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How To Future-Proof Your Content From Google AI Core Updates

How To Future-Proof Your Content From Google AI Core Updates

It’s  the first-half of 2024 and the interaction between search engine algorithms and content creators has reached an unprecedented level of complexity. With the introduction of Google’s Core March Update, the dynamics of online visibility have undergone a significant transformation, presenting both challenges and opportunities for those engaged in the ever-evolving digital marketing scene.

At the core of this shift is a need to address a growing phenomenon: AI-generated content. As algorithms become more sophisticated and user expectations rise, there is a heightened urgency to navigate this terrain with precision. This is where E-E-A-T—Expertise, Experience, Authoritativeness, Trustworthiness—comes into play. E-E-A-T is a guiding principle introduced by Google to ensure that online content meets rigorous standards of credibility and reliability.

In this article, we embark on a journey to explore the implications of the Google Core March Update 2024 and to uncover strategies for content creators to not only adapt but thrive in this new sector. From understanding the intricacies of AI-generated content to strengthening your digital presence with E-E-A-T-aligned practices, we delve into the essential tactics for establishing visibility and authority in an era characterized by the fusion of technology and human expertise.

Table of contents:

  1. What is the Google March 2024 Update Really About
  2. Why AI-generated is a challenge that needs to be solved
  3. What sites have been impacted the most and how were they affected?
  4. What can I do to future-proof my content strategy in the era of spammy AI content?

What is the Google March 2024 Update Really About

The March 2024 core update is Google’s first core update of the year. Unlike previous core updates, this one brings enhancements to various aspects of Google’s core system. It’s a comprehensive update touching on multiple systems within the core, prompting Google to implement subsequent updates to these systems over the following period.

We were getting used to navigating through the effects of the Helpful and Core Updates separately, they’ve now been combined! This adds an extra layer of complexity to assessing any potential impacts and performing correlation analysis.

In plain language, it means that SEOs and webmasters like you and me won’t receive individual announcements for helpful content updates anymore; instead, they’ll be rolled into the core updates. 

According to Chris Nelson from Google’s Search Quality team, the March 2024 core update is more intricate than previous ones, involving changes across multiple core systems. Google has refined its core ranking systems to deliver more useful results, employing a range of innovative signals and methods. In essence, the prioritization of helpful content is now a central aspect of core updates.

Cyrus Shepard delved into the depths of 50 different websites and identified some intriguing correlations that shed light on crucial factors affecting site performance.

He discovered that sites burdened with excessive and intrusive ads, particularly sticky video ads, are more susceptible to falling victim to Google’s Helpful Content System. This finding reinforces what we’ve learned from industry experts like Google and Glenn Gabe: if you’ve been impacted, it’s high time to reposition your ad strategy.

Furthermore, adopting a first-person writing style could act as a defense against the impacts of the Helpful Content System, or assist in your recuperation if you’ve already been affected. Although not a direct indicator, it closely adheres to Google’s “first-hand experience” guidelines, highlighting a noteworthy correlation that requires careful consideration.

Why AI-Generated Is A Challenge That Needs To Be Solved

The entry barrier to becoming a copywriter or content writer has drastically decreased with the emergence of new AI models, assuming you’re proficient in utilizing these tools. While content production has become more affordable, we’re also witnessing a surge in the quantity of content being generated, much of which is unverified and consequently leads to a subpar user experience. Picture yourself seeking medical information or any YMYL (Your Money or Your Life) topic and stumbling upon a website where an inexperienced teenager offers an answer. Is this the direction we envisioned for search engines?

I’m uncertain if this aligns with the vision ChatGPT intended for search-related activities, but search engines like Google are undoubtedly grappling with the challenge of delivering excellent results for users. It appears that their fundamental quality model is being put to the test, inevitably affecting their business model. Poor quality Search Engine Results Pages (SERPs) not only hinder ad sales but also impede the development of engaging user experiences. This is detrimental for both Google and users like you and me.

What Sites Have Been Impacted The Most And How Were They Affected?

Accordingly, the sites that have been impacted the most by Google’s March 2024 Core Update are low-quality, AI-generated websites that manipulate search results. This update has led to the deindexing of numerous websites, resulting in significant losses in organic search traffic and advertising revenue for affected website owners. 

The deindexed sites showed signs of heavy reliance on AI-generated content, with some having up to 100% of their posts generated by AI. The impact of this update is substantial, with over 40% of SERPs being completely deindexed from Google’s search results in the early stages.

This is huge! I would not underestimate it if I were you, especially if your website business model is relying on advertising revenue.

What Can I Do To Future-Proof My Content Strategy In The Era Of Spammy AI-Content?

One effective approach is to prioritize ethical AI by embracing the creation of vetted, fact-checked content while leveraging tools like WordLift and ontology design for knowledge graphs.

First and foremost, investing in vetted and fact-checked content ensures that your audience receives accurate and trustworthy information. In the new era where misinformation proliferates, establishing your content as reliable and credible is essential for building trust with your audience. E-E-A-T is not easy to build but we’ve been there for multiple clients, learned first-hand and have the know-how on how to tackle this further.

Integrating WordLift into your content strategy offers numerous benefits. By enriching your content with structured data and semantic markup, WordLift helps search engines better understand the context and relevance of your content. This not only improves your content’s visibility in search results but also enhances its accessibility to users seeking credible information.

Additionally, WordLift’s ability to create a knowledge graph around your content fosters deeper connections between topics, providing a more comprehensive and engaging user experience.

Ontology design further strengthens your content strategy by organizing and structuring information in a meaningful way. By defining relationships between concepts and entities, ontology design ensures that your content is logically structured and easily navigable for both users and search engines. This not only improves user engagement but also reinforces your content’s authority and expertise in your niche. By prioritizing accuracy, relevance, and credibility, you can future-proof your content strategy and maintain a competitive edge in the digital sector.

Navigating the Future of AI Regulation: Insights from the WAICF 2024

Navigating the Future of AI Regulation: Insights from the WAICF 2024

Table of content:

The World AI Cannes Festival: Innovation, Strategic Partnerships and the Future of Humanity in the Age of AI

The World AI Cannes Festival (WAICF) stands as a premier event in Europe, attracting decision-makers, companies, and innovators at the forefront of developing groundbreaking AI strategies and applications. With an impressive attendance of 16,000 individuals, featuring 300 international speakers and 230 exhibitors, the festival transforms Cannes into the European hub of cutting-edge technologies, momentarily shifting focus from its renowned status as a global cinema stage.

This year marked WordLift’s inaugural participation in the festival, where we capitalised on the diverse opportunities the event offered. We were exposed to a myriad of disruptive applications such as the palm-based identity solution showcased by Amazon to streamlining payment and buying experience for consumers. Furthermore, we observed the emergence of strategic partnerships among key market players, exemplified by the collaboration between AMD and Hugging Face. As Julian Simon, Chief Evangelist of Hugging Face, aptly stated, “There is a de facto monopoly on computers today, and the market is hungry for supply.”

Engaging in thought-provoking discussions surrounding the future intersections of humanity and AI was a highlight of the event. One of the most captivating keynotes was delivered by Yann LeCun, the chief AI scientist of Meta and a pioneer in Deep Learning. LeCun discussed the limitations of Large Language Models (LLMs), emphasising that their training is predominantly based on language, which constitutes only a fraction of human knowledge derived mostly from experience. One of his slides provocatively titled “Auto-regressive LLMs suck” underscored his message that while machines will eventually surpass human intelligence, current models are far from achieving this feat. LeCun also shared insights into his latest work aimed at bridging this gap.

Navigating the Global Wave of AI Regulation

Allowing the more technically equipped participants to delve into discussions about the technical advancements showcased in Cannes, I will instead focus on a topic that, while less glamorous, holds great relevance: the anticipated impact of forthcoming AI regulation on innovation and players in the digital markets. This theme was prominent during the festival, with several talks dedicated to it, and many discussions touching upon related aspects of this trend.

Although in Europe the conversation predominantly revolves around the finalisation of the AI Act (with its final text expected in April 2024, following the EU Parliament’s vote), it’s essential to recognize that this is now a global trend. Pam Dixon, executive director of the World Privacy Forum, presented compelling data illustrating the exponential rise in governmental activities concerning AI regulation, highlighting the considerable variations in responses across jurisdictions. While some initially speculated that AI regulation might follow a path similar to GDPR, establishing a quasi-global standard in data protection to which most entities would adapt, it’s becoming evident that this won’t be the case. The OECD AI Observatory, for instance, is compiling a database of national AI policy strategies and initiatives, currently documenting over 1,000 policy initiatives from 70 countries worldwide.

One audience question particularly resonated with me: ‘If you are a small company operating in this evolving ecosystem, facing the challenges of this emerging regulatory landscape, where should you begin?’ To be honest, there’s no definitive answer to this question at the moment. Although the AI Act has yet to become EU law, and its effective enforcement timelines are relatively lengthy, WordLift, like many others in this industry, is already fielding numerous requests from customers seeking reassurance on our compliance strategies. Luckly, WordLift has been committed to fostering a responsible approach to innovation since its establishment.

Ethical AI and Compliance: WordLift’s Proactive Approach

For those working at the intersection of AI and search engine optimization (SEO), ethical AI practices are paramount concerns. WordLift has conscientiously crafted an approach to AI aimed at empowering content creators and marketers while upholding fundamental human values and rights. Previous contributions on this blog have covered various aspects of ethical AI, including legal considerations, content creation, and the use of AI in SEO for enterprise settings, explaining in details how WordLift translates the concept of trustworthy AI into company practices, ensuring that its AI-powered tools and services are ethical, fair, and aligned with the best interests of users and society at large. 

While the AI Act mandates that only high-risk AI system providers undertake an impact assessment to identify the risks associated with their initiatives and apply suitable risk management strategies, at WordLift we have proactively seized this opportunity to enhance communication with stakeholders, developing a framework articulating our company’s principles across four main pillars:

  1. Embracing a ‘Human-in-the-loop’ approach to combine AI-based automation with human oversight, in order to guarantee content excellence.
  2. Ensuring Data Protection & IP through robust processes safeguarding client data, maintaining confidentiality, and upholding intellectual property rights.
  3. Prioritising Security with a focus on safeguarding against potential vulnerabilities in our generative AI services architecture.
  4. Promoting Economic and Environmental Sustainability by committing to open-source technologies and employing small-scale AI models to minimise our environmental footprint.

We are currently in the process of documenting each pillar in terms of the specific choices and workflows adopted. 

Contextualising Corporate Strategies: Navigating Open Issues in AI Regulation within the Larger Landscape

However, it’s essential to contextualise SMEs and startups compliance policies in the bigger picture, where mergers and partnerships between major players providing critical upstream inputs (such as cloud infrastructure and foundation models) and leading AI startups have become a trend. 

This trend is exemplified by the recent investigation launched by the US Federal Trade Commission on generative AI partnership, and it usually suggests that the market for Foundation Models (FM) may be moving towards a certain degree of consolidation. This potential consolidation in the upstream markets could have negative implications for downstream markets where SMEs and startups operate. These downstream markets are mostly those in the red rectangle in the picture below, extracted from the UK CMA review of AI FM. Less competition in the upstream markets may lead to a decrease in the diversity of business models, and reduce both the degree of flexibility in using multiple FM and the accountability of FM providers for the outputs produced.

An overview of foundation model development, training and deployment

As highlighted by LeCun in his keynote, we need diverse AI systems for the same reason we need diverse press, and for this the role of Open Source is critical. 

In this respect, EU policymakers have landed, after heated debates, on a two tiers approach to regulation of FM. The first tier entails a set of  transparency obligations and a demonstration of compliance with copyright laws for all FM providers, with the exception of those used only in research or published under an open-source licence. 

The exception does not apply for the second tier, which covers instead models classified as having high impact (or carrying systemic risks, art 52a), a classification presumed on the amount of compute used for its training (expressed in floating-point operations, or FLOPs). According to the current text, today only models such as GPT-4 and Meta LLama-2 would find themselves falling into the second tier. While the tiering rationale has been criticised by part of the scientific community, the EU legislators seem to have accepted the proportional approach (distinctly treating different uses and development modalities) advocated by OS ecosystems and the compromise reached is viewed as promising by the OS community. 

The broad exemption of free and open-source AI models from the Act, along with the adoption of the proportionality principle for SMEs (art 60), appears to be a reasonable compromise at this stage. The latter principle stipulates that in cases involving modification or fine-tuning of a model, providers’ obligations should be limited to those specific changes. For instance, this could involve updating existing technical documentation to include information on modifications, including new training data sources. This approach could be successful in regulating potential risks associated with AI technology without stifling innovation.

However, as the saying goes, the devil is in the details. The practical implications for the entire AI ecosystem will only become apparent in the coming months or years, especially when the newly established AI Office, tasked with implementing many provisions of the AI Act, begins its work. Among its many responsibilities, the AI Office will also oversee the adjustment of the FLOPs threshold over time to reflect technological and industrial changes.

In the best case scenario, legislative clarity will be achieved in the next months through a flooding of recommendations, guidelines, implementing and delegated acts, codes of conduct (such as the voluntary codes of conduct introduced by art 69 for the application of specific requirements). However, there is concern about the burden this may place on SMEs and startups active in the lower portion of the CMA chart, inundated with paperwork and facing relatively high compliance costs to navigate the new landscape. 

The resources that companies like ours will need to allocate to stay abreast of enforcement may detract from other potential contributions to the framework governing AI technology development in the years ahead, such as participation in the standardisation development process. Lastly, a note on a broader yet relatively underdeveloped issue in the legislation: who within the supply chain will be held accountable for damages caused by high-risk AI products or systems? Legal clarity regarding liability is crucial for fostering productive conversations among stakeholders in the AI value chain, particularly between developers and deployers. 

Let’s hope that future iterations of the AI regulatory framework will effectively distribute responsibilities among them, ultimately leading to a fair allocation.

Questions to Guide the Reader

What is the significance of the World AI Cannes Festival (WAICF) for AI innovators and decision-makers?

The festival stands as a premier platform for the exhibition and discourse of AI advancements and strategies. Attending this event offers a unique opportunity to delve into cutting-edge applications, connect with key players across the AI value-chain, gain insights into their business strategies, and participate in high-level discussions exploring the evolving intersections of humanity and AI

How does the anticipated AI regulation in Europe impact innovation and the digital market landscape?

The latest version of the AI Act reflects over two years of negotiations involving political and business stakeholders in the field. The inclusion of broad exemptions for free and open-source AI models, coupled with the adoption of the proportionality principle for SMEs, presents a potential avenue for regulating AI technology’s risks without impeding innovation. However, the true impact will only become evident during implementation. Concerns arise regarding compliance costs, particularly for smaller entities, and the lack of legal clarity surrounding liability, which is vital for facilitating constructive dialogues among stakeholders in the AI value chain, particularly between developers and deployers.

What are WordLift’s strategies for aligning with ethical AI practices and upcoming regulations?

Since its inception, WordLift has adopted a proactive approach characterised by a commitment to ethical AI. Building upon this foundation, the company is now actively preparing for regulatory compliance by articulating a comprehensive framework based on four pillars.

How might the consolidation of the market for Foundation Models (FM) affect SMEs and startups in the AI sector?

As larger companies acquire dominance in the market for FMs, SMEs and startups may face greater hurdles in accessing these foundational technologies, potentially leading to increased dependency on them. This could pose a risk of stifling innovation over time. Regulators must closely monitor upstream markets to prevent a reduction in the diversity of business models, ensuring that smaller players retain flexibility in utilising multiple FMs and holding FM providers accountable for the outputs they generate.

WordLift Wraps Up 2023 With Multiple Recognitions

WordLift Wraps Up 2023 With Multiple Recognitions

WordLift completes 2023 with huge success and accolades from the Gartner Digital Markets brands – Capterra, Software Advice, and GetApp. Our products got recognized in various flagship reports under multiple software categories in 2023!

Capterra

“I like how easy it was to connect Google Sheets to your Google Search console and pull all the data into the sheet where it was easy to use. The confidence measure of which schema to add was also very useful”

[Source: Zunaid K.]

“WordLift has been an incredibly useful tool to manage our website’s SEO strategy. We appreciate the user-friendly interface which allowed us to quickly and efficiently optimize pages for search engine friendliness. The automated processes eliminated manual labor, saving us time and money. What truly impressed us is the personalized customer support we received from the WordLift team – they quickly responded with helpful advice and solutions whenever we had questions or issues.”

[Source: Sarfaraz K.]

Software Advice

“I like the opportunity to augment my website with additional data that help search engines understand my topics.”

[Source: Marco]

“I like support provided by the wordlift team to create adhoc customization”

[Source: Federico]

GetApp

“Implemented it on an article that wasn’t doing well for the target keyword, even though it was the only page targeting that exact term on the internet. So, as soon as I used WordLift to mention the entities that were in the exact term, the rankings started increasing, and the article went from 12th to 2nd position.”

[Source: Ishaan S.]

“This is one of the best SEO applications out there. I recommend this to all those who are looking for an excellent SEO application. Its AI system works amazingly with your marketing needs.”

[Source: Francis Rod D.]

Want to review WordLift ? Click here.

Our recognition in these prestigious reports is a significant achievement for us. It is a testament to our commitment to providing a high-quality solution that meets the needs of businesses across a wide range of industries. It also serves as a valuable endorsement for businesses looking for effective software solutions.

We have always strived to achieve higher customer satisfaction, which is why WordLift has been a top-rated product on all Gartner Digital Markets sites, with an overall rating of 4.8 out of 5. We would like to sincerely thank all our users for loving us so much and rating us so high.

About Gartner Digital Markets:

Gartner Digital Markets is a Gartner business unit composed of Capterra, GetApp, and Software Advice. It is the world’s premier source for software vendors to connect with in-market buyers, through research, reviews, and lead generation.

For more information, visit this page.

Entity Based SEO: How To Optimize Your Entity Vocabulary

Entity Based SEO: How To Optimize Your Entity Vocabulary

WordLift analyses your content and detects the words representing the main concepts, facts, persons, and places mentioned in the text. As a content creator or editor, you can identify the entities that better describe the essential meaning of your content between those words. With just one click, those entities will be translated into schema.org markup, and, at the same time, they will be saved into your internal vocabulary.

What is entity vocabulary?

In WordLift, a vocabulary is a repository of entities. Entities describe the ideas, concepts, places and people you talk about on your website. 

Entities help organize the content that you’re writing. As you annotate an article with an entity, WordLift creates a relationship between the article and entity so that a computer can better understand it.

Every time you annotate an entity, WordLift creates a context card that lets the reader know more about what we are talking about.

For example, as seen in the video below, if I marked the entity Schema.org in my article, WordLift will create a card that the user can click on to read more information about that entity. It is the same for all the entities to which I add the markup. This makes the content more complete and relevant and makes the reader spend more time on the website.

WordLift, by default, creates new pages in the form of this entity vocabulary. What to do with the new content. We highlight 4 different strategies in this article:

  • The Curated Vocabulary. Start adding the most relevant entities to your website, add a description, featured image and make them user friendly. It adds to your workload, but you can link those pages internally and let Google index them.
  • The Hidden Vocabulary. Use WordLift to markup each page and article on your site, but don’t link or index the vocabulary. You still benefit from entity-based SEO, but you have less pages and less content to worry about.
  • The Experimental Vocabulary. Use a hybrid approach to let your users roam free and access the entities while preventing Google from accessing it. Once you’re ready for prime time, you can easily switch from Experimental to Curated.
  • The Alternative Vocabulary. You curate your tags and categories, and we do the rest! You don’t need to spend time building your entity vocabulary because you already invested the time in creating great tags and categories.

Choice 1: The Curated Vocabulary

If you curate the entities in your vocabulary, you can expect some organic traffic to your vocabulary pages. In this case, you have to set the Vocabulary pages as indexed for Google’s crawlers and add a link to those entities from the articles and pages which mention them. 

What does it mean to curate your vocabulary entities?

Creating an entity in your vocabulary is simple and requires just a few essential steps

Go to Vocabulary, Add Entity, then add all the information about your entity. 

WordLift automatically suggests which other relevant topics to mark up (they are highlighted) within the text of your content to create links to other entities in your vocabulary.

Complete all the properties of the entity to increase the visibility of your content.

Then Publish, and if you go to the Vocabulary, you can see your entity. 

For example, this is the entity E-commerce SEO created with WordLift where we added Title, Description, sameAS, Excerpt, Entity Type, Image.

In addition, you can use widgets to enrich the page and make the content more attractive. We added like the Faceted Search that you can see below: 

Inserting the Faceted Search widget only takes 3 simple steps, as I show you in the image below: 

Choice 2: The Hidden Vocabulary

On the other hand, you might prefer to focus on your main pages and articles without devoting much time to the entities of your vocabulary. It means that your content will contain the markup, and Google and search engines will continue to understand your website content. Still, the user experience will not be affected by internal links nor Google will index your vocabulary pages. 

To do this, go to your Post, go to WordLift and add a markup to the relevant entities to your content. Then choose which entities you want to not link to and update. 

You can choose this solution not only if you don’t have time to take care of your vocabulary entities, but also for other reasons: 

  • You are using an entity that is the very basis of the topic you are exploring, and you assume your readers already know it enough. 
  • It would help if you had to markup semantically your article with many entities, but you are afraid that links could distract your readers.
  • You may have an SEO concern about the number of links on your page, and you don’t want to have too many links per article.

You can also globally decide to link or not to link entities in the WordLift Settings.

Go to WordLift settings, go to Link by Default. If you select YES, all entities in your vocabulary that you add with markup to your content will automatically be linked. If you choose NO, you will select which entities to link to and which not to.

Choice 3: The Experimental Vocabulary

In this case, you can start linking your content from your pages without allowing Google to index those pages. Search engine algorithms do not like useless web pages, that is, duplicate pages, off-topic pages, pages with poor content. Using this kind of vocabulary, you avoid showing Google and search engine pages that they might consider irrelevant and penalize your website’s SEO. 

To do this, go to the vocabulary, click the entity, click on Yoast SEO, go to Advanced and change the settings, not allowing search engines to show the page in search results, and update the entity. 

You can evaluate the results of the content you have chosen to index. Depending on the results you will get, you could decide to start further curating your entities. 

At any time, you can easily switch from Experimental to Curated Vocabulary. 

Choice 4: The Alternative Vocabulary

The fourth option is to augment your website through categories and tags. 

With WordLift 3.32 newly released feature, you don’t need to use the content classification pane of WordLift to add a markup, but you can use a tag or a category directly. It means that all your content with that specific tag is already connected to a tag with smart features, and it’s better recognizable for Google and Bing and other search engines.

In this way, a tag or a category is treated in the same way as an entity recognized in the content classification box. It makes everything easier because if you are already using tags and categories, you don’t need to do anything else that curate them. 

Save the tag with all its properties, and then go to the post. You don’t need to use the Content Classification box but add the tag and update. You can do the same with categories.

Tags and categories are treated in the same way as an entity recognized in the Content Classification box and used to build your Knowledge Graph, making your content intelligent and understandable to search engines. Your website will be automatically optimized for semantic SEO.

Watch the video to learn more👇

Are you ready for the new SEO?
Try WordLift now!

The Ultimate Checklist to Optimize Content for Google Discover

The Ultimate Checklist to Optimize Content for Google Discover

The shift from keyword search to a queryless way to get information has arrived.

Google Discover is an AI-driven content recommendation tool included in the Google Search app. Here is what we learned from the data available in the Google Search Console.

Google introduced Discover in 2017, and in September 2018 it claimed that there were already 800M active users consuming content using this new application. Back in April 2019, Google added in the Google Search Console statistical data on the traffic generated by Discover. This data is meant to help webmasters, and publishers in general, understand what content is ranking best on this new platform and how it might be different from the content ranking on Google Search.

Ready to get featured in Google Discover?
Start your free trial!

What was very shocking for me to see, on some of the large websites we work for with our SEO management service, is that between 25% and 42% of the total number of organic clicks are already generated by this new recommendation tool. I did expect Discover to drive a significant amount of organic traffic, but I totally underestimated its true potentials.

A snapshot from GSC on a news and media site

In Google’s AI-first approach, organic traffic is no longer solely dependent on queries typed by users in the search bar.

This shift has a tremendous impact on both content publishers, business owners, and the SEO industry as a whole.

Machine learning is working behind the scenes to harvest data about users’ behaviors, to learn from this data, and to suggest what is relevant for them at a specific point in time and space.

Let’s have a look at how Google explains how Discover works.

From www.blog.google

[…] We’ve taken our existing Knowledge Graph—which understands connections between people, places, things and facts about them—and added a new layer, called the Topic Layer, engineered to deeply understand a topic space and how interests can develop over time as familiarity and expertise grow. The Topic Layer is built by analyzing all the content that exists on the web for a given topic and develops hundreds and thousands of subtopics. For these subtopics, we can identify the most relevant articles and videos—the ones that have shown themselves to be evergreen and continually useful, as well as fresh content on the topic. We then look at patterns to understand how these subtopics relate to each other, so we can more intelligently surface the type of content you might want to explore next.

Embrace Semantics and publish data that can help machines be trained.

Once again, the data that we produce, sustains and nurtures this entire process. Here is an overview of the contextual data, besides the Knowledge Graph and the Topic Layer that Google uses to train the system:

To learn more about Google’s work on query prediction, I would suggest you read an article by Bill Slawski titled “How Google Might Predict Query Intent Using Contextual Histories“.

What I learned by analyzing the data in GSC

This research is limited to the data gathered from three websites only. While the sample was small, a few patterns emerged:

    1. Google tends to distribute content between Google Search and Google Discover (the highest overlap I found was 13.5% – these are pages that, since Discover data has been collected on GSC, have received traffic from both channels)
    2. Pages in Discover have not the highest engagement in terms of bounce rate or average time-on-page when compared to all other pages on a website. Yet, they are relevant for a specific intent and well-curated.
    3. Traffic seems to work with a 48-hours or 72-hours spike, as already seen for the top stories.

For news websites and, generally speaking, for websites with a high frequency of publishing, it makes sense to filter Google Analytics results to track Google Discover traffic in real-time. Follow Valentin Pletzer’s instructions to learn how to do it. It is not trivial and he has everything you need to get started.

To optimize your content for Google Discover, here is what you should do.

1. Make sure you have an entity in the Google Knowledge Graph or an account on Google My Business

Entities in the Google Knowledge Graph need to be created in order for Discover to be able to recognize them.

Results for WordLift
Results for WordLift

For business owners

Either your business or product is already in the Google Knowledge Graph, or it is not. If it is not, there are no chances that the content you are writing about for your company or product will appear in Discover (unless this content is bound to other broader topics). I can read articles about WordLift in my Discover stream since WordLift has an entity in the Google Knowledge Graph. From the configuration screenshot above, we can see there are indeed more entities when I search for “WordLift”:

    • one related to Google My Business (WordLift Software Company in Rome is the label we use on GMB),
    • one from the Google Knowledge Graph (WordLift Company)
    • one presumably about the product (without any tagline)
    • one about myself as CEO of the company

So, get into the graph and make sure to curate your presence on Google My Business. Very interestingly, we can see the relationship between myself and WordLift is such that when looking for WordLift, Google also shows Andrea Volpini as a potential topic of interest.

In these examples, we see that from Google Search I can start following persons that are already in the Google Knowledge Graph and the user experience in Discover for content related to the entity WordLift.
In these examples, we see that, from Google Search, I can start following persons already in the Google Knowledge Graph and Discover’s user experience for content related to the entity WordLift.

2. Focus on high-quality content and a great user experience

It is also good to remember that quality is essential, both in terms of the content you write (alignment with Google’s content quality policies) and user experience. A website that loads on a mobile connection in 10 seconds or more won’t be featured in Discover. A clickbait article — with more ads than content — won’t be featured in Discover. An article written by copying other websites and patently infringing copyright laws is not likely to be featured in Discover.

3. Be relevant and write content that truly helps people by responding to their specific information need

Recommendations tools like Discover only succeed when they can entice the user to click on the suggested content. To do so effectively, they need to work with content designed to answer a specific request. Let’s see a few examples “I am interested in SEO” (entity “Search Engine Optimization”), or “I want to learn more about business models” (entity “Business Model”).

The more we can match the user’s intent, in a specific context (or micro-moment if you like), the more likely we will be chosen by a recommendation tool like Discover.

4. Understand and enhance E-A-T signals

E-A-T (Expertise, Authoritativeness, and Trustworthiness) signals are used by Google to the ability of a given author, source, or page to provide authentic value to search engine users. To create content that can appear in Discover, it is essential to understand and improve these signals.

To do so, you need to secure your site by using HTTPS, optimize the author’s page by including dates, bylines, and any structured information about the author to provide reliability, trustworthiness, and transparency. If we look at the structured data for the entity associated with Doreid (using the validator of schema.org) we can see how we can help the search engine reconcile the information about a Person. This is one way to improve E-A-T signals. 

5. Always use an appealing hi-res image and a great title

Images play a very important role in Google’s card-based UI as well as in Discover. Whether you are presenting a cookie recipe or an article, the image you chose will be presented to the user, and it will play its role in enticing the click. Besides the images’ editorial quality, I suggest you follow the AMP requirements for images (the smallest side of the featured image should be at least 1.200 px).

You also want to make sure Google has the rights to display your high-quality images, and this can be done either using AMP or by filling out this form to express your interest in Google’s opt-in program. Similarly, a good title, much like in the traditional SERP, is super helpful in driving the clicks.

To learn more about Super-Resolution for images, I recommend you to read our article and try our AI-powered Image Upscaler. With it, you can enlarge and enhance images from your website to improve structured data markup by using a state-of-the-art deep learning model.

Find out more about SEO image optimization and make sure you see your content appear in Google Discover, see our latest web story?

Don’t underestimate the value of Open Graph metadata

Speaking about images, titles, and cards, also consider that the Open Graph metadata is now playing a role in Google Discover. Google might choose to show a piece of content using the og:title, og:image, and og:description tags for the preview card.

The funny thing is that this relation between Open Graph metadata and Google Discover has been found by mistake by Michal Pecánek and the Ahrefs team. They noticed that a typo present in the og:title (but not in the article’s actual title) was showcased to Google Discover users. Good catch!

Google Discover and the og:title tags
Here is the typo that suggested to Ahrefs’s team that Google Discover was using Open Graph metadata.

Open Graph Metadata are the same ones used by social media channels such as Facebook and LinkedIn to show the preview of a web page. So, knowing it or not, you might be using the Open Graph Protocol to polish the social media previews of your web pages, posts, and articles. Always be accurate in filling the editorial information for social media sharing as it might also be displayed on Google Discover.

6. Organize your content semantically

Much like Google does, using tools like WordLift, you can organize content with semantic networks and entitiesSemantic enrichment allows you to: a) help Google (and other search engines) gather more data about “your” entities b) organize your content the same way Google does (and therefore measure its performance by looking at topics and not pages and keywords) c) train our own ML models to help you make better decisions for your business.

Let me give you a few examples. I provide, let’s say, the information about our company and the industry we work for by using entities that Google can crawl. Google’s AI will be able to connect content related to our business with people interested in “startups”, “SEO” and “artificial intelligence”. As we usually say, machine learning is hungry for data, and semantically rich data is what platforms like Discover use to learn how to be relevant.

If I look at the traffic I generate on my website, not only in terms of pages and keywords but using entities (as we do with our new search rankings dashboard or the Google Analytics integration), I can quickly see what content is relevant for a given topic, and I can improve it. I can also decide to plan more editorial content about the most popular topics.

WordLift Dashboard
Use entities to analyze our your content is performing on organic search.

Here below is a list of pages, that we have annotated with the entity “Artificial Intelligence”. Are these pages relevant for someone interested in AI? Can we do a better job of helping these people learn more about this topic?

A detail of the WordLift dashboard
A few of the articles tagged with the entity “Artificial Intelligence” and their respective query

7. Experiment with Web Stories

A Web Story is a visual storytelling format that immerses the user in a tap-through full-screen experience. Web Stories can appear in Google Search, Google Images, in the Google app, and, also, in Google Discover.

As few publishers are using this format, it’s good to experiment with Web Stories to get a Google Discover spot. 

Web Stories include visual narratives, engaging animations, and tappable interactions. Therefore, you can use them to engage users on Google and then bring them to your website, inviting them to learn more.

Be careful here: Web Stories should not have more than one outlink or attachment per page.

To make your first Web Story eligible for display on Google, you need to build a Web Story with AMP and make sure you are following Google’s guidelines.

To help Google better understand your Web Story, you can add structured data to your Web Story. With structured data, Web Stories can also be eligible for other types of rich results (for example, the Top stories carousel or a host carousel).

8. Create a social engagement around your content

User engagement is one of the critical elements determining how successful a piece of content is in Google Discover and how long it will be exposed there. You can encourage engagement and interaction by sharing your content on social media, of course.

We have also seen that, by investing a few pounds in advertising on other social networks like Facebook, we can help Google rank the content on Discover.

Of course, the investment should be minimal and always proportioned to the amount of traffic that you expect to get on Discover for that type of content.

9. Extend the lifespan of your content

Usually, the life of a piece of content on Google Discover is as short as 48 hours. If you want to extend it, you can update the content by adding new information. We have experimented with both changing URLs and publishing dates. These are not recommended actions and go against Google’s guidelines, but it is worth knowing that at present, they do work for prolonging the lifespan of a content piece on Discover.

For this web story on automatically generated content in SEO, which now turns out to be the second longest-running on Google Discover for this blog, we had indexation issues in the beginning, we had updated the content (without changing nor the publishing date nor the URL) and apparently, it worked.

If you want to get similar data for your content in Google Discover, you can try the Google Discover Insights web app, that runs on Streamlit

10. Train the Knowledge Graph to explore the content, not just to search

Search is changing. Moving from push to pull, from information retrial to content recommendation, the search is becoming predictive and dialog-oriented, able to suggest to the user contents related to his topic of interest. 

As shown in the video below, I begin with a generic query such as “kalicube tuesday” and a panel helps me discover the upcoming event. This is Google MUM in action that helps me refine and discover something I don’t know exist. 

The Knowledge Graph and Google MUM are enabling these new interactions with the SERP. Adding structured data by building your KG means making your content understandable to Google and search engines in general. 

Training the Knowledge Graph helps Google provide meaningful recommendations to searchers across their entire journey.   

Learn more about Google Discover – Questions & Answers

In the next paragraphs of this article, you can find a list of questions that I have been able to answer as data from Discover was made available in GSC. I hope you’ll find it useful too.

How does Discover work from the end-user perspective?

The suggestions in Discover are entity-based. Google groups content that believes relevant using entities in its Knowledge Graph (i.e., “WordLift”, “Andrea Volpini”, “Business” or “Search Engine Optimization”). Entities are called topics. The content-based user filtering algorithm behind Discover can be configured from a menu in the application (“Customize Discover”) and fine-tuned over time by providing direct feedback on the recommended content in the form of “Yes, I want more of this”, “No, I am not interested”. Using Reinforcement Learning (a specific branch of Machine Learning) and Neural Matching (different ways of understanding what the content is about), the algorithm can create a personalized feed of information from the web. New topics can be followed by clicking on the “+” sign.

Topics are organized in a hierarchy of categories and subcategories (such as “Sport”, “Technology”). Read more here on how to customize Google Discover.

How can I access Discover?

On Android, in most devices, accessing Discover is as simple as swiping from the home screen to the right.

Is Google Discover available only in the US?

No, Google Discover is already available worldwide and in multiple languages, and it is part of the core search experience on all Android devices and on any iOS devices with the Google Search app installed. Discover is also available in Google Chrome.

Do I have to be on Google News to be featured in Discover?

No, Google Discover also uses content that is not published on Google News. It is more likely that a news site will appear on Google Discover due to the amount of content published every day and the different topics that a news site usually covers.

Is evergreen content eligible for Discover, or only freshly updated articles are?

Evergreen content that fits a specific information need is as vital as newsworthy content. I spotted an article from FourWeekMBA.com (Gennaro’s blog on business administration and management) that was published was first published in 2017 under the entity “business”.

FourWeekMBA on Discover

Does a page need to rank high on Google Search to be featured in Discover?

Quite interestingly, on a news website where I analyzed the GSC data, only 13.5% of the pages featured in Discover had received traffic on Google Search. Pages that received traffic on both channels had a position on Google Search <=8.

Correlation of Discover_Clicks, Google Search_Position
Correlation of Google Discover Clicks and Google Search Position

How can I measure the impact of Discover from Google Analytics?

A simple way is to download the .csv file containing all the pages listed in the Discover report in GSC and create an advanced filter in Google Analytics under Behaviour > Site Content > All pages with the following combination of parameters:

Filtering all pages that have received traffic from Discover in Google Analytics
Filtering all pages that have received traffic from Discover in Google Analytics

What is the difference between Google News and Google discover?

Google News is a news aggregator developed by Google to show users news and articles on the day’s main topic. Google Discover uses AI to offer users the information they want. It is made to “surface content relevant to you, even when you’re not looking.”

How is Discover different from Search?

Google search displays a result in response to a query (you are looking for information about a topic, product, or service; you go on Google and search for it). On the other hand, Discover brings up content based on your interests, and its feed changes regularly based on new web content posted or user interests that have changed. 

Discover is another crucial step in the evolution of search engines, where we go from push to pull, from information retrial to content recommendation, from query to dialogue. Check out our web story on Google Discover to learn more about this change and the new challenges it opens up.

Structured Data Testing Tool Bye Bye! Top 6 alternatives to validate your markup

Structured Data Testing Tool Bye Bye! Top 6 alternatives to validate your markup

Google’s decision to shut down the Structured Data Testing Tool to enhance Rich Results Test usage has raised an engaging debate in the world of SEO. Is this good news for experts around the world or it’s time to look for better alternatives? We might have the answer to this question.

On July 7, 2020, Google announced the upcoming shutdown of the Structured Data Testing Tool, an instrument widely used to date by SEO experts to verify the correct implementation of the structured data on a webpage. The decision is closely linked to the announcement of the release from the beta version of a new, more effective, testing tool, Rich Results Test. As Google explains:

“Rich results are experiences on Google Search that go beyond the standard blue link. They’re powered by structured data and can include carousels, images, or other non-textual elements. Over the last couple of years, we’ve developed the Rich Results Test to help you test your structured data and preview your rich results.”

To announce the transition from one tool to another, Google has also added a new message to the closing tool.

As you can read in the official documentation, the new tool brings more advantages to the analysis and more targeted advice on improving structured data, including:

  • Showing which Search feature enhancements are valid for the markup you are providing
  • Handling dynamically loaded structured data markup more effectively
  • Rendering both mobile and desktop versions of a result
  • It is fully aligned with Search Console reports

The tool can be used to test both code snippets and web page URLs and provides users with errors and warnings. The errors prevent a page from being displayed with the multimedia results in SERP, while the warnings indicate that one or more elements concerned will not be shown in the rich results. For example, as specified in the documentation, if there was a warning for a missing image property, that page could still appear as a rich result, just without an image.

The analysis of valid structured data on Rich Results Test
Here’s how the new tool highlights errors and helps you improve them

As announced by Google earlier this month, Rich Results Test is finally out of beta and fully supports all Google Search rich result features. The tool was born in 2017 as a solution to test rich snippets, rich cards, and all other multimedia search results. When it was launched, however, it only supported four types of structured data: recipes, job listings, films, and courses. It has now been updated and finally supports all types of structured data that can be seen in SERP on Google.

Rich Results Test: is it the best solution to test structured data? What are the limits of the tool?

Rich Results Test is ready to replace the old Structured Data Testing Tool. Is it good news? For now only in part, as the international SEO consultant Aleyda Solis points out in a tweet:

When Aleyda Solis wrote this feedback it was clear that Rich Results Test wouldn’t support all types of structured data, but only those that trigger Google Rich Results. Turns out she wasn’t the only one raising the issue and this week Google’s John Mueller said that the company heard the feedbacks and that “we are planning on expanding the Rich Results Testing Tool.”

As he explained, the original idea was to simplify the job for those who were only interested in the “types of structured data that actually have an effect in search. And that’s why we focus on the Rich Results Tool which focuses on the things that we would show as Google in the search results.” But SEO experts want it all. We’ll stay updated to learn more about future improvements to the new testing tools.

However, the launching of a new tool is always an exciting time to discover new features and understand how they can help us improve our content to win the front row seats on Google Search, especially if we are talking about Rich Results. But it also opens up an important question: what if there are other, better, tools out there? Let’s take off the tooth right away and find out the best alternatives outside the Googleplex.

Top Structured Data Testing Tools

First of all: do you really need to use a structured data testing tool? Absolutely yes. These testing tools are extremely useful as they give you a lot of important information on the deployment of the structured data in your web pages, providing insights about how the search engines read these data and if they are eligible for Rich Results. Of course, each testing tool is different and can help you improve your structured data through several features. Let’s take a look at the most interesting structured data testing tool out there.

SEO Site Checkup

Price: $39.95 with a 14-day free trial

SEO SiteCheckup is a website analysis tool that contains more than one tool, including the “dear old” Structured Data Testing Tool, in one-window service. All you need to do is paste the URL of the site and click Checkup to validate the structured data, check the schema usage, monitor your website SEO, and display any issues that need to be fixed such as page load speed, URL redirects, and mobile responsiveness.

Yandex Structured Data Validator

Price: Free

If you think you’ll miss the Structured Data Testing Tool, Yandex Structured Data Validator is a suitable alternative as is very similar to the Google tool. Along with check the markup on your site, this site helps you monitor how the structured data is processed and “seen” by search engines and whether the crawlers will be able to extract the information present in the structured data. 

RDF Translator

Price: Free

RDF Translator is a multi-format conversion tool for structured markup. The main value of this tool is that, unlike most other free tools out there, it supports data formats such as XML, N3, and N-Triples. Along with the use of RDF Translator to validate your structured data, you can also incorporate the tool on your website, as it comes with REST API for developers.

JSON-LD Playground

Price: Free

It comes by itself that JSON-LD Playground is the best tool for validating JSON-LD structured data format. The use is quite simple: you just have to enter the markup code with <script type=’application/ld+json‘> or the URL of the remote document and wait to get a detailed report.

Bing Markup Validator

Price: Free

Bing Markup Validator is a part of the Bing Webmaster Tools that also includes SEO Analyzer and Keyword Research Tool. This tool is particularly useful to verify your webpages markup and get an on-demand report that helps you validate different types of structured data such as HTML Microdata, RDFa, JSON-LD, OpenGraph, and Schema.org.

Structured Data Linter

Price: Free

Structured Data Linter is a pretty minimalistic tool that helps you verify the structured data present in your web pages by simply pasting the URL of a page or a code or by just uploading a file. It supports RDFa and JSON-LD but at the moment does not support microformats.

We’ve seen the best alternative to Google’s Rich Results Testing Tool, but what about data quality monitoring?

Ok, at this point you have an overview of the new Rich Results Tool and of the most suitable alternatives out there that will help you check the markup in your web pages. But is that the best you can get? Our answer is simply: no.

As avid structured data users ourselves, having developed a powerful AI SEO tool that relies on data quality in order to enhance the content of a website and make sure that connects in the right way with search engines, we decided to build our own testing and monitoring tool.

Yes, you heard right! We think to know exactly what you need not only to validate structured data and find any error but also to do it in a smart, time-saving way. How? Take a look at the most relevant features of our tool:

  1. UPTIME. Test your structured data availability automatically worldwide
  2. VALIDATION. Ensure that data is always valid. We alert when something breaks, or if Google’s rules have changed
  3. ALERTING. Get alerted by WordLift when errors or warnings are found
  4. GUIDES. Learn how to improve your website rich result’s performance

Testing is crucial, but what about monitoring? Our new WordLift tool not only gives you an exhaustive report to constantly keep control of your quality data but also alerts you when you need to intervene, making your job easy and your markup secure.  

Uh, didn’t I tell you? You can also take advantage of our dedicated technical support!

Optimizing SEO with AI Agent Top SEO trends for 2023 BLOOM for SEO Prompt engineering in SEO FAQ Schema Markup