Two weeks after the update, the rankings are still fluctuating. Should we change the content in this round?

📅 2026-11-01 👁️ 0

After the garbage update push is completed more than two weeks later, the ranking is still fluctuating. Should we change the content at this time? First, clarify two things: the official has confirmed that the push has been completed, and the ranking has stabilized, which are not the same time point. Taking this round as an example, the official statement is that the push was completed on October 8th, and what is different this time is that it took two weeks to complete; the same statement also mentions that recovery may take several months. That is to say, the two weeks after the completion date are still in the fluctuation window, and the greatest cost of changing the content at this time is attribution failure.

How long will the vibration last after the completion date?

The push is complete only meaning that the algorithm side is no longer in a gray area, and the performance on the site side still depends on the redistribution of crawling and indexing. The common observation rhythm is like this: within one to two weeks after completion, there is still shaking, which is within the normal range; after three to four weeks, if it still falls unidirectionally and the decline is concentrated in a few templates or a type of page, it is more likely to be a problem with the site itself.

Do not use the whole site average when making judgments. Break down the data by terminal, by country or region, and by page type, as fluctuations often occur only on a single aspect. The whole site average will offset the rise and fall, leading people to misjudge it as 'not serious' or 'the whole site is finished.'

Record the baseline first before making a judgment.

Before deciding on any action, first stabilize the baseline: note the exposure, clicks, and positions of the main keywords in the week before this round of fluctuations, record the list of affected page types, and then fix the observation time each day to the same period. The role of the baseline is to provide a reference for subsequent judgments, rather than relying on a feeling to compare yesterday and today.

At the same time, list your own actions in a timeline: modified templates, adjusted navigation, batch replaced text, merged categories. These actions, if they fall within the fluctuation window, will be mixed with the effects of the algorithm. Many phenomena that look like algorithmic penalties are actually structural changes made in the same period.

What signal appears to change the content

There are three types of signals worth taking action on. The first type is the page itself has obvious problems: content repetition, missing conclusions, not in line with the search intent. This type of problem exists both before and after the update, and the benefits of changes can be independently evaluated. The second type is indexing and technical exceptions: the target page is not indexed, the jump link is wrong, and the structured entry is missing. The third type is continuous one-way decline exceeding a full observation cycle, and excluding changes made by oneself.

On the contrary, if you only see fluctuations in rankings without any of the above, do not change the content. Changes during the update will invalidate the attribution, and it will be impossible to determine whether this change is a补救 or a new disturbance source one week later.

The minimum modification when changing content.

If it is necessary to make changes, minimize the scope of modification. Change only one type of page and one variable at a time, record the time and scope after the change, and give it at least a two-week observation period. Be especially cautious with batch actions: whole-site batch changes in titles, replacing certain words across the entire site at once, this type of operation affects all pages, and if the direction is wrong, the cost of rollback is very high, and it is also difficult to determine which type of page is affected.

Structure changes take another path: Adjust navigation, merge categories, and perform such actions on a few columns first, confirm that the pages are accessible and internal links are not broken, and then expand the scope. It is more reliable to schedule changes during specific time windows than to manually control the time, and it can also avoid concentrating content releases during fluctuation periods.

These two capabilities in the AnQiCMS backend can be used together: Site-wide replacement is suitable for controlled batch text adjustment, but it is necessary to back up first and then execute, and use range limits to affect the templates and columns; Navigation settings and single-page management determine the extent of structural changes, keep records before modification, and review according to page type after modification; The time factor is used to schedule content placement in a stable window.

Common questions

The ranking is dropping, won't two weeks of inaction miss the recovery window?The recovery cycle itself is measured in months, and small changes made within two weeks are unlikely to show any effect, but may pollute the control. It is more cost-effective to use this time to record baselines and exclude self-changes.

Can you try adding a batch of content first?Adding new content and algorithm recovery are two different things. The more stable approach in the update window is to fix the clear problems of existing pages first, and then arrange for the addition of new content after the fluctuations converge and continue to place it.

How can you confirm if it's something you've broken?Compare with the timeline. Arrange the background template changes, navigation adjustments, and batch replacement records in chronological order, and compare them with the starting date of the decline. In most cases, you can locate the specific action.

Related articles

Only about forty percent of the pages cited by AI overview are in the top ten, should the external links be adjusted?

A study covering over 800,000 search result pages shows that the proportion of pages cited by AI overview and ranked in the top ten has dropped from over 70% to about 40% in a year. This article explains why this set of data is not enough to overthrow the external link plan, what aspects of the external link side do not need to be changed, and the two things that can be done first, such as the keyword library, anchor text, and paragraph structure within the site.

2026-11-01

The adoption rate statistics of two llms.txt files differ by more than a factor of two, so which one should be used to allocate work?

The adoption rate of llms.txt is the same, but the readings from different studies range from ten percent to nearly fifty percent, the gap mainly comes from the denominator rather than the conclusion. This article decomposes several statistics according to the sample size and what they can answer, and gives three indicators that are more important than the adoption rate: whether it has been read, whether the content is consistent with the site map, and whether the maintenance cost can be automated.

2026-11-01

The sites that block training crawlers are almost no longer cited, can this data be implemented directly?

A study covering thousands of domain names shows that almost no references can be obtained by blocking the domains captured by training class. This article explains why this set of readings cannot be directly applied: sample scope, industry composition, and category mixing will all contaminate the results, and a minimum experimental design for small-scale comparative observations on your own site is given.

2026-11-01

Pages with ads are blocked by default for training crawler, what configuration line should the new domain check?

The newly connected domain blocks training and proxy crawlers by default on the page displaying ads, while search crawlers are still allowed. The verification should be done in three layers: which domains and page types it affects, the user agent names written in the configuration, and the actual visits and rejection results in the access logs. This article also explains the division of labor between access control, site map, and llms.txt.

2026-11-01

Exporting the entire old station into a package and then importing it, will the attachments fall outside?

The packaged file exported from the entire station usually contains media files, whether the attachments will fall outside when imported across systems depends on whether the path and fields can correspond. This article compares the three import routes of packaging, table, and compressed package, respectively, what they take away, explains where the upload volume limit is stuck at each level, and gives the three acceptance and rollback preparations after migration.

2026-11-01

Can a lightweight memory PHP program withstand the corporate station, what indicators to look at

Can a lightweight memory PHP website program withstand an enterprise station? It needs to be evaluated based on three indicators: the number of data tables and the size of the code package only reflect the installation surface, the resident memory water level, single machine concurrency carrying capacity, and static structure determine the peak performance. This article provides a set of verification order, first read the volume, then run pressure test, and finally draw conclusions according to your own site configuration, and attach the memory aperture of the Go technology stack for reference.

2026-11-01

Who manages the server for self-built background and hosting platform, and where is the difference in maintenance working hours?

The difference in server division between self-built CMS backend and hosting platform is concentrated in the three steps of patching, backup acceptance, and upgrade rollback. This article compares each item with the patch frequency and labor cost range given by the operation and maintenance cost study, explaining that hosting does not mean zero labor and self-building does not mean all manual, and provides a method for calculating maintenance hours into annual costs.

2026-11-01

Does the AI crawler have dozens of user agents, and should training and search classes be separated?

The list of user agents for AI crawlers indeed has dozens, but it is more practical to divide them into training, retrieval, and user-initiated types according to their use: the training type can be tightened as a whole, and the retrieval type and user-initiated type should be relaxed. robots.txt controls access, llms.txt controls which navigation to read, and the two have different divisions of labor. After the change, the actual user agents visiting should be checked against the log.

2026-11-01