Content decay is what happens when a post that used to bring in steady traffic slowly loses it. Usually search results have shifted, the information has aged, or newer content has overtaken it. The posts worth your time are the ones that were genuinely strong and are now fading. Posts that were never big to begin with can wait.
Here is how to find the ones that matter on the Explore page.
First, How % Change Works in Clariti
Clariti has three "% Change" filters and columns on the Explore page:
Page Views % Change
Sessions % Change
Visitors % Change
Each one compares the time window you pick against the equal window immediately before it. The window comes from a single control: as soon as you add a traffic filter or column, a Performance Period selector ("Show metrics for") appears at the top of the Filters panel, and it applies to every traffic filter and column at once. Pick 90 days and you are comparing the last 90 days to the 90 days before that. Pick 1 year and you are comparing the last year to the year before it.
That choice matters more than anything else on this page, which brings us to the most common mistake.
Set the Performance Period to 1 Year
If you compare the last 90 days to the previous 90 days, you are comparing summer to spring, or fall to summer. For a seasonal site, that will flag nearly every soup, chili, and holiday recipe as "decaying" every single summer, and nearly every salad and popsicle recipe as decaying every winter. That pattern is seasonality, and it fixes itself.
Setting the Performance Period to 1 year compares this year to last year, so both windows contain the same seasons. What is left after that is real decline. One year is also the longest comparison Clariti offers, since % Change is not available for the 2 years or All time periods.
Use a shorter period only when you are investigating something specific and recent, like a suspected algorithm update.
The Filter Recipe
On the Explore page, click Add Filter and build these four, then set the Performance Period to 1 year.
1. Page Views: set a floor.
Set the minimum to something meaningful for your site, like 2,000 over the last year. This is what separates real decay from noise. A post that fell from 12 views to 4 is down 67%, but it does not matter. Raise or lower the floor until the list is a size you would actually work through.
2. Page Views % Change: the decline itself.
Set the range from -100% to -25%. Anything shallower than about -25% year over year is usually normal fluctuation. Tighten it to -40% if you want only the steepest drops.
3. Date Published: leave out anything from the last year.
This step is the one people skip, and it is the difference between a useful list and a useless one. Brand new posts almost always show a big negative % change, because they are coming down off the spike they get when they are first published and promoted. That is completely normal and there is nothing to fix.
Set Date Published to end about 12 months ago so those posts drop out of the list.
4. Date Last Modified: find the stale ones.
Set this to end about 6 months ago. A post that is declining and has not been touched in six months is a much better use of your time than one you already refreshed last month, which may just need longer to recover.
Then Sort by Traffic
Once the filters are set, add the Page Views and Page Views % Change columns using the columns icon in the upper right of the list (its tooltip says "Select Columns to Show in List"). Then sort by Page Views, highest first, by clicking the column header. In the table the long names are shortened, so Page Views % Change shows as "Views %" in the header.
Sorting by traffic puts your biggest posts at the top, so you are looking at the largest amount of traffic actually lost. A post down 30% from 100,000 views has lost far more than a post down 80% from 3,000, but sorting by percentage would bury the first one and put the second on top. Percentage tells you how badly a post is sliding. Volume tells you how much it is costing you. Fix the expensive ones first.
Turn the List Into a Plan
Once you are happy with the list, do not leave it as a filter you have to rebuild every time:
1. If you do not have a project for this yet, create one first (for example "Content Refresh"). The assign option stays greyed out until at least one active project exists.
2. Open the actions menu (...) at the top right of the list and choose Assign to Project.
3. In the window, assign Filtered Items. It is selected for you whenever filters are active and no rows are checked, so there is no need to check every box by hand. You can still hand-pick posts with the checkboxes and assign just Selected Items instead.
The same menu has Manage Labels. A label like "DECAYING" lets you track this group over time when you re-run the filter each quarter.
After you refresh a post, add an annotation on its Performance chart to mark the date. That way, when you look back in three months, you can see whether the update actually moved the line. See How to Use Annotations on Your Performance Charts.
Confirm It Is Really Decay
Before you rewrite anything, open the post and check the Performance tab:
Add a year comparison to see this year against last year on the same calendar dates.
Chart the Google traffic source on its own. If Google is down but Pinterest is flat, it is a search problem and the fix is the content. If everything fell off a cliff on the same day, it is more likely a technical issue or an algorithm update.
Check the keyword table for positions that have slipped. A post that fell from position 3 to position 8 will lose most of its clicks even though nothing about the post changed.
Common Mix-Ups
The filter and column is named Page Views % Change. In the table header it is shortened to "Views %", which is why you will sometimes see it written as "Views % Change." When you are adding the filter or column, look for the full name.
There is no filter called Date Republished. Use Date Last Modified, which reflects the last time the post was updated in WordPress.
A % Change filter always follows the Performance Period. It compares your chosen period to the equal period right before it, so the period you pick is the comparison, and comparisons max out at 1 year.
Frequently Asked Questions
Why is a post I just published showing a huge negative % change?
Because it is coming down off its launch spike. New posts get a burst of traffic from email, social, and initial indexing, and then settle into a normal baseline. That is expected. Filter out anything published in the last 12 months so these do not crowd your list.
Is there a faster way to get started?
Yes. Super Search understands sorting phrases like "by drop in views" (or "by drop in sessions"). Type one and Clariti sorts your whole library by steepest decline and adds the right columns for you. Then add the filters above to narrow it down. See How to Use Super Search.
Should I use Page Views, Sessions, or Visitors?
Page Views is the usual choice for spotting decay, since it is closest to how much a post is being read. All three behave the same way in the filters, so use whichever you track elsewhere. Just stay consistent so your numbers stay comparable between reviews.
How far back can I compare?
Comparisons max out at 1 year, and Clariti keeps roughly two years of Google data, which is exactly enough for a 1-year comparison. If your site has less than two full years of Google Analytics history, use a shorter period and read the results with seasonality in mind.
Can I just ask for this instead of building filters?
Yes. If your account has access to the Clariti MCP, you can ask your AI assistant something like "what should I refresh?" or "what is losing traffic?" and it will run this same analysis, comparing recent traffic against an earlier baseline and then checking which of those posts have not been updated in six months. See What Is the Clariti MCP?.
Still Have Questions?
Reach out anytime and we will help you sort it out. Email us at [email protected].