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18 Online Review Statistics Every Marketer Should Know

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18 Online Review Statistics Every Marketer Should Know

Online reviews are an unavoidable part of doing business in today’s digital age.

Every marketer worth their salt knows that online reputation is everything.

Whether you own or manage a small mom-and-pop restaurant, a computer software company, or a chain of coffee shops, your customers are likely to look for you online.

That means one of the first things they’ll do is look for online reviews about your business.

Of course, positive reviews help you to create a trusted brand, which people are more likely to purchase from. However, how you respond to negative reviews also says much about your business.

Why Online Reviews Are So Powerful

Yelp, Google Business Profile, TripAdvisor, and similar are a boon for consumers, giving them a platform to learn about businesses before patronizing them.

For business owners? Not so much.

It seems that no matter how hard you try, you’re bound to get that one bad review that could potentially overshadow all your glowing reviews.

Online reviews, however, are an unavoidable part of doing business online.

For millennials, reviews are empowering, helping them make an informed and thought-out purchase decision (useful when deciding if a restaurant’s $15 avocado toast is worth it).

If you still aren’t completely on board, here are online review statistics that may change your mind.

1. Positive & Negative Reviews Influence Consumers

According to a 2021 report by PowerReviews, over 99.9% of customers read reviews when they shop online.

Furthermore, 96% of customers look for negative reviews specifically. This figure was 85% back in 2018.

When people look for bad reviews, they’re interested in knowing some of the company’s weaknesses. Where could they improve? If the downfalls are minor, it makes the researcher feel assured.

A near-perfect rating is often viewed as less credible and leads to consumer skepticism if reviews are too positive.

2. Consumers Trust Reviews Like Recommendations From Loved Ones

BrightLocal’s local consumer survey shows that 49% of consumers trust reviews as much as personal recommendations from friends and family members.

Screenshot from BrightLocal, January 2023

When you consider just how much we trust the people we love, it’s compelling to think that every 1 in 2 people trust online reviews as much.

However, the research reveals that some occasions cause consumers to suspect a review’s validity. So, you do need to be mindful of this.

Situations that can raise suspicion that a review may be fake include:

  • The review is overboard in its praise (45%)
  • The review is one of many reviews with similar content (40%)
  • The reviewer uses a common pseudonym or is anonymous (38%)
  • The review is overboard in negativity (36%)
  • The review is one of only a few positive amongst many negative reviews (32%)
  • The review contains hardly any text and is just a star rating (31%)

3. The More Reviews, The Better Reputation

The More Reviews, the BetterScreenshot from BrightLocal, January 2023

BrightLocal’s research also found that 60% of consumers feel that the number of reviews a business has is critical when reviewing and deciding whether to use its services.

Although this has dropped since 2020, it’s still a high figure, especially compared to 2019, 2018, and 2017.

4. Most Consumers Don’t Trust Advertising

While online reviews are seeing a rise in consumer trust, the same can’t be said for traditional advertising.

According to Performance Marketing World, 84% of millennials don’t trust conventional advertising.

If anything, this finding is a sign of the times. People are tired of ads being pushed on their faces, especially ads that belie the truth of the quality of the products and services they get from brands.

5. Shoppers Research Product Reviews On Their Phones – Outside Of Your Store

OuterBox recently revealed that every 8 in 10 shoppers use their smartphones to look up product reviews while they are in-store.

Before buying an item, shoppers will quickly search to see what other people have had to say about the product in question.

Some will compare prices, determining whether they can find the item elsewhere cheaper.

This statistic shows how the online and offline worlds are becoming increasingly integrated. If you don’t have a good online review presence, it can have a negative impact on the number of sales you make in-store.

6. Reviews Shared On Twitter Increase Social Commerce

Yotpo has revealed that reviews on social media platforms increase social commerce, especially on Twitter. You can see this displayed in the chart below:

Reviews Shared on Twitter Increase Social Commerce by More Than 6%Screenshot from Yotpo.com, January 2023

When we think of social media, we associate it with building brand awareness. However, it’s also effective for driving sales.

Shopify recently published a survey that revealed the average conversion rate for the social media websites represented in the graph above:

  • The average conversion rate for LinkedIn is 0.47%
  • The average conversion rate for Twitter is 0.77%
  • The average conversion rate for Facebook is 1.85%

Yotpo Data found that when reviews are shared on social platforms, the conversion rate is 5.3 times higher for LinkedIn, 8.4 times higher for Twitter, and 40 times higher for Facebook.

All these statistics show us that reviews are an incredibly powerful form of social proof that results in higher conversion levels across LinkedIn, Twitter, and Facebook.

Furthermore, a lot of the eCommerce world is underestimating Twitter’s force.

7. Reviews Are Just As Important Among Jobseekers

If you thought consumers were the only ones concerned about reviews, think again.

Research published by Glassdoor indicates that 86% of employees and job seekers research reviews on a business and ratings to determine whether they should apply for a job.

Google Reviews on GlassdoorScreenshot from Glassdoor.com, January 2023

As competition for talent in certain industries gets tougher, companies will have no choice but to be more conscious about their employer brand if they wish to attract top talent.

8. 3.3 Stars Is The Minimum Rating Customers Accept

When deciding whether to engage with a business, it has been indicated that 3.3 stars out of 5 are the lowest rating customers are likely to consider.

If you have a lower rating than this, your business may be overlooked and lose valuable consumers to the competition.

It probably does not come as a shock to discover that only 13% of consumers will contemplate using a company with a rating of 2 stars or less.

9. Sustainability Is A Recurring Theme In Travel Reviews

The Expedia.com Travel Recovery Trend Report revealed that the environment and sustainability are two chief themes for online guest reviews.

Some of the terms most typically found in reviews include the following:

  • Renewable energy
  • LED light bulbs
  • Electric car charging
  • Single-use plastics
  • Recycling

Expedia believes that millennial and Gen-Z travelers are more likely to consider environmentally friendly travel options.

10. 18 – 34 Year Olds Trust Online Reviews as Much as Personal Recommendations

Research shows that 91% of 18 to 34-year-olds trust reviews online just as much as personal recommendations.

Let’s think about this for a second: we’re now trusting online comments just as much as we trust feedback from the people we know and love.

This shows how much high regard millennials and Gen Z give to online reviews.

11. Tiny Subject Line Changes Can Get More Reviews

When soliciting reviews, most businesses send an email post-purchase.

Yotpo studied the subject lines of 3.5 million of these post-purchase review request emails to discover what works and what doesn’t when asking customers for reviews.

While this is much more than a single statistic, here is a synopsis of the top subject line tweaks to get more reviews:

  • An emotional appeal doesn’t greatly impact the review response rates.
  • Include your store name to increase reviews.
  • Incentives inspire more reviews in every industry.
  • Ask a question in the subject line.
  • Exclamation points boost reviews for food and tobacco businesses!
  • Avoid using a totally uppercase word in your subject lines.

12. Reputation Management Software Pays For Itself

Podium released a very interesting report on online reviews, stating that 94% of local companies who utilize a reputation management tool make up for the cost with the ROI.

How your company appears online massively dictates what shows up in terms of your bottom line.

Because of this, companies are investing more in their reputations than ever before.

One way they do this is by investing in reputation management software. This gives them the ability to have clarity regarding how their business is reviewed online.

13. Customers Believe A Product Should Have 100+ Reviews

Power Reviews recently posted interesting statistics about the number of reviews shoppers want.

In a perfect world, 43% of consumers have indicated that they want to see more than 100 reviews for an item.

Take a look at the table below to see consumer expectations regarding review volume:

43% of Customers Believe a Product Should Have 100+ ReviewsScreenshot from PowerReviews.com, January 2023

Consumers indicate that a notably high volume of reviews can have a big, positive impact on their purchase likelihood.

Out of those surveyed, 64% indicated that they would be more likely to purchase an item if it had over 1,000 reviews than if it only had 100 reviews.

Furthermore, 54% are more likely to purchase an item if it has 10,000+ reviews compared to 1,000 reviews. So, more is always better when it comes to quantity.

14. Few Travelers Post Unsolicited Online Hotel Reviews

BrightLocal has also uncovered that 78% of travelers never post unsolicited online hotel reviews. This means you cannot simply rely on customers to post hotel reviews of their own free will. They need to be encouraged to do so.

Customers say that the main ways they have been asked to leave a review are as follows:

  • Via email (41%)
  • During the sale/in-person (35%)
  • When receiving an invoice or receipt (35%)
  • SMS text (27%)

You need to be mindful of how you approach customers when asking to leave a review. The last thing you want to do is come across as pushy. At the same time, you want to make customers feel compelled to post a comment.

Offering an incentive, such as a special discount or entry into a competition, is a good approach.

15. Consumers Are Becoming Increasingly Suspicious Of Facebook Reviews

While online consumers rely on reviews to make purchasing decisions, they’re also suspicious of fake reviews. In fact, 93% of Facebook account holders are suspicious of fake reviews on this social media platform.

Consumers Are Becoming Increasingly Suspicious Of Facebook ReviewsScreenshot from Brightlocal, January 2023

As you can see from the table, only 7% of users don’t feel at all suspicious about Facebook reviews.

Users also have low trust in Google, Yelp, and Amazon reviews.

16. Most Consumers Use Rating Filters

Did you know that 7 in 10 consumers utilize rating filters when looking for companies?

Out of all the different rating options, the most popular is to narrow down a search based on the rating it is, for example, to only show hotels with ratings of four stars or above.

This helps customers only view products, locations, and services that fall within their standards. No one wants to waste their time on things that don’t fit!

17. Customers Expect You To Respond To Negative Reviews Within 7 Days

When customers post negative reviews about a business, they expect a response. Not only this, but they don’t want to wait around for it.

Review Trackers have stated that 53% of customers expect companies to respond to negative feedback within one week.

One in three consumers has a shorter timeframe than this; three days or less.

Therefore, you really need to ensure you’re keeping up with the reviews you receive and responding appropriately.

18. Your Response To A Review Can Change How Customers View Your Business

Podium’s 2021 State of Reviews publication revealed that 56% of consumers had changed their perspective on a business based on how they responded to a review.

We know that it can make you feel sick to your stomach when you receive a bad review from a customer. However, this statistic shows that there is the potential to turn this into a positive.

If you respond empathetically and try to understand the customer, they will feel like you really care about them and the service they receive. You can turn an unsatisfied customer into a loyal one.

And, even if the consumer who has complained does not reply, the fact you’ve tried to rectify their grievance will show your business in a positive light when others read the review.

The Bottom Line On The Impact of Online Reviews

These statistics reveal one unavoidable truth: online reviews are important and are here to stay.

Simply put, online reviews are directly linked to consumer trust and creating social proof.

Rather than fear them, you should look at them as a way to get a direct line to your customers.

If you are yet to begin your efforts to manage your online reputation, now’s as good a time as any to get started by doing the following:

  • Educate your customers on the importance of leaving reviews, but make sure to communicate that these reviews will help you improve your business, which can only be a good thing for them.
  • Take charge of your brand on all review platforms. Respond to feedback and make sure complaints are managed in a timely and orderly fashion.
  • Claim your Google Business Profile to ensure that any information about your business on Google is accurate and updated.
  • Ask and encourage your customers to leave a review of your product or service.

More resources:

Featured Image: ParinPix/Shutterstock



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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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Google Updates Search Console Video Indexing Report

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Google Updates Search Console Video Indexing Report

Google’s updated Search Console Video indexing report now includes daily video impressions and a sitemap filter feature.

  • Google has updated the Search Console Video indexing report to provide more comprehensive insights into video performance in search results.
  • The updated report includes daily video impressions, which are grouped by page, and a new sitemap filter feature to focus on the most important video pages.
  • These updates are part of Google’s ongoing efforts to help website owners and content creators understand and improve the visibility of their videos in search results.



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