SEO is a process. A typical workflow includes: covering search intents – achieving good indexing – attaining good rankings – gaining favorable display – conducting SEO data analysis. All issues such as website construction methods and promotion content optimization must be determined by the final analyzed data. Taking data analysis as the sole criterion for measuring website optimization results is what constitutes scientific SEO.

Without practical data analysis measures, doing SEO is just relying on intuition, which is unreliable.

How to analyze various SEO data of a website? On a macro level, authoritative statistical tools such as webmaster statistics are essential. Analysis of some core data, including keyword rankings and website traffic, is indispensable.

Chengdu Caijiang SEO has written an article on website SEO data analysis that is worth learning from. The original text is as follows:

The daily enthusiasm of website optimization mostly comes from checking one’s own rankings and indexing status. This is basically the motivation to keep going with SEO every day. Seeing rankings rise is like watching the stocks you invested in go up, bringing joy for a few minutes.

For SEO practitioners who pay attention to the fluctuation curves of website data, it is common to sort out and analyze various website data every day to confirm daily optimization effects. However, many SEOs face a complicated problem: understanding data is one thing, but achieving results based on data is another. Some even shift their focus from SEO execution to data analysis.

For example: many websites have been penalized (de-indexed or downgraded) recently, but webmasters do not know the real reason, only attributing it to natural Baidu fluctuations. Since many sites were affected, they ignored it. For experts, seeing partial websites penalized usually means they have been hit by a Baidu algorithm update. However, many beginner webmasters have limited thinking and awareness, and rarely pay attention to reference data beyond their own sites.

Regarding the recent introduction of the Mianyu Algorithm, it cracks down on behaviors including but not limited to impersonating official sites, keyword stuffing in titles, and other low-quality profit-making practices that seriously harm user experience, such as distorted profit models and cross-platform profit-seeking. Generally speaking, websites can be quickly restored by rectifying according to Baidu’s requirements.

What basic knowledge should webmasters master when observing website data?

What basic knowledge should webmasters master when observing website data?

1. Reasons for decreased indexing or unstable search results?

 

 

1. Unstable search indexing: Check website indexing via Baidu Webmaster Platform. As long as the index does not decline continuously or sharply, fluctuations in indexing volume have little impact.

2. Continuous decline in website indexing: Caused by keyword stuffing, website penalties, hidden links, a large number of dead links after website redesign, etc.

3. No indexing at all: Poor user experience, slow loading speed, unstable server, low-quality content, chaotic URL structure, sandbox period, etc.

2. Data analysis for keywords without effective rankings?

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