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Google Doesn’t Care What’s In An Image

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Google’s web search algorithm doesn’t care what’s in an image. All that matters is it’s marked up with the correct structured data.

Whether it’s an award-winning photograph, or a blank square, it’s all the same in terms of the SEO value it adds to the page.

This is discussed during the Search Central SEO hangout with Google’s John Mueller recorded on October 22.

A site owner named Andrew Sychev joins the Q&A to ask Mueller about using placeholder images in conjunction with lazy loading.

Sychev has his site set up to load images further down a page as grey squares until a visitor starts scrolling.

When a visitor gets closer to where the image is located on the page, the grey square is replaced with an actual photo.

This is done to improve page speed and to prevent a page from shifting around in a visitor’s browser, which may happen when a bunch of images are loaded all at once.

Since Googlebot doesn’t interact with web pages, and therefore won’t see the images, Sychev asks if there’s any harm in using this set up.

While this question relates to using lazy loading as a way of improving cumulative layout shift (CLS), the answer given by Mueller applies to SEO in general.

Would using your own photos add more SEO value to a page than using generic stock images?

Can Google recognize when an image contains useful data, such as a chart or an infographic?

These are all questions that come up around images and web search— and here’s the answer.

Google’s John Mueller On Images & Web Search

As it relates specifically to web search, not image search, Google doesn’t care what’s in your photos.

Google’s only concerned about signals such as structured data and alt text.

That’s what’s important to web search as it can help Google understand the page better.

“I don’t think we care, to be quite honest. I don’t think for web search we look at the specific images on the page and say oh this is a nice image and this is a boring image.

We basically use those images in image search and that’s where we care what the content of the images care. But within web search we don’t really care if it’s a gray square or if it’s a picture of a beach.”

To answer the original question, substituting images for grey squares in a lazy loading setup would be perfectly fine.

Mueller reiterates that structured data communicates all the information Google needs.

“It sounds okay. I think for the core web vital side, the CLS side, that’s something you can test where you try it in one way or the other way. With regards to indexing what is important is that we have information about the images on those pages.

So what you can do if you’re not sure if your lazy loading is recognized by Google is use the image structured data. On the pages themselves, give us the structured data for those images and then we can definitely pick that up.”

Keep in mind this information is applicable to Google’s web search algorithm only. What’s in an image does matter to the Google Images algorithm.

More important than that— it matters to visitors.

While Google may not care about the work you put into crafting the perfect graphic for a piece of content, your visitors will.

Images can impact how a person feels after consuming a piece of content. If the images made a difference to how much they enjoyed it, then they’re probably going to come back.

Hear Mueller’s full response in the video below.


Featured Image: Beach Creatives/Shutterstock

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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

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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

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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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Google Brings Bard Students Math and Coding Education in the Summer

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Google Brings Bard Students Math and Coding Education in the Summer

Google is stepping up its AI efforts this summer by sending Bard, its high-profile chatbot, to summer school. The aim? To boost the bot’s math and coding smarts. These developments are excellent news— when Bard first debuted, it was admittedly not a finished product. But Google is steadily plugging away at it, and have now implemented implicit code execution for logical prompts, and handy Google Sheets’ integration to take it to the next level.

Thanks to implicit code execution, Bard can respond to inquiries requiring calculation or computation with Python code snippets running in the background. What’s even more amazing is that coders can take this generated code and modify it for their projects. Though Google is still apprehensive about guaranteeing the accuracy of Bard’s answers, this feature is said to improve the accuracy of math and word problems by an impressive 30%.

In addition to this, Bard can now export directly to Sheets when asked about tables. So, you don’t need to worry about copying and pasting, which comes with the risk of losing formatting or data.

From the company’s I/O keynote address, it is clear that they are focused on making the most of what Bard can offer. As they continue to speak highly of the chatbot, we’re sure to expect more features and capabilities when the summer comes around.

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