When preparing quarterly reports, you might run into an unexpected snag: GA4 sessions are up 10% year-over-year despite no changes in initiatives. The acquisition channel breakdown and top pages look virtually identical. There is simply no reason visible on the site to explain the increase.
In situations like this, the cause sometimes lies outside your measurement tools. The browser extension shifts taking place in 2026 are precisely this type of change.
Full-fledged ad blockers have vanished from Chrome
Chrome and Edge have phased out the legacy extension specification (Manifest V2). As a result, uBlock Origin no longer runs on Chrome or Edge and has been replaced by the stripped-down Lite version. At present, Firefox is the only major browser running the full-featured version. Brave also continues its own independent support.
Technically, this is an overhaul of how extensions block network traffic. Under the legacy spec, extensions could intercept individual requests and decide on the fly whether to allow or block them (webRequest). Under the new spec, browsers apply pre-registered rules instead (declarativeNetRequest). Dynamic per-request evaluation is no longer possible, and a cap has been placed on the number of rules that can be registered.
At its peak, uBlock Origin reportedly had around 40 million users on Chrome alone. Every one of those users has either switched to the Lite version, moved to a different browser, or is now browsing without any ad blocker installed.
How analytics tags are blocked is shifting
Ad blocker filter lists do not target only ads. Analytics scripts and tag delivery domains are also included in many filter lists. In other words, in environments where ad blockers are working aggressively, those sessions are never recorded in GA4.
This is where the loss of dynamic evaluation comes into play. Analytics tag delivery has long been a game of cat-and-mouse, shifting domains and paths to evade blocks. Relying solely on pre-registered rules makes it difficult to keep up with these shifts. As a result, tracking is likely getting through more easily in Chrome environments than before.
| Browser | Legacy extensions | Direction of impact on tracking |
|---|---|---|
| Chrome / Edge | Phased out (migrated to Lite version) | Blocking weakens, pushing recorded sessions higher |
| Firefox | Still available | Data gaps remain as before |
| Brave | Still available, with native browser-level blocking | Remains as before, or shows greater data loss |
Note that this table illustrates directions, not magnitudes. Exactly what percentage shift occurs on your site depends on your visitors' browser breakdown and how many of them actually use ad blockers. The baseline differs drastically between B2B tech sites and consumer-facing sites.
How to verify this in your own data
Rather than relying on guesswork, you can verify this using your existing data. In GA4 Explorations, line up monthly session counts broken down by browser. Having two years of data makes trends easier to evaluate.
Look at shifts in share rather than absolute numbers. If Chrome's share jumps in a month where nothing changed on your site, that is very likely when the impact hit. If Firefox and Brave shares did not drop simultaneously, it suggests that actual users did not migrate; rather, sessions that were previously invisible are now being tracked.
Performing this check changes how you write your reports. Instead of simply stating "YoY +11%," you can add a note that "a portion is due to changes in tracking conditions." Conversely, reporting this as the result of marketing initiatives without checking will leave you unable to explain why the same growth fails to materialize in the following quarter. We outline baseline GA4 monitoring in GA4 initial setup and key metrics to track.
Cross-checking against search metrics
Another effective technique is cross-referencing against data from a completely different tracking pipeline.
Google Search Console impressions and clicks are recorded on the search results side. They cannot be blocked by browser extensions. When aligning GA4 organic sessions against GSC clicks over the same period, if only one metrics spikes, tracking artifacts are likely at play. If both move in tandem, traffic has genuinely grown.
This cross-check is valuable well beyond the topic of ad blockers. During periods when search result layouts change and traffic patterns shift entirely—such as The impact of AI Overviews on search traffic—looking at a single tool can lead you to misdiagnose the cause. We also touched on expanding traffic sources in Domestic rollout of ChatGPT ads and website traffic architecture. Always verifying the reason behind moving numbers across two or more independent pipelines is the practical takeaway here.
What to do next
First, pull up the browser session breakdown for the past two years. This five-minute report will show whether you can continue making standard year-over-year comparisons. If there is no step-change, you can continue comparing data as before.
If you do spot a step-change, record that month as an annotation in your reports. Nobody will remember six months from now, and failing to document it means rehashing the exact same debate later.
If you want to review your tracking architecture or build a routine for cross-referencing multiple data sources, GleamHub offers consultations for development, AI, and automation. Because remediation depends on your current measurement setup, we provide individual estimates. Please reach out via Contact Us.
