Google changes the rules of the game: what does the disappearance of parameter n mean and how to adapt to the SEO market
Google quietly removed the page numbering parameter from its search results, changing not only how parsers work, but also the approach to analytics, link building, and measuring SEO effectiveness.
What happened?
Recently, we at WAMP noticed some interesting and quite significant changes in Google's search engine. At first glance, they seem like a minor technical detail — just a change in the parameters of the search results URL. However, there is a much deeper shift behind this that affects the SEO market, analytics, the work of parsers, and even competition in the field of artificial intelligence.
The essence of the changes is that Google has completely removed the page numbering parameter from search results. Previously, specialists could add a query to the URL, specifying the desired page number and thus obtaining, for example, 100 search results at once. Now this option is no longer available. Google only returns the first page, i.e. 10 results, and that's it.
For the average user, this may seem insignificant — after all, most people rarely go beyond the first few pages of search results. But for SEO agencies, analytics platforms, and position monitoring services, this change has become critical.
Previously, it was possible to get the top 100 search results for a keyword with a single query, saving resources and time. Now, to collect the same amount of data, you need to make ten separate queries. For services such as Ahrefs, SEMrush, or SE Ranking, this means a tenfold increase in load — both on their own servers and on Google's infrastructure.
The company's official position sounds simple and logical: “Fighting scraping.” Google claims that automated data collectors create an excessive load on the system, and now the company is stepping up measures against such practices. This includes forming separate anti-scraping teams and implementing additional filters.
From a technical point of view, this explanation seems convincing. However, in our opinion, there are other, more strategic motives behind this move. There is active discussion in the professional community that the changes are aimed not so much at SEO tools as at developers of large language models (LLMs) such as ChatGPT, Perplexity, and others.
The fact is that these models actively use Google search results for training and generating responses. They collect snippets, texts, and facts directly from SERP (Search Engine Results Page) to form their own responses to users. And by removing the ability to get extended results using the numbering parameter, Google has actually complicated and significantly increased the cost of the data collection process for them.
Thus, this step can be seen as a way to strengthen the position of its own AI direction — Gemini — and at the same time limit the capabilities of competitors. It is possible that this is part of a broader Google strategy to control access to data that fuels artificial intelligence.
The economic logic here is also obvious. Maintaining server capacity to process millions of automatic requests from parsers costs the company a fortune. Experts estimate that the cost of processing such traffic can reach millions of dollars per month. Against this backdrop, simply disabling the parameter that allows for the mass collection of search data is more profitable than continuing to fight bots.
In addition, Google has repeatedly demonstrated a similar approach in the past. Suffice it to recall the story with PageRank — when the indicator, which had long been the main tool for assessing the authority of a website, the company simply stopped displaying it publicly. At the time, this also caused an uproar in the SEO community, but years later, it became clear that Google was gradually closing direct access to data that could be used outside its ecosystem.
The current situation looks similar: the company is removing a tool that provided too much transparency and allowed data to be obtained without Google's involvement. Now, if someone wants to obtain detailed SERP data, they have two options: use the official API (with restrictions and a paid quota) or settle for only the first page of results.
For us as an agency, this was a signal that the search analytics market is facing major changes. Many familiar parsing tools that relied on collecting complete results will no longer work correctly. This means that the economics of SEO analytics will also change — the cost of data will increase, position updates will become slower, and access to deep results will become more expensive.
At WAMP, we see this not only as a limitation, but also as an opportunity to rebuild our approach to analytics. We are already testing alternative data sources, cross-checking through several independent systems, and developing our own search visibility analysis tools without direct parsing of results.
Google is changing the rules of the game again, and this case is no exception. It is important not just to observe, but to adapt: to assess what data is really needed for business and how it can be obtained safely and reliably. After all, the more direct paths to information are closed, the higher the value of expert analysis, flexibility, and the ability to find workarounds that are still legal.
How will the changes affect SEO work?
After the first few days of discussions in professional chat rooms and forums, it became clear that Google's changes, with the removal of the page numbering parameter in search, were not just an inconvenience, but a real stress test for the entire SEO tools industry. We at WAMP closely monitored the market's reaction and recorded the first steps taken by the major players.
Perhaps the most obvious consequence is that SERP parsing has become more expensive. This is not a metaphor, but a literal economic reality. One of the largest providers of “raw” search data, Datav OSIО, has openly announced that, starting September 19, the cost of SERP extraction will now be calculated based on 10 results per query. If you want to get the top 50, pay five times more; for the top 100, pay ten times more.
This means that the costs of all platforms that collect millions of search positions daily have increased exponentially. At the same time, end customers (SEO specialists, agencies, and marketers) are still unclear about who will cover these costs — services or users.
Interestingly, the reaction of the largest SEO platforms has been mixed.
SE Ranking publicly stated that it would continue to provide top 100 data, although it noted that collection may become slower. Historical data will be preserved, but they prefer not to talk about the increase in cost and possible price changes yet. It is quite possible that this is more of a marketing message — to maintain user confidence while the technical and financial implications are being assessed within the company.
Semrush acknowledged the problem and confirmed that it affects absolutely all market players. They reported that they have a “temporary solution,” but did not provide any details. At the same time, the company has begun to shift the focus of its communications: their materials now increasingly emphasize that the real value of the data is concentrated in the top 10 and top 20 results, rather than the entire top 100. In essence, this is an attempt to explain that monitoring positions beyond the second page is not so critical for decision-making.
Tim Soule from Ahrefs previously expressed a similar position, saying that the battle for user attention takes place in the top lines, and there are practically no clicks beyond that. And now that access to this data has become much more difficult, the market is forced to accept this as the new reality.
Some platforms, such as EQ-Ranker, have gone even further and simply stated that they now only collect the top 20. Others, such as Ahrefs, were still reorganizing at the time of the discussion and did not give a final comment, although it is obvious that the changes will also affect their algorithms. Auxiliary tools such as Spicerap are now actively used for interim data verification, but they will soon face the same limitations.
In general, we can say that a new unspoken standard is forming — the top 20 instead of the top 100. Everything else will become a “premium-level” option: either for a separate fee or with much slower updates. And if top 100 analytics used to be considered a basic feature of any SEO service, now it is becoming an expensive and not always justified tool.
For us practitioners, the consequences are obvious. First, it becomes more difficult to track the growth dynamics of positions outside the top 20. Previously, we could see how a site gradually rose from 50th to 40th, then to 30th place — this gave an understanding of progress, helped motivate the client, and adjust the strategy. Now, this entire “gray area” simply disappears: advancement to the top 20 may go unnoticed if the tool does not support in-depth data collection.
Second, the changes also affect Google Search Console (GSC) analytics. According to forecasts by some experts, in particular the Google Search Hold team, shifts in metrics can be expected. Because Google now displays results beyond the second page less often, some impressions will simply cease to be counted.
The paradox is that because of this, the average metrics in GSC may even improve — but not because the site has started to perform better. The average position may “even out” upwards because the most distant, irrelevant pages that were pulling the metric down will disappear from the calculation. CTR may also increase — after all, impressions will decrease, and clicks mainly come from the top. As a result, we get nice statistics: positions seem to be growing, clickability is higher, but there is no real increase in traffic.
Moreover, given the growing influence of AI Overviews (new Google answers with elements of artificial intelligence), some of the traffic may gradually “move” there. At the same time, website owners will see a paradoxical picture in GSC — metrics seem to be improving, but the number of visits from search is not growing.
Some analysts, including Brody Clark, have put forward an interesting hypothesis: that Google may have deliberately implemented the change with the removal of the numbering parameter not only for the sake of resource optimization, but also to mask the drop in organic traffic caused by the introduction of AI blocks. When metrics start to behave unusually, it can be explained by “technical changes” rather than a decrease in clicks due to the appearance of AI answers above the search results.
Therefore, one of the first practical steps that we at WAMP recommend to all clients is to urgently download the complete data history from Google Search Console for the last 16 months. This needs to be done now, before the system recalculates and “rewrites” the old statistics according to the new rules. The saved historical data will help you compare traffic before and after the changes and correctly assess the real dynamics.
Thus, a new era of search analytics is forming before our eyes. Google is focusing on the top 10 and top 20, and the entire market is forced to adapt to this. For the SEO industry, this means a narrowing of the observation horizon; for analysts, it means an increase in the cost of data; and for businesses, it means the need to look more closely at real traffic metrics rather than “improved” averages in reports.
What will change for agency clients?
The most significant consequence of the changes in Google search was their impact on link building. The reason is simple—the blow fell on the reporting system. After all, it was the visible positions that were used to build agency reports and justify the effectiveness of the link strategy.
Previously, everything was transparent: you could show a client that their site had moved from 79th to 53rd place and say, “Here are the results of our work, here is the graph, here is the dynamics.” It was a familiar metric that everyone understood. But now, when tools only track the top 20, an obvious question arises: how can you prove progress if the site is still outside the top 20?
The client opens the report, looks at the top 20 positions, and doesn't see themselves there. They ask, “Where are the results we're paying for?” Agencies and SEO specialists find themselves in a difficult situation: the familiar measurement system no longer makes sense.
That is why, in our opinion, the market is on the verge of a paradigm shift in link building. Instead of measuring success solely by rankings, more attention will be paid to actual referral traffic. The question now is not “what position have we achieved,” but “how many people actually clicked on the links and what did they do on the site.”
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This approach shifts the focus from quantity to quality. Now it is more important not just to “buy a link,” but to find a platform with a live audience, relevant topics, and engaged readers. The value of a donor is determined not only by the weight of the domain, but also by its ability to actually bring people in, not just transfer PageRank.
Yes, it's more complicated. It requires analytics, thorough site verification, and user behavior assessment. But this is a move towards market maturity. SEO and link building are no longer a “positioning game” but are becoming an integral part of the marketing cycle, where not only visibility but also conversion is measured.
Looking at the bigger picture, this change with the removal of the page numbering parameter is only part of a major restructuring of the Google ecosystem. At WAMP, we see this as a consistent step towards integrating AI into the search structure itself.
First, Google is actively rolling out AI Overviews — new AI-powered answers that are already being tested and are displayed by default in a number of countries. These blocks take up half the screen and replace the classic search results, and most importantly, they have already begun to be monetized.
The Ads Max (ADI) program allows ads to be displayed directly within AI responses. This is a fundamentally new model: the user receives not just a link to a website, but a ready-made answer with advertising already built in. In essence, Google is turning search into a hybrid environment — a mixture of an information assistant and an advertising block.
Second, the company is experimenting with snippets. Instead of the usual descriptions under the link, texts generated by AI based on the Gemini database are now increasingly appearing. This looks informative, but at the same time reduces the incentive to click on the source. An example is the Yelp search result: the AI itself substituted prices, opening hours, and a brief description of the establishments. The user got the answer and didn't go anywhere.
At the same time, the conflict with publishers is growing. Major media holdings, including the owners of Rolling Stone and Billboard, have already sued Google, accusing the company of using their content in AI Overviews without permission or compensation. The publishers claim that Google is essentially “repackaging” their texts and stealing traffic, turning copyrighted content into free fuel for its answers.
And that's not the only front. The US Federal Trade Commission is investigating Google and Amazon for possible manipulation of advertising auctions. So Google is simultaneously rebuilding its product architecture, fighting regulators, changing its search interface, and introducing AI into every level of interaction.
The company, of course, explains everything in the usual way: “We are making search better for users.” The argument is classic: Google strives to provide the fastest and most accurate answers, and it still cites its sources, they say. Formally, yes, the links remain. But for publishers and website owners, this is little consolation: traffic goes up to the AI block, not to the websites.
Interestingly, the updated guidelines for assessors (people who manually evaluate the quality of search results) now specifically mention the evaluation of AI Overviews. The list of critically important topics — Your Money, Your Life (YMYL) — has also expanded. In addition to finance and health, it now includes elections, government institutions, and public safety. This suggests that Google understands the risks associated with the accuracy and responsibility of AI responses and is trying to play it safe.
Key points
When you combine all these elements—disabling page numbering, the growing influence of AI Overviews, the increasing complexity of SEO tools, and legal disputes—it becomes clear that Google is rebuilding its search model. And with that, everything we knew about SEO success metrics is changing.
The concept of “position” is gradually losing its meaning. In the future, where users will see not a list of links but a single “smart answer” from Google, there will no longer be the familiar top 1 or top 20. This raises the question: how can we measure effectiveness? How can we prove the value of SEO if visibility is no longer linear?
Simply finding a way to circumvent new parsing restrictions is a tactic, not a strategy. The strategy is to adapt to the new reality. At WAMP, we see several directions worth pursuing:
1. Focus on brand traffic that is not dependent on search fluctuations.
2. Strengthen expert content that is difficult for AI to paraphrase.
3. Emphasize interaction with the audience—direct communications, email, communities.
4. Integrate SEO into marketing analytics as part of the overall sales funnel.
This is no longer just a matter of website optimization, but of building a sustainable ecosystem in which the brand retains its influence even when search becomes smarter and less transparent.
It can be said that we are witnessing a paradigm shift in SEO. Technical techniques are giving way to content, analytics, and brand strategies. Google is changing the rules, and these changes are happening right before our eyes.
At WAMP, we will closely monitor developments and share our practical observations. Because new market standards are being formed right now — and those who adapt first will gain a real advantage in the search for the future.
