Algorithm impact
Compare page traffic before and after a date you choose, such as a Google update.
In shortAlgorithm impact (Analytics → Search Console → Algorithm impact) compares each page's Google clicks and impressions before and after a date you choose, usually the start of a Google update. It lists the pages that moved by 10% or more, counts winners and losers, and asks an AI model what the pattern suggests. You supply the date; the tool doesn't know Google's update calendar.
When to use it
Google changes its ranking systems constantly and announces the bigger changes: core updates, spam updates and others. When traffic shifts around one of those dates, you want to know two things: did the update cause it, and which pages were hit. Algorithm impact answers the second question directly and gives you evidence for the first.
You can also use it for your own events: a site migration, a redesign, a big internal-linking change. Any date where you expect a before and after.
Before you start
- Find the update's start date in Google's Search Status Dashboard, which lists confirmed ranking updates with their start and end dates. The tool has no list of updates built in.
- Wait until the update has finished rolling out, which often takes around two weeks. Running it mid-rollout measures a moving target.
- Check that the site in the top bar is the one you want.
Run the analysis
- Open Algorithm impactGo to Analytics → Search Console → Algorithm impact. The empty state reads *Select an algorithm update date and click "Analyze Impact"*.
- Enter the date and the windowsSet Algorithm Update Date to the update's start date. Days Before sets how far back the before window goes (7 to 90 days). See the warning below before relying on Days After.
- Click Analyze ImpactClick Analyze Impact. When it finishes you'll see three cards: Pages gained >10% clicks, Pages lost >10% clicks and Total pages analyzed.
- Read the AI analysis and the tableAI Algorithm Analysis looks at the biggest winners and losers and suggests what kind of update the pattern resembles, what the winners share and what to do. Page-Level Impact lists up to 30 pages with Before Clicks, After Clicks, Click Change and Imp. Change, sorted by the percentage change in clicks.
In the current version the after window always runs from the update date to today, whatever you type in Days After, and it compares raw totals. If the update was 60 days ago and Days Before is 30, the after window holds twice as many days and almost every page looks like a winner. For a fair comparison, set Days Before to the number of days between the update date and today (up to 90). Also, Total pages analyzed counts only the pages listed (those that moved 10% or more, up to 30), not your whole site. And because the list is sorted by percentage, a page that went from 2 clicks to 6 can fill a slot ahead of one that lost hundreds of clicks; check Before Clicks to see which changes matter.
How to read the result
| What you see | What it probably means | What to do |
|---|---|---|
| Losses spread across most page types | A site-wide quality or trust reassessment, typical of core updates | Review overall helpfulness: who wrote it, first-hand experience, depth versus what ranks now |
| Losses concentrated in one section or template | Something about that section: thin pages, heavy ads, outdated content | Compare a losing page with a winning page side by side |
| Clicks down, impressions steady | Rankings held but the results page changed, or position slipped a little | Check those queries in Google; look at CTR opportunities |
| Very few pages changed | The update probably didn't affect you | Look elsewhere: seasonality, a technical issue, a lost link |
Google's guidance for core updates is that there's usually nothing specific to fix: the system re-assessed many sites, and recovery tends to come from broadly better content over time, often at a later update. Resist big changes during the rollout. Make deliberate improvements to the losing pages, starting with the ones that brought the most clicks before.
Run the Content decay radar to see whether losers were already declining before the update, and the URL ranking analyzer with custom periods of equal length for a cleaner before-and-after. The Diagnose a traffic drop playbook chains them.
Check yourself
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