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17 SEO Copywriting Tips To Help Your Rankings

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17 SEO Copywriting Tips To Help Your Rankings

Writing is already hard enough, but writing with the goal of ranking in Google requires even more strategic planning.

Successful SEO copywriters consider what users want, and how search engines actually work, throughout their writing process.

For those site owners who want to grow their visibility through content, understanding SEO copywriting is the right place to start.

What Is SEO Copywriting?

SEO copywriting is the process of creating content with the goal of ranking in search engines for relevant keywords.

The process can be applied to your homepage, product pages, blog posts, or even your profiles on review sites.

When done well, SEO copywriting can increase the total number of keywords that your content ranks for.

Why Does SEO Copywriting Matter To Ranking?

Google relies on natural language processing to understand what users are searching for and what our content is about.

Over the years, NLP models have gotten far more advanced.

If you want to learn more about NLP technology, put some of your own website content into Google’s Natural Language API Demo.

Then, see how Google works to understand it.

Screenshot from Google’s Natural Language Processing API Demo Tool, December 2021
Syntax Analysis in Google's Natural Language Processing API Demo ToolScreenshot from Google’s Natural Language Processing API Demo Tool, December 2021

Because of Google’s advancements in NLP, SEO copywriting has evolved to be far less about quick tricks and far more about creating informative and valuable content for users.

But as seen above, Google is still a robot.

SEO copywriters should consider how search engine technology actually works and leverage that knowledge when writing their content.

SEO Copywriting Tips For Better Rankings

The best content will always be created with users in mind.

But, there are strategic choices copywriters can make to help crawlers better understand their content and promote it accordingly.

Here are some SEO copywriting tips for creating content that is loved by both users and search engines alike.

Research And Prewriting

1. Choose A Realistic Keyword Goal

Before you start writing, you should have a clear keyword target in mind. But make sure you set your content up for success by setting realistic and achievable keyword goals.

Keyword research is the foundation of the SEO copywriting process.

You might be tempted to choose industry keywords that have higher search volume, but those keywords are often extremely competitive.

If you are a website with less authority, you’re unlikely to rank on page one for those terms, no matter how high-quality your content is.

So how do you know if your content stands a chance of ranking?

Keyword difficulty scores can serve as a benchmark for your keyword goals.

Keyword difficulty score in the SearchAtlas keyword researcher toolScreenshot from SearchAtlas, December 2021
Keyword Difficulty score in Ahref's Keyword ExplorerScreenshot from Ahrefs, December 2021

I suggest finding relevant keywords with difficulty scores that are less than or equal to your site’s DA.

These keywords might be long-tail or have more informational search intent, but they can present real opportunities for your content to rank quickly and start driving clicks.

2. Analyze The Top-Ranking Content 

Want to know what it will take to rank? Look at the content that is already on page one.

Review the top-ranking pieces of content and use them as models for your own content creation.

How long is the content? What are the page titles and meta descriptions that are enticing the users to click?

Top-Ranking Content for the Keyword Screenshot from SearchAtlas, December 2021

The goal here is not to create a carbon copy of your competitors, but to better understand what content, authority, and page experience signals that Google crawlers are responding to.

3. Understand And Write For Search Intent

Search intent is often narrowed down into four categories: Navigational, Informational, Transactional, and Commercial.

The search intent of your target keyword determines what type of content you should create.

For transactional keywords, Google is more likely to promote product or service pages knowing that the user wants to make a purchase.

For informational queries, Google more often ranks blogs, top-ten lists, how-to articles, and resource-driven content types.

Most likely, your keyword can be categorized in the above four categories, so strive to meet that intent with your content.

4. Outline Your Structure

Not all content outlines will look exactly alike, but the idea is to determine the overall topic, subtopics, headings, and main points the content will include.

If you’re optimizing properly, your keyword targets will have a prominent place in these structural components.

Not all copywriters like to work from outlines, but they can be very useful in ensuring proper on-page SEO practices.

5. Prioritize Quality Over Everything Else

Google wants to rank quality content for its users.

But what is quality in the eyes of crawlers? Relevance, load times, backlinks, and referring domains, to name just a few.

In terms of the quality signals that are communicated through the writing, Google is looking for:

  • Comprehensive, in-depth content.
  • Original reporting and analysis.
  • Expert authorship and sourcing.
  • Proper grammar and spelling.

Do your best to meet these signals, and Google is more likely to see your website as high-quality.

The SEO Copywriting Process

6. Explore Your Topic In-depth

Although content length is not a ranking factor, there is a strong correlation between longer content and top rankings.

That’s because long content is more likely to display the quality signals listed in tip #5. Additional studies have shown that longer content also earns more backlinks and social engagements.

So do your best to be comprehensive and explore your content in-depth.

Keyword tools can help you expand on your content by showing you the subtopics that have a relationship to your keyword goal.

7. Write For Passage Ranking

Google’s Passage Ranking update went live in early 2021. As a result, Google no longer just indexes and ranks web pages, but specific passages of content.

For example, the below content provides a thorough answer to the search query, [What is an SEO assistant?].

When the user clicks on the SERP result, Google has indexed the exact part of the web page that answers that question and highlights it for users.

Example of Passage Ranking from ZipRecruiterScreenshot from ZipRecruiter, December 2021

Passage Ranking means that your content has so many opportunities to rank for multiple queries.

Strategic use of structure, headlines, and questions is key to helping passages of your content rank well in search.

8. Use A Content Optimization Tool

Leveraging AI and NLP tools can result in major boosts in keyword rankings.

Clearscope, SearchAtlas, SEMrush, and others all have content optimization software that eliminates some of the guesswork of the SEO copywriting process.

These tools identify common words and topics used in top-ranking content and suggest similar terms for you to include in yours. As long as you incorporate them naturally, the results can be significant.

Screenshot from Google Search Console showing increased impressions and average positionsScreenshot of Google Search Console, December 2021

I’ve seen content tools have an almost immediate impact on the total number of keywords, impressions, and average positions that web pages earn.

More SEO copywriters should be using them.

9. Offer Answers To Related Questions

Another way to improve keyword rankings is to answer common questions that users are asking in relation to your target keyword.

There are a couple of ways you can find out what these questions are: Google Search and a keyword tool.

Look to People Also Ask and autocomplete to see what common questions people are asking about the topic. Then, make sure you include those questions and their answers in your content.

Screenshot from Google displaying autcompletesScreenshot from search for [how to fix garbage disposal], Google, December 2021

Similarly, some keyword tools can tell you the common questions that searchers are asking.

Screenshot of google.com showing people also askScreenshot from search for [how to fix garbage disposal], Google, December 2021

10. Include Synonyms And Keywords In Your Headings

It’s important to include your keywords in your h1s and h2s, but Google is now smart enough to understand synonyms and other related terms.

Choose words that have a semantic relationship with your primary keyword target.

Google’s NLP algorithms use them to understand your content more deeply.

Adding these terms into your headings can help you signal strong relevance but without keyword stuffing.

11. Avoid Long Sentences, Long Paragraphs, And Misspellings

In terms of readability, you want your content to be easily understood by a variety of people. If your content is too academic or technical, some may choose to bounce back to the SERPs.

Similarly, content that is poorly written or full of typos will deter readers.

Aim for shorter sentences and paragraphs to improve the reading experience.

Some SEO tools suggest a grade level, but the idea is to keep the language simple and accessible to as many people as possible.

Copywriting Extras

12. Break Up Your Content With Rich Media

Although long-form text is important to ranking, your content should have other non-textual elements that help readers stay engaged.

Make sure you include images, videos, or infographics in your content, particularly to break up long passages of text.

Google likes to see content that incorporates rich media, so leverage it to your advantage.

If that rich media slows down the performance of your pages though, it can work against you. So make sure any rich media is optimized for speed and performance.

13. Include Relevant Links With Contextual Anchor Text

Your internal and external links, as well as the anchor text of those links, are also important quality signals to Google.

Make sure you link to relevant, authoritative sources. Also, make sure you utilize anchor text best practices:

  • Anchor text should be relevant to the destination page.
  • Don’t use too much exact match anchor text.
  • Avoid generic anchor text (e.g. “click here”).
  • Use contextual anchor text as often as possible.

14. Make Your Content Easy To Navigate 

Features like a table of contents and jumplinks make your content more user-friendly.

This is particularly true for longer articles or resource pages.

adding jumplinks in wordpressScreenshot from WordPress, December 2021

Google crawlers like to see these navigational elements on the page that improve UX. Make sure you incorporate them whenever you can.

After The Writing

15. Make Sure That Google Understands Your Content

A week or so after you publish your content, login into your Google Search Console account to confirm that Google is understanding it correctly.

See what keywords you are earning impressions for.

If they are close to or relevant to your original keyword goal, great. If not, you may need to revise the content.

Higher positions and clicks will come with time and authority building, but impressions are a good early sign that Google understands your content and knows when to promote it.

16. Optimize And Test Your Meta Tags

Google now rewrites page titles and meta descriptions when it sees fit, but this only happens about 20% of the time.

It is still important to write optimized meta tags so Google understands your content and users are enticed to click.

However, you don’t have to take a one-and-done approach to meta tag optimization.

If after several months, your content gets to page one but still has a low click-through rate, test out page titles and meta descriptions to see which produce the best results.

17. Revise And Update Accordingly

Over time, your content will eventually become outdated.

New information may become available, keywords may grow more competitive, links may break, and more.

So make sure to revisit old or underperforming content to see if more attention is needed.

Your most important content assets should be updated at least once a year, particularly if they are discussing industry trends or analysis.

Final Thoughts On SEO Copywriting

The reality is, SEO copywriting doesn’t end after the content is published on your website.

The internet changes, algorithms evolve, and your content needs to be updated accordingly.

If you deploy this final tip, you can increase the shelf-life of your content so it maintains top keyword rankings for years to come.

More resources:


Featured Image: WarmWorld/Shutterstock




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Google CEO Confirms AI Features Coming To Search “Soon”

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Google CEO Confirms AI Features Coming To Search "Soon"

Google announced today that it will soon be rolling out AI-powered features in its search results, providing users with a new, more intuitive way to navigate and understand the web.

These new AI features will help users quickly understand the big picture and learn more about a topic by distilling complex information into easy-to-digest formats.

Google has a long history of using AI to improve its search results for billions of people.

The company’s latest AI technologies, such as LaMDA, PaLM, Imagen, and MusicLM, provide users with entirely new ways to engage with information.

Google is working to bring these latest advancements into its products, starting with search.

Statement From Google CEO Sundar Pichai

Sundar Pichai, CEO of Google and Alphabet, released a statement on Twitter about a conversational AI service that will be available in the coming weeks.

Bard, powered by LaMDA, is Google’s new language model for dialogue applications.

According to Pichai, Bard, which leverages Google’s vast intelligence and knowledge base, can deliver accurate and high-quality answers:

“In 2021, we shared next-gen language + conversation capabilities powered by our Language Model for Dialogue Applications (LaMDA). Coming soon: Bard, a new experimental conversational #GoogleAI service powered by LaMDA.

Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence, and creativity of our large language models. It draws on information from the web to provide fresh, high-quality responses. Today we’re opening Bard up to trusted external testers.

We’ll combine their feedback with our own internal testing to make sure Bard’s responses meet our high bar for quality, safety, and groundedness and we will make it more widely available in coming weeks. It’s early, we will launch, iterate and make it better.”

In Summary

Increasingly, people are turning to Google for deeper insights and understanding.

With the help of AI, Google can consolidate insights for questions where there is no one correct answer, making it easier for people to get to the core of what they are searching for.

In addition to the AI features being rolled out in search, Google is also introducing a new experimental conversational AI service called Bard. Powered by LaMDA, Bard will use Google’s vast intelligence and knowledge base to deliver accurate and high-quality answers to users.

Google continues demonstrating its commitment to making search more intuitive and effective for users. As Pichai said in his statement, the company will continue to launch, iterate, and improve these new offerings in the coming weeks and months.

Source: Google



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Google Updates Structured Data Guidance To Clarify Supported Formats

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Google Updates Structured Data Guidance To Clarify Supported Formats

Google updated the structured data guidance to better emphasize that all three structured data formats are acceptable to Google and also explain why JSON-LD is is recommended.

The updated Search Central page that was updated is the Supported Formats section of the Introduction to structured data markup in Google Search webpage.

The most important changes were to add a new section title (Supported Formats), and to expand that section with an explanation of supported structured data formats.

Three Structured Data Formats

Google supports three structured data formats.

  1. JSON-LD
  2. Microdata
  3. RDFa

But only one of the above formats, JSON-LD, is recommended.

According to the documentation, the other two formats (Microdata and RDFa) are still fine to use. The update to the documentation explains why JSON-LD is recommended.

Google also made a minor change to a title of a preceding section to reflect that the section addresses structured data vocabulary

The original section title, Structured data format, is now Structured data vocabulary and format.

Google added a section title the section that offers guidance on Google’s preferred structured data format.

This is also the section with the most additional text added to it.

New Supported Formats Section Title

The updated content explains why Google prefers the JSON-LD structured data format, while confirming that the other two formats are acceptable.

Previously this section contained just two sentences:

“Google Search supports structured data in the following formats, unless documented otherwise:

Google recommends using JSON-LD for structured data whenever possible.”

The updated section now has the following content:

“Google Search supports structured data in the following formats, unless documented otherwise.

In general, we recommend using a format that’s easiest for you to implement and maintain (in most cases, that’s JSON-LD); all 3 formats are equally fine for Google, as long as the markup is valid and properly implemented per the feature’s documentation.

In general, Google recommends using JSON-LD for structured data if your site’s setup allows it, as it’s the easiest solution for website owners to implement and maintain at scale (in other words, less prone to user errors).”

Structured Data Formats

JSON-LD is arguably the easiest structured data format to implement, the easiest to scale, and the most straightforward to edit.

Most, if not all, WordPress SEO and structured data plugins output JSON-LD structured data.

Nevertheless, it’s a useful update to Google’s structured data guidance in order to make it clear that all three formats are still supported.

Google’s documentation on the change can be read here.

Featured image by Shutterstock/Olena Zaskochenko



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Ranking Factors & The Myths We Found

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Ranking Factors & The Myths We Found

Yandex is the search engine with the majority of market share in Russia and the fourth-largest search engine in the world.

On January 27, 2023, it suffered what is arguably one of the largest data leaks that a modern tech company has endured in many years – but is the second leak in less than a decade.

In 2015, a former Yandex employee attempted to sell Yandex’s search engine code on the black market for around $30,000.

The initial leak in January this year revealed 1,922 ranking factors, of which more than 64% were listed as unused or deprecated (superseded and best avoided).

This leak was just the file labeled kernel, but as the SEO community and I delved deeper, more files were found that combined contain approximately 17,800 ranking factors.

When it comes to practicing SEO for Yandex, the guide I wrote two years ago, for the most part, still applies.

Yandex, like Google, has always been public with its algorithm updates and changes, and in recent years, how it has adopted machine learning.

Notable updates from the past two-three years include:

  • Vega (which doubled the size of the index).
  • Mimicry (penalizing fake websites impersonating brands).
  • Y1 update (introducing YATI).
  • Y2 update (late 2022).
  • Adoption of IndexNow.
  • A fresh rollout and assumed update of the PF filter.

On a personal note, this data leak is like a second Christmas.

Since January 2020, I’ve run an SEO news website as a hobby dedicated to covering Yandex SEO and search news in Russia with 600+ articles, so this is probably the peak event of the hobby site.

I’ve also spoken twice at the Optimization conference – the largest SEO conference in Russia.

This is also a good test to see how closely Yandex’s public statements match the codebase secrets.

In 2019, working with Yandex’s PR team, I was able to interview engineers in their Search team and ask a number of questions sourced from the wider Western SEO community.

You can read the interview with the Yandex Search team here.

Whilst Yandex is primarily known for its presence in Russia, the search engine also has a presence in Turkey, Kazakhstan, and Georgia.

The data leak was believed to be politically motivated and the actions of a rogue employee, and contains a number of code fragments from Yandex’s monolithic repository, Arcadia.

Within the 44GB of leaked data, there’s information relating to a number of Yandex products including Search, Maps, Mail, Metrika, Disc, and Cloud.

What Yandex Has Had To Say

As I write this post (January 31st, 2023), Yandex has publicly stated that:

the contents of the archive (leaked code base) correspond to the outdated version of the repository – it differs from the current version used by our services

And:

It is important to note that the published code fragments also contain test algorithms that were used only within Yandex to verify the correct operation of the services.

So, how much of this code base is actively used is questionable.

Yandex has also revealed that during its investigation and audit, it found a number of errors that violate its own internal principles, so it is likely that portions of this leaked code (that are in current use) may be changing in the near future.

Factor Classification

Yandex classifies its ranking factors into three categories.

This has been outlined in Yandex’s public documentation for some time, but I feel is worth including here, as it better helps us understand the ranking factor leak.

  • Static factors – Factors that are related directly to the website (e.g. inbound backlinks, inbound internal links, headers, and ads ratio).
  • Dynamic factors – Factors that are related to both the website and the search query (e.g. text relevance, keyword inclusions, TF*IDF).
  • User search-related factors – Factors relating to the user query (e.g. where is the user located, query language, and intent modifiers).

The ranking factors in the document are tagged to match the corresponding category, with TG_STATIC and TG_DYNAMIC, and then TG_QUERY_ONLY, TG_QUERY, TG_USER_SEARCH, and TG_USER_SEARCH_ONLY.

Yandex Leak Learnings So Far

From the data thus far, below are some of the affirmations and learnings we’ve been able to make.

There is so much data in this leak, it is very likely that we will be finding new things and making new connections in the next few weeks.

These include:

  • PageRank (a form of).
  • At some point Yandex utilized TF*IDF.
  • Yandex still uses meta keywords, which are also highlighted in its documentation.
  • Yandex has specific factors for medical, legal, and financial topics (YMYL).
  • It also uses a form of page quality scoring, but this is known (ICS score).
  • Links from high-authority websites have an impact on rankings.
  • There’s nothing new to suggest Yandex can crawl JavaScript yet outside of already publicly documented processes.
  • Server errors and excessive 4xx errors can impact ranking.
  • The time of day is taken into consideration as a ranking factor.

Below, I’ve expanded on some other affirmations and learnings from the leak.

Where possible, I’ve also tied these leaked ranking factors to the algorithm updates and announcements that relate to them, or where we were told about them being impactful.

MatrixNet

MatrixNet is mentioned in a few of the ranking factors and was announced in 2009, and then superseded in 2017 by Catboost, which was rolled out across the Yandex product sphere.

This further adds validity to comments directly from Yandex, and one of the factor authors DenPlusPlus (Den Raskovalov), that this is, in fact, an outdated code repository.

MatrixNet was originally introduced as a new, core algorithm that took into consideration thousands of ranking factors and assigned weights based on the user location, the actual search query, and perceived search intent.

It is typically seen as an early version of Google’s RankBrain, when they are indeed two very different systems. MatrixNet was launched six years before RankBrain was announced.

MatrixNet has also been built upon, which isn’t surprising, given it is now 14 years old.

In 2016, Yandex introduced the Palekh algorithm that used deep neural networks to better match documents (webpages) and queries, even if they didn’t contain the right “levels” of common keywords, but satisfied the user intents.

Palekh was capable of processing 150 pages at a time, and in 2017 was updated with the Korolyov update, which took into account more depth of page content, and could work off 200,000 pages at once.

URL & Page-Level Factors

From the leak, we have learned that Yandex takes into consideration URL construction, specifically:

  • The presence of numbers in the URL.
  • The number of trailing slashes in the URL (and if they are excessive).
  • The number of capital letters in the URL is a factor.
Screenshot from author, January 2023

The age of a page (document age) and the last updated date are also important, and this makes sense.

As well as document age and last update, a number of factors in the data relate to freshness – particularly for news-related queries.

Yandex formerly used timestamps, specifically not for ranking purposes but “reordering” purposes, but this is now classified as unused.

Also in the deprecated column are the use of keywords in the URL. Yandex has previously measured that three keywords from the search query in the URL would be an “optimal” result.

Internal Links & Crawl Depth

Whilst Google has gone on the record to say that for its purposes, crawl depth isn’t explicitly a ranking factor, Yandex appears to have an active piece of code that dictates that URLs that are reachable from the homepage have a “higher” level of importance.

Yandex factorsScreenshot from author, January 2023

This mirrors John Mueller’s 2018 statement that Google gives “a little more weight” to pages found more than one click from the homepage.

The ranking factors also highlight a specific token weighting for webpages that are “orphans” within the website linking structure.

Clicks & CTR

In 2011, Yandex released a blog post talking about how the search engine uses clicks as part of its rankings and also addresses the desires of the SEO pros to manipulate the metric for ranking gain.

Specific click factors in the leak look at things like:

  • The ratio of the number of clicks on the URL, relative to all clicks on the search.
  • The same as above, but broken down by region.
  • How often do users click on the URL for the search?

Manipulating Clicks

Manipulating user behavior, specifically “click-jacking”, is a known tactic within Yandex.

Yandex has a filter, known as the PF filter, that actively seeks out and penalizes websites that engage in this activity using scripts that monitor IP similarities and then the “user actions” of those clicks – and the impact can be significant.

The below screenshot shows the impact on organic sessions (сессии) after being penalized for imitating user clicks.

Image Source: Russian Search NewsImage from Russian Search News, January 2023

User Behavior

The user behavior takeaways from the leak are some of the more interesting findings.

User behavior manipulation is a common SEO violation that Yandex has been combating for years. At the 2020 Optimization conference, then Head of Yandex Webmaster Tools Mikhail Slevinsky said the company is making good progress in detecting and penalizing this type of behavior.

Yandex penalizes user behavior manipulation with the same PF filter used to combat CTR manipulation.

Dwell Time

102 of the ranking factors contain the tag TG_USERFEAT_SEARCH_DWELL_TIME, and reference the device, user duration, and average page dwell time.

All but 39 of these factors are deprecated.

Yandex factorsScreenshot from author, January 2023

Bing first used the term Dwell time in a 2011 blog, and in recent years Google has made it clear that it doesn’t use dwell time (or similar user interaction signals) as ranking factors.

YMYL

YMYL (Your Money, Your Life) is a concept well-known within Google and is not a new concept to Yandex.

Within the data leak, there are specific ranking factors for medical, legal, and financial content that exist – but this was notably revealed in 2019 at the Yandex Webmaster conference when it announced the Proxima Search Quality Metric.

Metrika Data Usage

Six of the ranking factors relate to the usage of Metrika data for the purposes of ranking. However, one of them is tagged as deprecated:

  • The number of similar visitors from the YandexBar (YaBar/Ябар).
  • The average time spent on URLs from those same similar visitors.
  • The “core audience” of pages on which there is a Metrika counter [deprecated].
  • The average time a user spends on a host when accessed externally (from another non-search site) from a specific URL.
  • Average ‘depth’ (number of hits within the host) of a user’s stay on the host when accessed externally (from another non-search site) from a particular URL.
  • Whether or not the domain has Metrika installed.

In Metrika, user data is handled differently.

Unlike Google Analytics, there are a number of reports focused on user “loyalty” combining site engagement metrics with return frequency, duration between visits, and source of the visit.

For example, I can see a report in one click to see a breakdown of individual site visitors:

MetrikaScreenshot from Metrika, January 2023

Metrika also comes “out of the box” with heatmap tools and user session recording, and in recent years the Metrika team has made good progress in being able to identify and filter bot traffic.

With Google Analytics, there is an argument that Google doesn’t use UA/GA4 data for ranking purposes because of how easy it is to modify or break the tracking code – but with Metrika counters, they are a lot more linear, and a lot of the reports are unchangeable in terms of how the data is collected.

Impact Of Traffic On Rankings

Following on from looking at Metrika data as a ranking factor; These factors effectively confirm that direct traffic and paid traffic (buying ads via Yandex Direct) can impact organic search performance:

  • Share of direct visits among all incoming traffic.
  • Green traffic share (aka direct visits) – Desktop.
  • Green traffic share (aka direct visits) – Mobile.
  • Search traffic – transitions from search engines to the site.
  • Share of visits to the site not by links (set by hand or from bookmarks).
  • The number of unique visitors.
  • Share of traffic from search engines.

News Factors

There are a number of factors relating to “News”, including two that mention Yandex.News directly.

Yandex.News was an equivalent of Google News, but was sold to the Russian social network VKontakte in August 2022, along with another Yandex product “Zen”.

So, it’s not clear if these factors related to a product no longer owned or operated by Yandex, or to how news websites are ranked in “regular” search.

Backlink Importance

Yandex has similar algorithms to combat link manipulation as Google – and has since the Nepot filter in 2005.

From reviewing the backlink ranking factors and some of the specifics in the descriptions, we can assume that the best practices for building links for Yandex SEO would be to:

  • Build links with a more natural frequency and varying amounts.
  • Build links with branded anchor texts as well as use commercial keywords.
  • If buying links, avoid buying links from websites that have mixed topics.

Below is a list of link-related factors that can be considered affirmations of best practices:

  • The age of the backlink is a factor.
  • Link relevance based on topics.
  • Backlinks built from homepages carry more weight than internal pages.
  • Links from the top 100 websites by PageRank (PR) can impact rankings.
  • Link relevance based on the quality of each link.
  • Link relevance, taking into account the quality of each link, and the topic of each link.
  • Link relevance, taking into account the non-commercial nature of each link.
  • Percentage of inbound links with query words.
  • Percentage of query words in links (up to a synonym).
  • The links contain all the words of the query (up to a synonym).
  • Dispersion of the number of query words in links.

However, there are some link-related factors that are additional considerations when planning, monitoring, and analyzing backlinks:

  • The ratio of “good” versus “bad” backlinks to a website.
  • The frequency of links to the site.
  • The number of incoming SEO trash links between hosts.

The data leak also revealed that the link spam calculator has around 80 active factors that are taken into consideration, with a number of deprecated factors.

This creates the question as to how well Yandex is able to recognize negative SEO attacks, given it looks at the ratio of good versus bad links, and how it determines what a bad link is.

A negative SEO attack is also likely to be a short burst (high frequency) link event in which a site will unwittingly gain a high number of poor quality, non-topical, and potentially over-optimized links.

Yandex uses machine learning models to identify Private Blog Networks (PBNs) and paid links, and it makes the same assumption between link velocity and the time period they are acquired.

Typically, paid-for links are generated over a longer period of time, and these patterns (including link origin site analysis) are what the Minusinsk update (2015) was introduced to combat.

Yandex Penalties

There are two ranking factors, both deprecated, named SpamKarma and Pessimization.

Pessimization refers to reducing PageRank to zero and aligns with the expectations of severe Yandex penalties.

SpamKarma also aligns with assumptions made around Yandex penalizing hosts and individuals, as well as individual domains.

Onpage Advertising

There are a number of factors relating to advertising on the page, some of them deprecated (like the screenshot example below).

Yandex factorsScreenshot from author, January 2023

It’s not known from the description exactly what the thought process with this factor was, but it could be assumed that a high ratio of adverts to visible screen was a negative factor – much like how Google takes umbrage if adverts obfuscate the page’s main content, or are obtrusive.

Tying this back to known Yandex mechanisms, the Proxima update also took into consideration the ratio of useful and advertising content on a page.

Can We Apply Any Yandex Learnings To Google?

Yandex and Google are disparate search engines, with a number of differences, despite the tens of engineers who have worked for both companies.

Because of this fight for talent, we can infer that some of these master builders and engineers will have built things in a similar fashion (though not direct copies), and applied learnings from previous iterations of their builds with their new employers.

What Russian SEO Pros Are Saying About The Leak

Much like the Western world, SEO professionals in Russia have been having their say on the leak across the various Runet forums.

The reaction in these forums has been different to SEO Twitter and Mastodon, with a focus more on Yandex’s filters, and other Yandex products that are optimized as part of wider Yandex optimization campaigns.

It is also worth noting that a number of conclusions and findings from the data match what the Western SEO world is also finding.

Common themes in the Russian search forums:

  • Webmasters asking for insights into recent filters, such as Mimicry and the updated PF filter.
  • The age and relevance of some of the factors, due to author names no longer being at Yandex, and mentions of long-retired Yandex products.
  • The main interesting learnings are around the use of Metrika data, and information relating to the Crawler & Indexer.
  • A number of factors outline the usage of DSSM, which in theory was superseded by the release of Palekh in 2016. This was a search algorithm utilizing machine learning, announced by Yandex in 2016.
  • A debate around ICS scoring in Yandex, and whether or not Yandex may provide more traffic to a site and influence its own factors by doing so.

The leaked factors, particularly around how Yandex evaluates site quality, have also come under scrutiny.

There is a long-standing sentiment in the Russian SEO community that Yandex oftentimes favors its own products and services in search results ahead of other websites, and webmasters are asking questions like:

Why does it bother going to all this trouble, when it just nails its services to the top of the page anyway?

In loosely translated documents, these are referred to as the Sorcerers or Yandex Sorcerers. In Google, we’d call these search engine results pages (SERPs) features – like Google Hotels, etc.

In October 2022, Kassir (a Russian ticket portal) claimed ₽328m compensation from Yandex due to lost revenue, caused by the “discriminatory conditions” in which Yandex Sorcerers took the customer base away from the private company.

This is off the back of a 2020 class action in which multiple companies raised a case with the Federal Antimonopoly Service (FAS) for anticompetitive promotion of its own services.

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Featured Image: FGC/Shutterstock



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