Google Clarifies How Helpful Content System Works

Google SearchLiaison cleared up a confusing passage in their Helpful Content System guidance that seemingly had the potential to cause inadvertent issues for innocent publishers.

Helpful Content System

Google’s Helpful Content System is based on a machine learning model that uses classifiers to generate a signal that is then used by Google’s ranking system to weed out low quality content.

A classifier is an algorithm in a machine learning model that assigns a label to an input. In the context of the Helpful Content System, the machine learning model is assigning a label to website content, which is turn generates a signal, like a thumbs-down.

That signal is also weighted, which means that a site with just a little unhelpful content gets a smaller thumbs down than a site with a lot of unhelpful content which would get a larger thumbs down.

The Helpful Content System generates a signal, which is one of hundreds or thousands of other signals used to rank a site (like links, relevancy, etc.).

Google Guidance Unintentionally Opaque

Google updated their guidance for the Helpful Content System during the last Helpful Content System in order to help add clarity of what this signal was so that publishers and SEOs could understand why sites lost rankings.

The word “opaque” means something that lacks clarify or transparency. And unfortunately there was one part of that guidance that seemed to be unintentionally opaque and consequently confusing.

This is the passage in question:

“Are you changing the date of pages to make them seem fresh when the content has not substantially changed?”

That passage is aimed at some users who are attempting to game Google’s freshness algorithm by making a relatively trivial change to the content then updating the publication date in order to trick Google into thinking that the old content is a newly published webpage.

But the problem is that many people return to a webpage and make minor changes to content to:

  • Fix typos
  • Replace or add a word to make it grammatically correct or clearer
  • Change words to make the content clearer

There are many legitimate but small changes that many people make to content.

The guidance that seemingly prohibited making small changes that results in date changes created the situation where a small improvement now held the potential to contribute to a negative assessment by the Helpful Content System.

This is exactly the issue flagged on X (formerly Twitter).

Luke Jordan (@lr_jordan) shared their valid concern:

“Google doesn’t understand nuance well enough to make blanket rules

It’s punishing websites for using a ‘last updated’ date for “small” changes

But in gaming, a patch/update could be as simple as an upgrade that cost 5 points now costs 6

And that tiny increase could change a lot about its usefulness

Users will want to know the post is up to date, and therefore relevant, so will refer to date and patch number

A genuinely valuable update might require changing the number 6 to 5, and a patch number from 9.0.1 to 9.0.2.

If the date says the guide was last updated 6 months ago, that makes no sense

Plus the (massively outdated) date shows in Google results, so people would click it far less too, with CTR being another ranking factor

Of course they can just pretend they understand all of this and being super duper helpful will always win!”

Google SearchLiaison responded:

“No, we don’t do this if updates are made to be helpful to people.

Not something we say.

Not in our guidelines.”

SearchLiaison is correct but because of the opacity of that one passage, it does appear to say what Luke Jordan says it means.

Luke followed up with:

“So, to confirm, you know if a single character change to an article is designed to be helpful for people?”

There is one additional post from Luke, accompanied with a screenshot of the passage in the guidance:

“cos it’s literally in your guidelines that you shouldn’t change the date of pages when the content has not substantially changed.”

SearchLiaison responded:

“The context of those question are if your doing something for Google.

If your just changing the date because you think “that’ll make Google think this is fresh,” you’re likely aligning with other behaviors that overall align with signals we use to identify the helpfulness of content.

It’s not just one thing. It’s not direct.

And it’s not an issue if you’re not doing things primarily for Google.”

Aligning With Other Behaviors

What SearchLiaison appears to be saying is that the date change tactic is just one of many tactics that the machine learning model uses to calculate the statistical probability that the webpage is employing SEO tactics for Google instead of doing something to create helpful and useful content.

There’s a thing about statistics where if you use only one metric in isolation the statistical model will make bad decisions.

That’s why in statistical models related to search it’s well documented that using multiple signals together to calculate the statistical probability is more accurate than using just one signal (metric).

If you’re new to this, check out this PDF of a statistical spam identification system that combines multiple features like on-page, off-page and user interaction metrics to arrive at the classification of whether a webpage is spam or not.

Not to put words into SearchLiaison’s response, but it seems they are implying that doing just one thing that’s a possible indicator of unhelpfulness is not enough to brand the webpage as unhelpful when there are no other negative signals in.

Here is what SearchLiaison said:

“If your just changing the date because you think “that’ll make Google think this is fresh,” you’re likely aligning with other behaviors that overall align with signals we use to identify the helpfulness of content.”

It’s good that SearchLiaison clarified this point because I also felt that the passage seemed overly broad and could lead to false positives (when an innocent site is classified as spam).

Featured image by Shutterstock/Merkushev Vasiliy

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