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Data-Backed Ways to Optimize for Google Featured Snippets



data backed ways to optimize for google featured snippets via mattgsouthern

New research into Google SERPs reveals the top ways of optimizing pages in order to maximize the potential of earning featured snippets.

SEMrush and Brado analyzed 1 million random SERPs with featured snippets to identify correlations between pages that earn these valuable search positions.

This data can be used by SEOs and site owners to create content that may have a better chance of being chosen for a featured snippet.

First, lets take a look at look at some general stats the study uncovered about featured snippets.

Featured Snippet Statistics

SEMRush and Brado studied 160 million keywords on desktop, and 46.1 million keywords on mobile, to find what percentage of keywords generate featured snippets.

Here’s a summary of their findings:

  • 19% of SERPs have featured snippets.
  • 7.3% of SERPs have double featured snippets.
  • 50% of a mobile screen is covered with a featured snippet.
  • 70% of featured snippets are paragraphs (an average of 42 words/249 characters).
  • 19.1% of featured snippets are lists (an average of 6 items/44 words)
  • 6.3% of featured snippets are tables (an average of 5 rows, 2 columns)
  • 4.6% of featured snippets are videos (an average of 6m35s)
  • Industries that have the greatest percentage of featured snippets are:
    • Travel
    • Computers & Electronics
    • Art & Entertainment
    • Science

Featured snippets appear most often for keywords with a specific search intent, such as long-tail keywords

Out of queries made up of 10 words, 55.5% have a featured snippet. In comparison, only 4.3% of single keyword searches have a featured snippet. The percentage gradually goes up as more words are added to a query, then drops off after 10 words.

Now let’s look at the common factors shared by content earning these featured snippet positions.

Optimizing Content For Google Featured Snippets

SEMRush breaks down the findings of its study and identifies these data-backed methods of optimizing content to earn featured snippets.

Answer Question-based Queries

The study finds 29% of queries triggering featured snippets start with a question-based word, such as “why,” “do,” and “can. Questions that start with “why” trigger the most featured snippets.

Of all “why” queries studied, 77.6% return a featured snippet. Queries starting with “can” have the second-largest percentage of featured snippets at 72.4%.

Date Your Content

Google frequently returns dated content in featured snippets.


Of the different types of featured snippets, these are the percentages that return content with a date:

Paragraph: 44%
List: 47%
Table: 19%
Video: 20%

Google also tends to keep featured snippets current; 70% of articles in featured snippets were published no later than 2-3 years ago.

However, older articles can still earn the featured snippet if they provide the best answer.

Use Subfolders Sparingly

According to the study, long URLs are less likely to earn a featured snippet. The “sweet spot” is a URL with 1-3 subfolders.

Of all featured snippets included in the study, 37.3% link to a URL with 2 subfolders. That’s followed by 1 subfolder at 21.9% and 3 subfolders at 21.2%.


To be clear, subfolders are the parts of the domain listed after forward slashes. As an example:

  • is the root domain. It has zero subfolders;
  • has one subfolder; and
  • has two subfolders.

It’s extremely unlikely that Google will return a website’s home page in the featured snippet position, as only 0.4% link to a domain with no subfolders.

Combine Multiple Questions in One Article

SEMRush recommends creating a “featured snippet hub,” which is be accomplished by answering multiple questions in a single piece of content.

This is said to increase the likelihood of earning multiple featured snippets with one URL.

However, I would be remiss not to mention SEMRush doesn’t provide any particular data to back up its recommendation here.

It would be helpful to see some mention of the percentage of featured snippets linking to a featured snippet hub.

It would also be interesting to know the average number of featured snippets earned per featured snippet hub.


What SEMRush does provide are these statistics about featured snippet hubs:

  • 98% use HTTPS
  • Content length is upwards of 1,100 words or more
  • 66% use structured data
  • They contain an average of 14.5 heading tags
  • They have an average of 8 images (with ALT tags)

For more on any of the data points included in this article, see the full study here.


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Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate




A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.


The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users



1280x924 gmail

Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.


Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches




Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.


While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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