s AI overviews on search visibility for online retailers.

The study found that 16% of eCommerce queries now return an AI overview in search results, accounting for 13% of total search volume in this sector.

Notably, 80% of the sources listed in these AI overviews do not rank organically for the original query.

“Ranking #1-3 gives you only an 8% chance of being a source in AI overviews,” Góralewicz stated.

Shift Toward “Accelerated” Product Experiences

International SEO consultant Aleyda Solis analyzed the disconnect between traditional organic ranking and inclusion in AI overviews.

According to Solis, for product-related queries, Google is prioritizing an “accelerated” approach over summarizing currently ranking pages.

She commented Góralewicz’ findings, stating:

“… rather than providing high level summaries of what’s already ranked organically below, what Google does with e-commerce is “accelerate” the experience by already showcasing what the user would get next.”

Solis explains that for queries where Google previously ranked category pages, reviews, and buying guides, it’s now bypassing this level of results with AI overviews.

Assessing AI Overview Traffic Impact

To help retailers evaluate their exposure, Solis has shared a spreadsheet that analyzes the potential traffic impact of AI overviews.

As Góralewicz notes, this could be an initial rollout, speculating that “Google will expand AI overviews for high-cost queries when enabling ads” based on data showing they are currently excluded for high cost-per-click keywords.

An in-depth report across ecommerce and publishing is expected soon from Góralewicz and Onely, with additional insights into this search trend.

Why SEJ Cares

AI overviews represent a shift in how search visibility is achieved for ecommerce websites.

With most overviews currently pulling product data from non-ranking sources, the traditional connection between organic rankings and search traffic is being disrupted.

Retailers may need to adapt their SEO strategies for this new search environment.

How This Can Benefit You

While unsettling for established brands, AI overviews create new opportunities for retailers to gain visibility without competing for the most commercially valuable keywords.

Ecommerce sites can potentially circumvent traditional ranking barriers by optimizing product data and detail pages for Google’s “accelerated” product displays.

The detailed assessment framework provided by Solis enables merchants to audit their exposure and prioritize optimization needs accordingly.


What are the key findings from the analysis of AI overviews & ecommerce queries?

Góralewicz’s analysis of 25,000 ecommerce queries found:

  • 16% of ecommerce queries now return an AI overview in the search results.
  • 80% of the sources listed in these AI overviews do not rank organically for the original query.
  • Ranking positions #1-3 only provides an 8% chance of being a source in AI overviews.

These insights reveal significant shifts in how ecommerce sites need to approach search visibility.

Why are AI overviews pulling product data from non-ranking sources, and what does this mean for retailers?

Google’s AI overviews prioritize “accelerated” experiences over summarizing currently ranked pages for product-related queries.

This shift focuses on showcasing directly what users seek instead of traditional organic results.

For retailers, this means:

  • A need to optimize product pages beyond traditional SEO practices, catering to the data requirements of AI overviews.
  • Opportunities to gain visibility without necessarily holding top organic rankings.
  • Potential to bypass traditional ranking barriers by focusing on enhanced product data integration.

Retailers must adapt quickly to remain competitive in this evolving search environment.

What practical steps can retailers take to evaluate and improve their search visibility in light of AI overview disruptions?

Retailers can take several practical steps to evaluate and improve their search visibility:

  • Utilize the spreadsheet provided by Aleyda Solis to assess the potential traffic impact of AI overviews.
  • Optimize product and detail pages to align with the data and presentation style preferred by AI overviews.
  • Continuously monitor changes and updates to AI overviews, adapting strategies based on new data and trends.

These steps can help retailers navigate the impact of AI overviews and maintain or improve their search visibility.

Featured Image: Marco Lazzarini/Shutterstock

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Google’s AI Overviews Go Viral, Draw Mainstream Media Scrutiny




Google's AI Overviews Go Viral, Draw Mainstream Media Scrutiny

Google’s rollout of AI-generated overviews in US search results is taking a disastrous turn, with mainstream media outlets like The New York Times, BBC, and CNBC reporting on numerous inaccuracies and bizarre responses.

On social media, users are sharing endless examples of the feature’s nonsensical and sometimes dangerous output.

From recommending non-toxic glue on pizza to suggesting that eating rocks provides nutritional benefits, the blunders would be amusing if they weren’t so alarming.

Mainstream Media Coverage

As reported by The New York Times, Google’s AI overviews struggle with basic facts, claiming that Barack Obama was the first Muslim president of the United States and stating that Andrew Jackson graduated from college in 2005.

These errors undermine trust in Google’s search engine, which more than two billion people rely on for authoritative information worldwide.

Manual Removal & System Refinements

As reported by The Verge, Google is now scrambling to remove the bizarre AI-generated responses and improve its systems manually.

A Google spokesperson confirmed that the company is taking “swift action” to remove problematic responses and using the examples to refine its AI overview feature.

Google’s Rush To AI Integration

The flawed rollout of AI overviews isn’t an isolated incident for Google.

As CNBC notes in its report, Google made several missteps in a rush to integrate AI into its products.

In February, Google was forced to pause its Gemini chatbot after it generated inaccurate images of historical figures and refused to depict white people in most instances.

Before that, the company’s Bard chatbot faced ridicule for sharing incorrect information about outer space, leading to a $100 billion drop in Google’s market value.

Despite these setbacks, industry experts cited by The New York Times suggest that Google has little choice but to continue advancing AI integration to remain competitive.

However, the challenges of taming large language models, which ingest false information and satirical posts, are now more apparent.

The Debate Over AI In Search

The controversy surrounding AI overviews adds fuel to the debate over the risks and limitations of AI.

While the technology holds potential, these missteps remind everyone that more testing is needed before unleashing it on the public.

The BBC notes that Google’s rivals face similar backlash over their attempts to cram more AI tools into their consumer-facing products.

The UK’s data watchdog is investigating Microsoft after it announced a feature that would take continuous screenshots of users’ online activity.

At the same time, actress Scarlett Johansson criticized OpenAI for using a voice likened to her own without permission.

What This Means For Websites & SEO Professionals

Mainstream media coverage of Google’s erroneous AI overviews brings the issue of declining search quality to public attention.

As the company works to address inaccuracies, the incident serves as a cautionary tale for the entire industry.

Important takeaway: Prioritize responsible use of AI technology to ensure the benefits outweigh its risks.

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New Google Search Ads Resemble AI Assistant App




New Google Search Ads Resemble AI Assistant App

A keynote at Google’s Marketing Live event showed a new AI-powered visual search results that feature advertisements that engage users within the context of an AI-Assisted search, blurring the line between AI-generated search results and advertisements.

Google Lens is a truly helpful app but it becomes unconventional where it blurs the line between an assistant helping users and being led to a shopping cart. This new way of engaging potential customers with AI is so far out there that the presenter doesn’t even call it advertising, he doesn’t even use the word.

Visual Search Traffic Opportunity?

Google’s Group Product Manager Sylvanus Bent, begins the presentation with an overview of the next version of Google Lens visual search that will be useful for surfacing information and for help finding where to buy them.

Sylvanus explained how it will be an opportunity for websites to receive traffic from this new way to search.

“…whether you’re snapping a photo with lens or circling to search something on your social feed, visual search unlocks new ways to explore whatever catches your eye, and we recently announced a newly redesigned results page for Visual search.

Soon, instead of just visual matches, you’ll see a wide range of results, from images to video, web links, and facts about the knowledge graph. It gets people the helpful information they need and creates new opportunities for sites to be discovered.”

It’s hard to say whether or not this will bring search traffic to websites and what the quality of that traffic will be. Will they stick around to read an article? Will they engage with a product review?

Visual Search Results

Sylvanus shares a hypothetical example of someone at an airport baggage claim who falls in like with someone else’s bag. He explains that all the person needs to do is snap a photo of the luggage bag and Google Lens will take them directly to shopping options.

He explains:

“No words, no problem. Just open Lens, take a quick picture and immediately you’ll see options to purchase.

And for the first time, shopping ads will appear at the very top of the results on linked searches, where a business can offer what a consumer is looking for.

This will help them easily purchase something that catches their eye.”

These are image-heavy shopping ads at the top of the search results and as annoying as that may be it’s nowhere near the “next level” advertising that is coming to Google’s search ads where Google presents a paid promotion within the context of an AI Assistant.

Interactive Search Shopping

Sylvanus next describes an AI-powered form advertising that happens directly within search. But he doesn’t call it advertising. He doesn’t even use the word advertising. He suggests this new form of AI search experience is more than offer, saying that, “it’s an experience.”

He’s right to not use the word advertisement because what he describes goes far beyond advertising and blurs the boundaries between search and advertising within the context of AI-powered suggestions, paid suggestions.

Sylvanus explains how this new form of shopping experience works:

“And next, imagine a world where every search ad is more than an offer. It’s an experience. It’s a new way for you to engage more directly with your customers. And we’re exploring search ads with AI powered recommendations across different verticals. So I want to show you an example that’s going live soon and you’ll see even more when we get to shopping.”

He uses the example of someone who needs to store their furniture for a few months and who turns to Google to find short term storage. What he describes is a query for local short term storage that turns into a “dynamic ad experience” that leads the searcher into throwing packing supplies into their shopping cart.

He narrated how it works:

“You search for short term storage and you see an ad for extra space storage. Now you can click into a new dynamic ad experience.

You can select and upload photos of the different rooms in your house, showing how much furniture you have, and then extra space storage with help from Google, AI generates a description of all your belongings for you to verify. You get a recommendation for the right size and type of storage unit and even how much packing supplies you need to get the job done. Then you just go to the website to complete the transaction.

And this is taking the definition of a helpful ad to the next level. It does everything but physically pick up your stuff and move it, and that is cool.”

Step 1: Search For Short Term Storage

1716722762 15 New Google Search Ads Resemble AI Assistant App

The above screenshot shows an advertisement that when clicked takes the user to what looks like an AI-assisted search but is really an interactive advertisement.

Step 2: Upload Photos For “AI Assistance”

1716722762 242 New Google Search Ads Resemble AI Assistant App

The above image is a screenshot of an advertisement that is presented in the context of AI-assisted search.  Masking an advertisement within a different context is the same principal behind an advertorial where an advertisement is hidden in the form of an article. The phrases “Let AI do the heavy lifting” and “AI-powered recommendations” create the context of AI-search that masks the true context of an advertisement.

Step 3: Images Chosen For Uploading

1716722762 187 New Google Search Ads Resemble AI Assistant App

The above screenshot shows how a user uploads an image to the AI-powered advertisement within the context of an AI-powered search app.

The Word “App” Masks That This Is An Ad

Screenshot of interactive advertisement for that identifies itself as an app with the words

Above is a screenshot of how a user uploads a photo to the AI-powered interactive advertisement within the context of a visual search engine, using the word “app” to further the illusion that the user is interacting with an app and not an advertisement.

Upload Process Masks The Advertising Context

Screenshot of interactive advertisement that uses the context of an AI Assistant to mask that this is an advertisement

The phrase “Generative AI is experimental” contributes to the illusion that this is an AI-assisted search.

Step 4: Upload Confirmation

1716722762 395 New Google Search Ads Resemble AI Assistant App

In step 4 the “app” advertisement is for confirming that the AI correctly identified the furniture that needs to be put into storage.

Step 5: AI “Recommendations”

1716722762 588 New Google Search Ads Resemble AI Assistant App

The above screenshot shows “AI recommendations” that look like search results.

The Recommendations Are Ad Units

1716722762 751 New Google Search Ads Resemble AI Assistant App

Those recommendations are actually ad units that when clicked takes the user to the “Extra Space Storage” shopping website.

Step 6: Searcher Visits Advertiser Website

1716722762 929 New Google Search Ads Resemble AI Assistant App

Blurring The Boundaries

What the Google keynote speaker describes is the integration of paid product suggestions into an AI assisted search. This kind of advertising is so far out there that the Googler doesn’t even call it advertising and rightfully so because what this does is blur the line between AI assisted search and advertising. At what point does a helpful AI search become just a platform for using AI to offer paid suggestions?

Watch The Keynote At The 32 Minute Mark

Featured Image by Shutterstock/Ljupco Smokovski

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