By Summary
/goto redirect system for outbound links in search results, which complicates rank tracking and search scraping efforts. This update obscures destination URLs, requiring additional steps to determine the actual link. This change impacts rank tracking systems, increasing the complexity and cost of associating rankings with canonical URLs. For data scraping, it adds a layer between scrapers and valuable SERP data, potentially leading to increased costs and detectability of scraping activities at scale. Workarounds will likely be developed, but the impact on ranking accuracy, update frequency, and pricing for SEO platforms remains a key concern.Google Rolls Out New /goto Redirects That Complicate Rank Tracking and Search Scraping
Google is rolling out a significant change to how outbound links work inside its search results. Instead of exposing a result’s destination URL directly in the search result HTML, Google is increasingly routing clicks through a google.com/goto URL that performs a server-side redirect to the actual destination. Google began testing the system in July 2026, and Nozzle reports seeing it on nearly 100% of SERPs across several residential IP providers. Google has now confirmed that the change is rolling out.
Google has not explicitly called the /goto system an anti-scraping feature, but its statement strongly points in that direction, saying it regularly deploys technical measures against “evolving forms of abuse” to protect its services and users.
Why This Matters for Rank Tracking
Traditional rank-tracking systems can fetch a Google results page, parse the HTML, identify each organic result, and extract the destination URL directly from the page. The new system potentially removes that last step.
According to Nozzle’s Derek Perkins, the new /goto URLs cannot simply be decoded to determine the destination URL. A rank tracker may instead have to request Google’s redirect URL and follow the server-side redirect to discover where each search result actually points.
That does not necessarily make rank tracking impossible. The ordering and visible information in the SERP can still be parsed. However, it may make accurately associating rankings with canonical destination URLs considerably more expensive and technically difficult.
A rank-tracking provider that previously needed roughly one Google request to analyze a SERP could potentially need many additional requests to resolve the links contained within it. Nozzle notes that a SERP can contain hundreds of links requiring resolution.
That creates several potential problems for rank trackers:
- More requests per keyword to identify ranking URLs.
- Higher infrastructure and proxy costs, particularly for trackers monitoring millions of keywords.
- Greater bot-detection exposure, because resolving redirects generates additional requests to Google.
- Slower SERP processing as links have to be followed rather than extracted directly.
- Potential accuracy issues for platforms that cannot reliably resolve every redirected URL.
- Possible pricing or usage-limit changes if providers’ cost per tracked keyword increases substantially.
Why This Matters for Google Data Scraping
The implications extend well beyond SEO rank trackers. Search-result APIs, competitive intelligence platforms, AI companies, research tools, and other services frequently obtain Google data by scraping search-result pages.
Google’s /goto system effectively adds another layer between a scraper and one of the most valuable pieces of SERP data: the actual URL Google is ranking.
Instead of receiving a clean relationship such as:
Position 3 → example.com/page
a scraper may initially receive something closer to:
Position 3 → google.com/goto/...
It then has to interact with Google again to determine the underlying destination.
This is particularly important at scale. Following a redirect is trivial when analyzing a handful of searches. Following potentially hundreds of additional Google URLs across millions of SERPs is a very different engineering problem and gives Google additional opportunities to identify, rate-limit, or block automated systems.
The change therefore appears less like an attempt to make scraping technically impossible and more like an effort to increase the cost, complexity, and detectability of scraping Google Search at scale.
Third-party providers will almost certainly develop workarounds. The important question for SEO platforms is what those workarounds require—and whether they affect ranking accuracy, update frequency, tracking limits, pricing, or the underlying data source used by each platform.