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12 Powerful Email Marketing Tips You Need to Know

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12 Powerful Email Marketing Tips You Need to Know

There is no doubt that email marketing is effective. But how many times have you sat down to begin an email marketing project and immediately felt overwhelmed?

Sometimes, it’s hard to know where to start, especially when working with a newer brand.

The good thing is that email marketing has never been easier, thanks to automation tools and innovative ways to deliver emails directly into subscribers’ inboxes.

If you don’t know where to begin or want to improve your current workflow, this article is for you.

So now, let’s look at some simple steps you can follow to ensure you’re using email marketing wisely.

Where To Begin With Email Marketing

So, you’re planning your email marketing strategy for your client. Where do you begin? Here are some helpful tips to get you started:

  • Keep your emails short and sweet. People get tired of reading long emails, so keep yours between 60 to 200 words.
  • People love visuals, especially in email marketing, so include images of your products or services.
  • Social proof helps convince readers that your offer is legitimate and worth their time. This includes sharing links or information in your emails from experts in the industry, positive testimonials, or influencers using the brand.
  • People want to know where to go next after reading your content. And since emails are usually opened on mobile devices, you need to provide a clear CTA at the end of each email. Whether it’s to a product page or recent content produced on the website.
  • Email marketing works best when you send regular emails. But even once a week isn’t enough. Studies show that people respond better to frequent emails than infrequent ones.

Now, let’s discuss the top 12 email marketing components for your strategy:

1. Create Optimized Lead Magnets

So, how do you get people to actually subscribe to your email listing? An effective lead magnet.

A lead magnet is usually the first thing visitors see when they land on a brand’s website. It gets them to click through and read more about a brand, so it needs to be eye-catching and compelling.

And if you don’t optimize your lead magnets for conversion, a brand could lose out on potential leads.

So, how do you make sure your lead magnets convert?

Your lead magnet should grab visitors’ attention right away. That means making it interesting, unique, and relevant to the business.

For example, you can use an incentive like a freebie or discount code to entice people to take action. You could also give away a free report or ebook in exchange for their name and email address.

Your lead magnet could also be the first email they receive, which can be a part of your welcome series (which I’ll talk about briefly).

It entices the users to keep receiving emails, so they don’t immediately unsubscribe after they receive a discount code or something similar.

2. Segment Your Subscribers

You’ve probably heard the term “subscriber segmentation.” It refers to a way of grouping your subscribers into groups based on their interests and behavior so that you can send them more relevant content, offers, and other messages.

This is an integral part of email marketing because it allows you to target your audience with personalized emails.

You can also use this technique to create multiple versions of your emails, such as a welcome email, a thank you email, and a follow-up email.

Segmenting your subscribers can help build trust and long-term interest for a brand because it presents them with information or offers they actually want to receive.

3. Craft A Welcome Series 

Welcome emails are usually sent automatically to new subscribers when they sign up, purchase a product, or make an account.

When creating a welcome series, you need to consider where the customer is in their journey with a brand. So, it’s beneficial to space the emails out over a set period of time and create each one with a specific intention.

A welcome series is a great way to keep potential customers engaged after they sign up. Especially since they receive emails from companies almost daily.

Some examples include: “Welcome! We hope you like our product” or “Your account has been activated.”

You can also send welcome emails to existing customers who haven’t logged in for a while.

For example, if someone signs up and doesn’t use the service for three months, you could send an email saying, “Hey, we noticed that you signed up recently. Would you be interested in using our service?”

This type of marketing is very effective because it’s personalized and targeted. It shows that you’re not sending out mass emails but rather ones specifically tailored to specific customers.

These emails are also a great way to help build trust with your customers and get them used to receiving emails from you.

4. Implement Automation

So now, you’ve done the work to craft an email series. Next, it’s time to automate their delivery, so you don’t have to send them out each time you need to, according to your schedule.

Automation in email marketing is easy to do using tools like MailChimp, Constant Contact, Campaign Monitor, and Convertkit.

These types of programs allow you to create automated emails based on triggers, such as when someone opens your email, clicks on a link, or purchases something from you.

This way, you no longer need to manually send out those emails, which can alleviate some stress when you’re dealing with a multitude of different subscribers.

5. Design Mobile-Friendly Emails

As I mentioned earlier, most people use their phones to check their emails, so making them mobile-friendly is crucial.

The email should be optimized for mobile phones if it promotes sales or discounts. For example, any sales information or product pictures should be easily viewed on their mobile device.

And users should be able to click on the promotion, link, or image and give them the option to view the brand’s site in their preferred browser on their phone.

The key elements to consider when designing mobile-friendly emails include:

  • Placing important links at the top of the page rather than down below.
  • Keeping graphics small.
  • Using text only where appropriate.
  • Optimizing images.
  • And testing different sizes of fonts and margins.

6. Personalize Your Emails

Even though the average person receives numerous unsolicited emails daily, sending personalized messages to potential leads is proven to boost response rates.

Personalizing your emails makes them feel less like spam. Plus, it gives your subscribers a sense of connection to you.

The key to successful email marketing is knowing exactly who you want to send emails and which messages resonate best with each group of recipients.

Once you know what works and what doesn’t, you can tailor your messages specifically to your audience and keep them coming back for more.

First, choose a subject line that clearly states what you will say in your email. This will help readers decide whether or not to click through your email.

Next, include a call to action, such as asking subscribers to check out a new product or sign up for a free trial.

Finally, customize each individual message by adding links to pages on your site where interested parties can read more information.

Get creative and do your research for the industry. For example, does adding emojis help to personalize the email, or is that a no-no for that specific industry?

7. A/B Test Email Content

The A/B testing of email content is a great way to improve your open rate. It’s also an excellent way to get more people on board with a product or service.

But it can be challenging to figure out what works best for you and your audience.

A/B testing helps marketers decide what works best for their business. For example, when designing email campaigns, it’s often necessary to split-test different versions of emails to determine which one performs better.

You can also test different subject lines. Subject lines are one of the most important parts of any email. They’ll help determine whether someone opens your message or not. It’s what hooks the subscriber to learn more.

The best way to test different variations of emails is to use A/B email testing software. This allows you to compare two versions side by side while showing only one version to half of your users at any given moment so that they don’t realize they’re receiving two different messages.

Most email automation platforms can also conduct A/B testing for your emails. And A/B testing isn’t just beneficial for email. For example, it’s important to test copy and content on a brand’s website, so A/B testing will come in handy in more ways than one.

8. Find The Best Timing

The best time to send emails to customers depends on several factors – such as when they last visited your website, what action they took while on your site, whether they completed any transactions, and more.

One way to determine which times work best for email campaigns is by using Google Analytics. You can use the Goal conversion section to view bounce rate, exit pages, and other data related to goal completion.

You should also consider other factors and incorporate them when you send emails based on people’s schedules. For example, you can see lower open rates on holidays, late into the evening, as well as Monday morning and Friday evenings.

9. Scrub Your List Of Non-Opens

It’s essential to manage your subscriber list. When you click “send” on your newsletter, your list contains all subscribers who did not open the email. If you see that certain people are ignoring all your emails, you might want to delete them from your list.

To delete them from your list, you need to go to the unsubscribe page, then select remove and confirm. This process may be repeated until all your non-opens are removed.

You don’t want to overload people who have already purchased or are no longer interested in the brand, so you don’t create a negative relationship with them.

Incorporating one of the email management tools to help you eliminate the consistent non-opens can help you manage your subscribers and decrease time spent on this repetitive task.

10. Include A Real Reply Email Address

This is one of the best ways to keep customers coming back for more. Users may want to send any follow-up emails directly to their spam folder if you don’t include an actual reply address.

But when you put your email address in the footer, they know exactly where to go. If a person has questions, they can email the brand’s team.

Again, this also helps build trust with the brand. They know they are communicating with real people who selected these emails for them versus being spammed with nonrelevant or generic content for the masses.

11. Experiment With Lead Generation Ads

The goal of lead generation ads is to reach people who may be interested in buying from the brand.

They usually appear at the top of the page, where they are visible for longer periods of time than other types of ads.

This means people tend to click on them more often than ads below the fold. So, as long as you don’t use these ads too frequently, you should be able to generate leads.

12. Utilize Email Analytics To Improve Campaigns

One way to utilize email analytics to improve campaigns is to check the bounce rate, opens, clicks, and unsubscribes for your emails. Then use that information to enhance your current efforts.

This includes sending emails at different times throughout the week, testing subject lines, changing up the call to action, and testing creative variations.

If you’re still struggling, try experimenting with lead magnets, such as free ebooks, white papers, and webinars.

These allow you to capture leads from those interested in learning about new topics. In addition, measuring results lets you know which emails work and which ones don’t.

You should also compare these variables (such as open rates) to industry metrics. For example, what’s the percentage of bounce rates for the industry you’re working with?

If you aren’t measuring results, you won’t have much data to base future decisions for your next email marketing campaign.

Final Takeaways

Email marketing is still one of the most effective ways to promote your online store, build relationships with customers, and generate sales.

The final step in this process is to put all these pieces together into an effective strategy. This means coming up with creative and effective ways to construct emails and email series.

It also means being able to measure the results of each tactic so that you can continue to improve your efforts going forward.

Leveraging email metrics and incorporating A/B testing can help build relationships with subscribers by presenting them with the information they want to read.

With a little bit of effort and creativity, you can use email marketing to increase a brand’s sales and help create long-term customers.

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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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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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