For many years, Google users and SEO professionals had a simple but very useful trick. Normally, Google shows only ten search results per page. However, by adding a URL parameter called &num=100, users could see up to 100 search results on a single page. This made it easier for SEO analysts to check more results at once, track keyword rankings efficiently, and analyze competitors in greater detail. AI tools and data scrapers also used this feature to collect larger sets of search data quickly.
Recently, Google removed the &num=100 parameter. Although this change might seem small, it has significant implications for SEO, AI tools, and businesses that rely on search data. In this blog, we will explain what the &num=100 parameter was, why Google removed it, how it affects SEO and AI-driven tools, and what businesses need to do to adapt.
What Was the &num=100 Parameter?
The &num=100 parameter was a URL addition that allowed Google to show up to 100 search results on a single page. By default, Google displays ten results per page. Using &num=100 enabled users to see many results at once without clicking through multiple pages.
For example, a normal Google search URL might look like this:
· https://www.google.com/search?q=best+electric+cars
With &num=100 added, the URL looked like this:
· https://www.google.com/search?q=best+electric+cars&num=100
This small change was very practical. SEO analysts could check many competitors quickly and identify patterns in search rankings. AI tools that generate insights from search data also used this feature to gather information more efficiently. Many businesses relied on it to save time and make better SEO decisions.
Why Did Google Remove It?
Google has not given an official detailed explanation for removing the &num=100 parameter. However, there are several likely reasons.
One reason is to reduce automated bot traffic. Many tools used &num=100 to collect large amounts of search data quickly. This caused unnecessary server load and sometimes created artificial search impressions, which can distort metrics. By removing this option, Google limits automated access and encourages more genuine interactions with search results.
Another reason is to focus on user-centered search results. Google wants the results people see and click on to reflect actual user behavior. Scraping 100 results at a time may not represent normal user activity, as most users only interact with the first page of results. Removing &num=100 helps ensure data is more reflective of real user engagement.
A third reason is related to AI-driven search tools. Google is investing heavily in technologies like Google Gemini. By limiting access to extensive search results, Google ensures AI models learn from the first page, which generally contains higher quality and more relevant content.
For official information and discussion from Google support, you can refer to these links:
- My “results per page” have suddenly gone from 100 to 10
- Why is the 100 results per page option no longer available
- I want 100 search results per page
How This Change Impacts SEO
The removal of the &num=100 parameter has both positive and negative effects for SEO professionals and businesses.
Positive Effects
One benefit is cleaner and more accurate data. With fewer automated scraping requests, SEO tools now provide information that more closely reflects real user interactions. Metrics such as average ranking, click-through rate, and impressions are more reliable, allowing businesses to make better decisions.
Another benefit is a stronger focus on the first page of results. Most users only interact with the top ten results, so optimizing for the first page aligns with Google’s goal of providing the most relevant content quickly.
Finally, this change encourages better content quality. Since tools and users now mostly see the first page, businesses are incentivized to produce content that is more engaging, relevant, and user-friendly.
Negative Effects
One challenge is the difficulty of tracking long-tail keywords. Previously, SEO analysts could monitor performance beyond the first page using &num=100. Now, analyzing positions beyond the top ten requires multiple requests, which is more time-consuming.
Another challenge is the increase in costs for SEO tools. Tools that want to analyze multiple pages must now make more requests to Google’s servers, which increases operational costs.
Finally, this change disrupts established workflows. Teams that used to analyze large sets of search results on one page now have to adjust their processes. This can slow down reporting and strategy planning, especially for businesses that relied heavily on bulk SERP analysis.
Impact on GEO and AI Tools
Generative Engine Optimization (GEO) focuses on optimizing content for AI-driven search results. AI models such as Google Gemini and other AI assistants often rely on SERP data to provide insights and recommendations. The removal of &num=100 affects these tools in several ways.
First, it limits access to data. AI tools can now access only the first page of results easily. This reduces the amount of information available for training and analysis, which may affect the accuracy and depth of AI-generated insights.
Second, collecting data becomes slower. To analyze more results, tools need to make separate requests for each page, which slows down the workflow and delays reporting.
On the positive side, this change encourages optimization for high-quality content. Since AI tools mostly see first-page results, businesses are incentivized to create content that is clear, relevant, and answers user questions, which improves visibility in AI search outputs.
Official discussions on Google support about these changes can be found here:
- Site dropped impressions by 90% over 13 days
- Is there any more information on the changes with the &num=100 parameter from Google available
Real-World Example
Suppose a company sells eco-friendly products. Before the removal of &num=100, the SEO team could view the top 100 results for keywords like “best eco-friendly gadgets.” They could identify smaller competitors on pages 5 or 6 and plan content strategies to outrank them.
Now, they can see only the first page of results easily. Tracking lower-ranked competitors requires multiple page requests, which takes more time and resources. AI tools that previously analyzed larger sets of results will now primarily focus on first-page content. This makes it even more important for businesses to optimize content to achieve high rankings on the first page.
What Google Wants to Achieve
The removal of &num=100 is a deliberate change by Google. The main goals appear to be:
- Prioritize real user behavior over automated data collection. Google wants search results to reflect what actual users see and click on.
- Protect its infrastructure. Limiting bulk requests reduces server load and maintains fast and stable search performance.
- Support AI-driven search. Tools like Google Gemini are designed to work with relevant, high-quality content. Limiting SERP access encourages businesses to optimize content that appears on the first page.
How Businesses Should Adapt
Businesses and SEO professionals should adjust strategies to the new environment.
- Focus on first-page SEO. Optimizing for the top positions is more critical than ever.
- Use tools that are adapted to the change and can efficiently analyze multiple pages.
- Optimize content for AI-driven search by creating content that is clear, relevant, and directly answers user questions.
- Monitor real user engagement metrics such as click-through rate, bounce rate, and time on page since analyzing large sets of SERP data is now more difficult.
Adapting to the Change
The removal of the &num=100 parameter may seem minor, but it reflects a larger shift in Google’s approach to search and data access. By limiting the number of results shown per page, Google reduces bot traffic, improves data accuracy, supports AI-driven search, and encourages businesses to produce higher-quality content.
SEO professionals, AI tool developers, and businesses should focus on first-page results, relevant content, and better user engagement to adapt successfully. Although it introduces some challenges, it also encourages a stronger emphasis on quality, which ultimately benefits users and search performance.
For further official information, you can visit the Google support links mentioned above.
