- In Google's Search Quality Rater Guidelines, effort is described together with originality and skill as a measure of content quality.
- The working time invested alone says little about how useful the result is. A longer text is therefore not yet a better text.
- The use of generative AI alone determines neither the effort nor the quality of a page.
Content effort is not a new ranking criterion as such, but the ability of AI to create content within minutes has brought one question back to the center of search engine optimization:
How much work goes into a piece of content – and what do visitors get out of it?
These are the questions behind the topic of content effort. In Google's Search Quality Rater Guidelines, effort is described together with originality and skill as a measure of content quality.
What matters is what becomes recognizable on the finished page: your own insights, careful explanations, traceable tests or helpful features. The working time invested alone says little about how useful the result is.
In practice, this added value often takes time. Collecting your own data, evaluating experience and checking explanations can rarely be done in a few minutes. A longer text is therefore not yet a better text.
So if you believe you have created high-quality content within minutes and with little effort, you should definitely keep reading.
What Google means by “effort”
“Effort” is mentioned many times in the current Search Quality Rater Guidelines. Google uses it to describe the evaluation criteria for its quality raters. Their ratings serve to check the search systems. Taken together, the statements on content effort give a clear picture of how high-quality content can be recognized.
Effort, originality and skill belong together
As a general rule, MC is high quality if it takes a significant amount of effort, originality, and talent or skill to create the content.
Google associates high-quality content with traceable effort, originality and talent or skill. Effort is therefore directly related to the quality of the result.
For most pages, the quality of the MC can be determined by the amount of effort, originality, and talent or skill that went into the creation of the content.
For most pages, these characteristics are used to assess the quality of the main content. For SEO practice, this means: the content creator's own contribution must be traceable in the content.
Helpful features also count as effort
As a reminder, there are many types of effort that people put into content creation, from directly creating the content on the page to building custom page functionality.
Effort covers more than texts, images and videos. Custom-built features can also be part of it if they help visitors with their concern or with solving their problem.
The content must fulfill the purpose of the page
MC is Low quality if it is created without adequate effort, originality, talent, or skill necessary to achieve the purpose of the page in a satisfying way.
Google describes content as low quality if the effort, originality or skill required to fulfill the page's purpose satisfactorily is lacking. So what also matters is what task the page has.
Particularly high quality must be recognizable in the result
MC created with a very high level of effort, originality, talent, or skill such that the page achieves its purpose very well.
For the highest quality level, Google names content that fulfills its purpose very well through particularly high effort, great originality or special skill.
Very high quality MC shows evidence of a high level of effort, originality, talent, or skill.
This effort must show in the finished content. Your own insights, precise explanations and careful preparation make the work done traceable.
How does Google recognize “high effort” content?
Google describes “high effort” as recognizable work toward content fulfilling its purpose well for visitors. The focus is on the presentation of the content, editorial work and careful curation.
1. Structure, edit and select content carefully
High level of effort: The website or content creators worked hard to create content that achieves the purpose of the page. The MC is well-organized, edited, and curated to support the purpose.
This is the clearest definition. High effort shows in content that is sensibly structured, revised and aligned with the page's purpose. Google gives the following examples:
- A news article with accuracy, depth and clarity.
- A question-and-answer page or forum post with a substantial discussion among several participants.
- A well-structured craft tutorial with understandable, helpful steps that allow others to successfully reproduce the result.
Shortening, sorting out and simplifying can also be an expression of high effort. What matters is whether the editing makes the content more helpful.
2. Develop useful features and systems
Effort may go into designing page functionality or building systems that power a webpage, such as the creation of a page that offers machine translation as a service to users.
Google explicitly takes into account the development work behind a page. The effort can lie in a tool or a feature. A positive rating example is a working, easy-to-use BMI calculator.
The visible text may therefore only partially reflect the actual effort of a page.
3. Gain information through your own research
Accurate, original, in-depth, and investigative reporting requires a high level of skill/talent and effort.
For journalistic content, Google names accurate, original and in-depth research. Particularly high-quality reporting provides information that would not have become known without this research and makes the primary sources used traceable.
A strong characteristic of high-quality content is the additional insight that comes from your own work.
4. Present your own experiments and experience in a traceable way
In an example of the highest quality, Google praises a recipe post:
The author of this blog has documented her extensive experimentation with a chocolate chip cookie recipe (Experience), and her expertise and skill is demonstrated in the large quantity of unique, original, and very satisfying MC.
Here, extensive experiments of one's own are documented and made usable for readers. For recipe pages, Google also names original images, more detailed steps and comments from people who have tried the recipe as possible characteristics of additional effort.
Your own tests and experience are particularly valuable. Also because they cannot be replicated by AI.
The standard depends on the purpose
The amount of effort expected … to create satisfying content for their purpose.
Google does not name a fixed number of hours, minimum length or budget limit. The expected effort depends on format and task.
High effort therefore becomes recognizable where research, editing, development or participation noticeably improve the result for visitors.
What Google describes as “low effort”
Just as high-quality content can be recognized by clear criteria, the same applies to inferior or “low effort” content.
The following examples have a common denominator: the page hardly adds to existing content or contributes little to solving the user's problem.
Reposts without your own contribution
Social media reposts with little additional comment or discussion
This refers to republished social media content that is hardly supplemented by your own comments or discussion.
Adopted content without context
Pages with content from other sources (e.g. pages of embedded videos or pages with “repinned” images) with little additional comment, discussion, or curation by the content creator of the page
Examples are collections of embedded videos or adopted images. There is no classification, discussion or careful selection of one's own that offers visitors additional value.
Best-of lists without your own insights
“Best” lists based on existing reviews and lists with little original content
The criticism is of best-of lists that are mainly based on existing reviews and lists and add hardly any original content.
Automatically generated mass content without added value
Using automated tools (generative AI or otherwise) as a low-effort way to produce many pages that add little-to-no value for website visitors as compared to other pages on the web on the same topic.
This is about many automatically created pages that offer hardly any additional value compared to existing content on the same topic. This approach is cited as an example of “scaled content abuse”.
Filler text without contribution to the page's purpose
Sometimes, MC includes “filler” - low-effort content that adds little value and doesn’t directly support the purpose of the page.
Filler text lengthens the page without significantly advancing its purpose. For visitors, this makes it harder to reach the information they are looking for when the helpful passages move further down as a result.
Summaries with little added value
There is little original content. It requires low effort to summarize a discussion. This page offers little added value over the original source.
In this rating example, Google criticizes a summary that offers hardly any original content or additional value compared to the original discussion. This does not imply a blanket judgment on summaries: what matters here is the low added value of the specific example.
How Google classifies AI content
The use of generative AI alone determines neither the effort nor the quality of a page. The guidelines quoted distinguish based on what result is created and what it offers visitors.
AI does not automatically mean little effort
Likewise, the use of Generative AI tools alone does not determine the level of effort or Page Quality rating.
Neither the effort nor the quality rating of a page can be derived from the use of generative AI.
AI can produce high-quality content
Generative AI tools may be used for high quality and low quality content creation.
Google explicitly names both possibilities: AI can be used to create high-quality and low-quality content.
For example, a high level of effort may be involved in creating high quality original artwork using Generative AI tools.
As an example, Google names original, high-quality artworks whose creation with generative AI can require a lot of work.
AI does not replace your own added value
However, it’s also possible to use Generative AI tools to create Lowest quality content with little to no effort, little to no originality, and little to no added value for website visitors.
Likewise, AI can produce content that shows hardly any effort, originality or additional value and receives the lowest quality rating.
For practice, the question remains: which work improves the result? AI can help with creation. Your own experience, the verification of statements and helpful context must still show in the finished content.
How an algorithmic effort estimate is documented
Content effort also appears in the publicly preserved Content Warehouse documentation. There, the data structure QualityNsrPQData contains a field called contentEffort with this description: LLM-based effort estimation for article pages
This documents an effort estimate for article pages supported by a large language model. The entry goes beyond a general quality requirement: it describes a concrete technical field for such an estimate.
Numerical estimate instead of measuring working time
For contentEffort, the documentation provides a list of entries of the type QualityNsrVersionedFloatSignal. Each entry contains a numerical value (value) and a version identifier (versionId). The structure thus allows several versioned values to be stored.
A documented LLM estimate, however, is not time tracking. The field description explains neither the inputs used nor the evaluation criteria, the scale or the language model used. Nor does the numerical data type prove that the entire content quality is measured exactly.
Where the field is classified
contentEffort belongs to the data structure QualityNsrPQData. This is included in CompressedQualitySignals via the field pqDataProto. A separate field called ugcDiscussionEffortScore is also documented there, which is described as a quality signal for user-generated content.
The documentation does not state that both fields are calculated using the same method. A uniform effort score for all page types can therefore not be derived from the similar names.
What remains open about the ranking effect
The technical documentation proves the field and its described purpose. It does not prove how it is currently used in ranking.
The sources examined do not show:
- whether contentEffort currently feeds into the production ranking calculation;
- what weight the value receives, if any;
- which characteristics the language model takes into account for its estimate;
- whether a higher value leads directly to better positions.
A technical equation with the effort criterion of the Quality Rater Guidelines is not documented either. A connection is plausible but remains an interpretation. Google explicitly states that the ratings of the quality raters do not feed directly into its ranking algorithms.
For content work, this does not result in a reliable way to specifically increase an internal score. The reliable guidance remains the published quality requirements: content should be helpful, original, traceable and appropriate to its purpose.
Practical comparison: little added value or recognizable original work
The following table translates the quality characteristics described into editorial examples. It is a guide for content work and not a formula for a particular Google rating.
| Area | Little additional value | Recognizable original work and value |
|---|---|---|
| Curation | Third-party content is collected without recognizable review. | The selection is checked, justified and organized according to traceable criteria. |
| Automation | Location pages differ almost only by the city name. | Pages contain relevant local information and answer the questions about the respective location. |
| Research | The text rephrases common standard knowledge. | Your own measurements, observations or practical tests add to existing knowledge. |
| Images and videos | Visual material provides no additional explanation. | Photos, screenshots or videos show relevant details and document the experiences described. |
| Product comparisons | Manufacturer information is listed without your own review. | Test setup, results and experience with the products reviewed are traceable. |
| Page structure | Long introductions delay the answer. | The central answer comes early; details and special cases follow in a clear order. |
Five steps to content with recognizable added value
1. Deliver the central answer early
The most important information belongs where visitors find it quickly. Introductions should clarify the concern and lead directly to the answer. Passages that only add length can be dropped.
2. Add your own insights
Your own data, surveys, practical tests and documented experience can take an article beyond existing information. What matters is their relevance to the question the content answers.
3. Make your approach and results traceable
Anyone who tests products should explain the test procedure. Anyone who describes experience from a project should name the starting point, the approach and the result concretely. Original images, screenshots and methodological explanations can make this work visible.
4. Explain limits and special cases
A helpful article also shows when a recommendation does not fit, which requirements apply and where difficulties arise. Such details help readers apply information to their own situation.
5. Put information into context with reasons
Your own assessment gains strength through traceable arguments. This includes checking evidence, naming uncertainties and explaining conclusions. The context should make clear what can be derived from the information.
Checklist before publishing
- User goal: Does the page answer the central question, and can the answer be found quickly?
- Added value: What insight, explanation or help does it add compared to content already available?
- Traceability: Are experience, tests and results sufficiently documented?
- Depth: Are relevant requirements, limits and special cases covered?
- Context: Are assessments and conclusions justified?
The yardstick for content effort is the value the work done creates in the finished content. Research, experience and care help visitors when they show in clear answers, traceable evidence and helpful details.
