How to Judge Content Quality in the AI Era? Do Advertorials vs Original Content Still Matter

Chapter 4: Content Marketing · Question 65

Many people doing content marketing share a confusion: I write "promotional pieces," but I also provide genuinely useful information—how does the search engine actually judge this? Will it be suppressed as an "advertorial"? The answer is—Baidu does have an identification mechanism, butthe key is not "whether there is promotional intent," but "whether content quality meets the standard"。

In the AI Era: How to Judge Article Quality?

If the above question still had a standard answer in the traditional era (search algorithm judgment), then today, when AI writing has become the default, the nature of the question has changed:When everyone uses AI to write, does the standard for judging article quality still hold?

My judgment is:The standard has not disappeared—it has shifted. The power of judgment has moved from "who the author is" (undeterminable and no longer important) to "whether the content itself can be recognized as valuable by both AI and users."

Three Dimensions for Judging AI Content Quality

Dimension 1: Factual Reliability (the "hard currency" of the AI era)

The biggest hallmark of AI content garbage is "correct but hollow." The criterion is not "whether it reads smoothly," but:

• Whether there areverifiable specific numbers and sources(“increased by 40%” vs “significant improvement”)
• Whether viewpoints havesources(data sources, reports, case studies)
• Whether it can withstandtraceability checks—AI will trace your data sources, and fabricated data falls apart at a single poke

Good content = content AI dares to cite with confidence, not content that reads comfortably.

Dimension 2: Information Increment (the scarcest resource in the AI era)

AI itself can write 90-point "correct nonsense," so the key to content quality now becomes:

• Whether it provides unique information that AI cannot generate from thin air—your own test data, customer feedback, industry insights, exclusive case studies
• Whether there areHuman judgment— Given the same facts, do you have a unique viewpoint, trade-offs, priorities
• Does it save readerstime— AI provides information; good content "makes the decision for the user"

Dimension 3: Structural parsability + reading experience (dual standard)

Readers in the AI era are twofold:humansandAI engines. Good content must appeal to both:

• For humans: clear logic, no fluff, hits the pain point directly
• For AI: structured (H2/H3, lists,FAQ, data annotations), so AI can extract and cite it

A practical checklist (review before writing/publishing)

Special note: let AI be the "draft machine" and humans be the "judge"

• Don't write content that "AI can spot as fake at a glance": no data, no cases, no opinions throughout — even AI itself won't cite you
• Division of labor: AI produces the framework and first draft; humans add tested data, real cases, and subjective judgment — this layer is the "originality" of the AI era
• Ultimate test: feed the content back to AI and ask "Would you cite this? What answer would you give based on it?" — whether AI is willing to cite you is the most objective content quality score in the AI era

Baidu's mechanism for identifying advertorials/low-quality marketing content

Hurricane Algorithm (targets content farms)

Baidu's Hurricane Algorithm launched in 2017 and has been upgraded multiple times; its core targets:

• Scraped and patched-together content: "pseudo-original" content spliced from multiple sources with shuffled paragraphs
• Clickbait content: title seriously mismatched with the body
• Cross-domain bulk scraping: a site publishing large amounts of content unrelated to its topic

Drizzle Algorithm (targets B2B advertorials)

Specifically aimed at low-quality advertorials on corporate sites:

• Keyword stuffingKeywordand contact information
• Large numbers of phone numbers and WeChat IDs interspersed in the body
• Empty page content whose main purpose is to display contact information

Typical signals that trigger penalties

The core logic behind how search engines differentiate

Search engines are not judging "whether you have a commercial purpose" but rather:

1. Does it provide value to users? — After reading this content, has the user's question been answered?
2. Is the information authentic and unique? — Does it offer insights or data that cannot be found elsewhere?
3. Is the experience good? — Can users read smoothly, or are they interrupted by ads and pop-ups?

In other words:An article that both promotes a product and genuinely helps users solve problems will not be penalized by search engines.

“The 80/20 rule”: the golden ratio for compliant promotional content

Extensive practice has verified that search-engine-friendly promotional content follows one principle:

• 80% of the lengthdevoted to providing real value (tutorials, analysis, data, comparisons)
• 20% of the lengthused to naturally introduce the product/brand (case studies, solutions, author introduction)

✓ Good example

An article on "How to Choose an Enterprise CRM System":

• The first 80%: objectively explaining the 5 core dimensions of CRM selection, the evaluation criteria for each dimension, and common industry pitfalls
• Bottom 20%: naturally introduce how your product solves a specific problem in the "real case studies" section

✗ Bad example

Articles with the same title:

• The opening paragraph vaguely says "CRM is very important"
• Then directly lists the product's 10 major features
• Ends with a purchase link and promotional information

SEO best practices for native advertising

If you really want to write promotional content, the following approaches can give it SEO value without getting penalized:

1. Start from usersearch intentwhen choosing topics: first research what users are searching for, then figure out how to integrate product information into the answer
2. Provide exclusive data or insights: industry reports, user research data, exclusive case studies—these are things advertorials don't have
3. Use real author identities: authors with a photo, bio, and industry background have better credibility and rankings
4. Internal linksnaturally and sparingly: at most 1-2 links to product pages throughout the article, appearing naturally in context
5. Allow objective comparisons: mentioning competitors isn't a bad thing—objective comparisons actually enhance content credibility

How to self-check whether content is risky

Ask yourself three questions:

1. If you removed all brand names and product links, would this article still have independent reading value?
2. Would a reader who doesn't know your company feel they "learned something" after reading it?
3. If you sent this content to peers, would they share it or think "another ad"?

If the answers to all three questions are positive, your content won't be judged as low-quality advertorial by search engines.

Practical recommendations

• Establish a "value-first" content review mechanism: before publishing each article, have a colleague from outside the marketing department read it and give feedback on whether they "learned something"—this simple test is more effective than any SEO checking tool
• Use data instead of stacking adjectives: replace "industry-leading" “ "rave user reviews" with "served over 3,000 enterprises" “ "NPS score of 72" ” (the above are example numbers, not real statistics)—both search engines and users trust specific numbers more
• Track user behavior metrics on "advertorial" pages: If the bounce rate exceeds 85% and the average time on page is under 30 seconds (rule-of-thumb thresholds), it means the content looks like an ad in users' eyes, and search engines will not be more lenient than users in their judgment

How should the two frameworks be used together?

Reading this far, you may ask: between the "three dimensions of AI judgment" mentioned earlier and this "search engine advertorial identification mechanism”" that follows, which one should take precedence?

The answer is to use them in combination, and in the AI era the former is becoming increasingly important:

One-sentence summary:Search engine rules determine whether your content "avoids penalties"; AI judgment criteria determine whether your content "deserves to be cited." The baseline of the traditional era (compliance) must still be upheld, but in the AI era the ceiling (being cited) is the real competitive edge.