Search engine crawlers: who they are and how they influence search results

Search engine results continue to be shaped not only by algorithms but also by human evaluation. That is why technical SEO optimization and link building should be combined with an understanding of how crawlers evaluate the quality of content. In this article, we will consider who the crawlers are, how and what they influence, how their assessments affect the algorithms, and what specific steps businesses need to take to steadily improve their rankings.

Who are search engine crawlers?

Search Quality Raters are ordinary people hired by search engines or contractors to check the quality of search results. They are not «manual admins» who raise or lower sites on demand. Their role is as follows:

• assessors evaluate the compliance of query results with quality criteria (for example, Google Search Quality Rater Guidelines);
• they check the relevance, completeness of the answer, credibility of the source, and user experience on the page;
• perform tasks on selected queries, in different language and regional sets;
• provide «human feedback» that becomes a training set for machine learning models.

How assessors’ evaluations work and how they translate into algorithm changes

To put the knowledge about assessors into practice, it is useful to visualize the process as a chain:

Each stage of this chain is important – and the impact of your content on the SERPs goes through it. Let’s take a step-by-step look at what happens inside the system and what it means for business.

Collecting human ratings

Assessors receive tasks – specific search queries and sets of results (SERPs). Their job is to evaluate how well each result matches the query according to a number of criteria: relevance, completeness of the answer, authority of the source, risks for the user (especially in YMYL topics such as finance, medicine, etc.).

This is where the «human inspection» of your content takes place: the assessor checks not only the technical optimization for keywords, but also whether the page provides a clear, complete, and useful answer to the user’s request.

Aggregation and validation

After the assessors have given their ratings, their results are aggregated into large sets and checked for consistency. Several people can evaluate the same SERP combination – the system cuts off anomalies (one sharply different voice), weighs repeated signals, and calculates representative metrics. Consistency tests are also performed: whether different evaluators give similar verdicts for the same cases.

A single bad rating is not decisive – repeated, cross-checked signals are important. If several crawlers independently emphasize a page’s weakness (e.g., lack of evidence or inconsistency of intent), this signal carries weight and is included in the training data set that will influence the algorithm. Therefore, it is not only worth correcting individual errors, but also identifying systemic problems that can give many «red flags.»

Training models based on human feedback

Aggregated and filtered ratings are used for machine learning: models learn to associate page features (structure, availability of sources, content format, engagement signals) with human ratings of usefulness. This is a process where the algorithm detects patterns and automatically starts favoring the types of pages that have received high ratings. In this way, a person forms rules that the machine applies automatically.

Anything you do to improve the obvious human signs of quality, such as structured content, links to authoritative sources, clear answers to a query, will become a feature in the ranking model. Investing in expertise and transparency has a double return because it improves the user experience and reinforces the «features» that the models look for in training.

Testing and gradual release of changes

The trained model is not immediately turned on in all regions and queries – updates are tested in a controlled manner:

• A/B launches;
• canary testing on limited clusters of users;
• comparison of metrics (retention, CTR, satisfaction).

The assessors continue to monitor the results after the release, looking for unwanted side effects. Only after confirming that the changes are useful and do not cause harm are the changes rolled out.

The effects of algorithmic changes often appear in waves and at different times in different regions. Therefore, you need to track trends rather than reacting to a one-time decline. Moreover, the improvements you make may not be immediately apparent. It takes time for the model to «pick up» new patterns and start favoring them.

This way, people evaluate, the system learns, and then the changes are rolled out in stages. This means that the business strategy should combine quick changes (UX, technical) with long-term investments in the authority and usefulness of the content.

Criteria for evaluating content by assessors

Assessors look at the page the way a real user would: whether they received a quick, clear, and useful answer to their query.

It is important for businesses not only to know these criteria, but also to be able to systematically meet them.

1. Relevance and completeness of the answer.

Assessors evaluate how well the page clearly answers the query: there is the necessary information on the first screen and key facts, a logical structure, and closure of all sub-questions. The page should solve a specific user task without the need to search for additional sources.

Practical steps for business:

• • start the article with a short summary (snippet-ready);
  • add tables, checklists, FAQs for common questions;
  • answer related questions within one page.

For example, for the query «how to treat seasonal allergies in adults», the assessor expects authoritative and safe content: links to medical sources, a doctor’s signature, and warnings against self-diagnosis. If this is not the case, the rating will be low.

2. Expertise, authority, trust (E-A-T).

Assessors evaluate who is behind the content: whether the author has relevant experience and whether verified sources are provided, as well as the availability of reviews, cases, and confirmation of expertise. The page should demonstrate reliability and credibility, especially for YMYL topics (health, finance, law), so that the user can trust the information without additional verification.

Practical tips:

• • add author signatures with a short biography and a link to the profile;
  • indicate sources (studies, standards, norms);
  • publish cases, testimonials, and certificates that confirm the expertise.

For example, when asked for a «small business loan», the assessor expects transparent information: loan terms, official sources, and the author or expert.

3. Quality of user experience (UX).

Assessors take into account not only the text, but also how convenient and comfortable it is for the user to receive information: download speed, adaptation to mobile devices, and the level of intrusive advertising.

To improve it, you should

• • optimize page speed (images, cache, critical CSS);
  • remove aggressive interstitial ads;
  • provide a logical structure with subheadings and short blocks.

For example, if the query is «online accounting for sole proprietorships», the assessor expects the page to load quickly without intrusive ads. If the page is slow and overloaded with banners, the score will be low.

4. User intent.

The crawlers look at whether the page meets the type of query itself – informative, commercial, or navigational.

Practical steps:

• • clearly segment content by intent (information, comparison, purchase page);
  • use separate landing pages for different stages of the funnel;
  • optimize headlines for real search queries.

For example, if a user searches for «buy office chairs», the assessor expects a commercial page with products, prices, and delivery terms. If the user gets to an informational article about materials, it will be a bad sign.

5. Local relevance (for local businesses).

For requests with a local intent, crawlers check the accuracy of local data: name, address, business hours, phone number, reviews, and local content.

Tips for businesses:

• • update your Google Business Profile and local directories;
  • encourage customers to leave honest reviews;
  • add local pages with unique content and structured data.

For example, if a cafe has incorrect opening hours, the crawler will record the discrepancy and the page will lose positions in the local block.

A practical action plan for business

Here are practical steps that allow you to combine technical and content optimization to achieve consistent results in search results today.

Following this plan helps to avoid chaotic edits and the cost of ineffective actions. A systematic approach ensures a balanced work on the technical aspects of the site and the quality of the content, increasing the chances of long-term success in search results. It also makes it easier to evaluate the effectiveness of the changes made and plan the next steps.

Impact of assessor ratings on voice search and AI assistants

Modern voice search engines and AI assistants (e.g., Google Assistant, Siri, Alexa) generate answers based on the same algorithms as traditional search, but with a special emphasis on the accuracy and speed of the answer. Assessor ratings directly affect these results: if the content demonstrates clarity, structure, expertise, and trust, the algorithms recognize it as reliable for short voice responses.

So, by optimizing your content for the criteria of the crawlers, you simultaneously increase your chances of getting into the blocks used by voice assistants. For example, FAQ blocks, clear tables, or specific action steps on the page help AI quickly identify key facts and formulate an accurate answer to the user.

Olha Tyshchenko

Editor

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