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Chatbots And AI Search Engines Converge: Key Strategies For SEO



Chatbots And AI Search Engines Converge: Key Strategies For SEO

A lot is happening in the world of search right now, and for many, keeping pace with these changes can be overwhelming.

The rise of chatbots and AI assistants – like ChatGPT and its new model GPT-4o, along with Google’s rollout of AI Overviews and Search Generative Experience (SGE) – is blurring the lines between chatbots and search engines.

New AI-first entrants, such as Perplexity and, also fragment the search space.

While this causes some confusion and necessitates that marketers pivot and optimize for multiple types of “engines,” it also presents a whole new array of opportunities for SEO pros to optimize for both traditional and AI-driven search engines in a new multisearch universe.

This evolution raises a broader question – perhaps for another day – about redefining what we call SEO to encompass terms like Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO).

Currently, every naming convention seems subject to change, which is something to consider as I write this article.

Either way, this evolution opens up tremendous opportunities for disruption in the overall search landscape.

What Is A Chatbot Or AI Assistant?

Screenshot from Wikipedia, May 2024

At the most basic level, chatbots use natural language processing (NLP) and large language models (LLMs) that are trained to extract data from online information, sources, and specific datasets. They then classify and fine-tune text and visual outputs based on a user’s prompt or question.

Chatbots are often used within specific applications or platforms, such as customer service websites, messaging apps, or ecommerce sites. They are designed to address specific queries or tasks within these defined contexts.

Right now, we see many crossovers between LLM-based chatbots and search engines. Rapid developments in these areas can cause confusion.

In this article, we’ll focus on the development of AI models in chatbots and their relation to search, with an inferred reference between chatbots and AI assistants.

The Evolution Of Chatbots And AI Models

Since ChatGPT emerged in November 2022, we’ve seen a significant boom in chatbots and AI assistants. Now, generative AI allows users to interact directly with AI and engage in human-like conversations to ask questions and complete various tasks.

For example, these AI tools can assist with SEO tasks, create content, compose emails, write essays, and even handle coding and programming tasks.

As they evolve, chatbots become multimodal (MMLLMs), improving capabilities beyond text to include images, audio, and more.

LLMs and LLMMsImage from 2024 AI Index Report from Stanford University, May 2024

For those interested in digging deeper into these models, the 2024 AI Index Report from Stanford University is a great resource for SEJ readers.

While many chatbots and AI models serve similar purposes, they also have distinct applications and use cases, such as content creation, image generation, and voice recognition.

Here are a few examples with some interesting differentiators and points:

  • ChatGPT: Conversational AI for research, ideation, text, image content, and more.
  • Google Gemini and Gemma: Uses Google’s LLM to connect and find sources within Google.
  • Microsoft Bing: Uses ChatGPT for conversational web search in Bing.
  • Anthropic Claude: Various AI models for content generation, images, and coding.
  • Stability AI: Suite of models and AI assistants for text, image, audio, and coding.
  • Meta Llama3: Utilizes Facebook’s social graph, its own Llama 3 model, and real-time data from Google.
  • Microsoft’s Copilot: AI assistant for business creativity and productivity apps.
  • Amazon LLM and Codewhisperer: Enhances customer and employer experiences.
  • Perplexity AI: Provides quick answers, sources of information, and citations.

Perplexity AI (which I will touch on later in this article) acts more like a search engine than many other chatbots and AI assistants.

Beyond their primary use cases, many companies are making their models available to a wider audience and broader ecosystems, allowing users to customize their own AI assistants.

For example, Amazon’s Bedrock enables AWS customers to use Anthropic and other LLMs, including Amazon’s own model, to create custom AI agents. Companies like Lonely Planet, Coda, and United Airlines are already using it.

On May 13, OpenAI launched its new flagship model, GPT-4. This model is a combination of AI technologies, bringing together what OpenAI calls “text, vision, and audio.” It also opens up access to its application programming interface (API), allowing developers to build their own applications.

All of this convergence has a lot of people wondering.

What’s The Difference Between Chatbots And Search Engines?

The first thing to note is that both chatbots and search engines are designed to provide information.

Search engines and some chatbot models share many similarities, which means their definitions can blur, and the relationships between them converge and collide.

However, at the moment (but it is changing), there is still a distinct difference between the two:

Search Engines

  • Search engines are better for exploring a wide range of topics.
  • They provide diverse perspectives from multiple sources.


  • Chatbots are better for quick answers, task completion, and personalized interactions.
  • They enhance the efficiency of the average searcher, making them much more effective at finding information.
Search engines vs chatbotsImage from author, May 2024

As more overlays and overlaps occur, the definitions of what constitutes a chatbot, an AI assistant, and a search engine may need to be redefined.

How Chatbots And Search Engines Work Together

Conversational search is a key area where search engines increasingly integrate chatbot features to provide a more interactive search experience.

You can ask questions in natural language, and the search engine may respond with direct answers or engage in a dialogue to refine your query.

Chatbots and AI assistants often utilize search engine technology to access information from the web, enhancing their ability to provide accurate and comprehensive answers.

This integration allows chatbots to go beyond their programmed knowledge base and tap into a broader range of information.

Here are a few examples:

  • Google: Integrates its own chatbot features into its search engine through SGE, providing direct answers and engaging in conversational search for some queries.
  • Bing: Incorporates a chatbot called “Bing Chat” that uses ChatGPT, conversational AI, and search technology to answer questions and provide information.
  • YouChat: A search engine that provides conversational responses to queries and allows for follow-up questions.
  • Meta: Utilizes its social graph and Google’s real-time data in its chatbot/AI assistant.
  • Perplexity AI: A chatbot that functions like a search engine, focusing on informational sources, sites, and citations.

These examples illustrate how the lines between chatbots and search engines are blurring. Thousands more instances show this convergence, highlighting the evolving landscape of digital search and AI.

How “Traditional” Search Engines Are Evolving As AI-First Entrants Arrive

The rise of generative AI and chatbots has caused significant upheaval in the traditional search space.

Traditional search engines are evolving into “answer engines.” This transformation is driven by the need to provide users with direct, conversational responses rather than just a list of links.

The line between chatbot engines and AI-led search engines is becoming increasingly blurred.

While AI in search is not a new concept, the introduction of generative AI and chatbots has necessitated a seismic shift in how search engines operate. For the first time, users can interact with AI in a conversational way, prompting giants like Google and Microsoft to adapt.

On May 14 at Google IO, Google announced the roll-out of AI Overviews as it integrates AI features into its search engine. It is also making upgrades to SGE.

The ultimate goal is to enhance its ability to provide direct answers and engage in conversational search. This evolution signifies Google’s commitment to maintaining its leadership in the search space by leveraging AI to meet user expectations.

In a recent interview on Wired Magazine titled It’s the End of Google Search As We Know It, Google Head of Search, Liz Reid, was clear that:

“AI Overviews like this won’t show up for every search result, even if the feature is now becoming more prevalent.”

As my co-founder, Jim Yu, states in the same article:

“The paradigm of search for the last 20 years has been that the search engine pulls a lot of information and gives you the links. Now the search engine does all the searches for you and summarizes the results and gives you a formative opinion.”

Beyond Google, we are seeing a rise in new, AI-driven search engines like Perplexity,, and Brave, which act more like traditional search engines by providing informational sources, sites, and citations.

These platforms leverage generative AI to deliver comprehensive answers and facilitate follow-up questions, challenging the dominance of established players.

Meta is also entering the fray by utilizing its social graph and real-time data from Google in its AI assistant, further contributing to the convergence of search and AI technologies.

At the same time, according to Digiday, TikTok is starting to reward what it calls “search value.”

Going forward, it’s important to remember that people have diverse needs, and we turn to different platforms for specific purposes.

Just as we go to Amazon for products, Yelp for restaurant suggestions, and YouTube for videos, the rise of AI will only amplify this trend. Each search engine will find its niche, leveraging its strengths to cater to particular user requirements.

ChatGPT is an intriguing case that stands out not for its research capabilities but for its prowess in content creation. While it excels in crafting high-quality content, its research functionalities fall short.

Effective research relies on real-time data, which platforms like ChatGPT currently lack. As we move forward, we expect to see search engines specialize even further, each excelling in specific areas based on its unique strengths and features.

What Does It All Mean For Marketers?

This fast-moving landscape and the convergence of search and AI presents both challenges and opportunities for marketers.

Optimizing for one engine is no longer sufficient; it’s essential to target multiple platforms – each with unique users, demographics, and intents.

Here’s how marketers can adapt and thrive in this dynamic environment.

Optimizing For Different Platforms


  • Strength: Dominates the traditional search space with a vast user base and comprehensive data sources.
  • Tip: Focus on core technical SEO, including schema markup and mobile optimization. Google’s Search Generative Experience means direct answers are becoming more prevalent, so structured data and high-quality content are vital.

Perplexity AI

  • Strength: Provides detailed citations and emphasizes source material, driving referral traffic back to original sites.
  • Tip: Ensure your content is authoritative and well-cited. Being a reliable source will increase the likelihood of your site being referenced, which can drive traffic and enhance brand trust.


  • Strength: Excels in conversational AI, making it suitable for quick answers and personalized interactions.
  • Tip: Create engaging, concise content that answers common questions directly. Utilize conversational language in your SEO strategy to match the style of ChatGPT interactions.

Key Strategies For Marketers

From optimizing technical SEO to harnessing the power of semantic understanding and creativity, these strategies provide a roadmap for success in the era of AI-driven search.

Core Technical SEO

Basics like site speed, mobile-friendliness, and proper schema markup remain crucial. Ensuring your site is technically sound helps all search engines index and rank your content effectively.

Semantic Understanding

Search engines and conversational AI are increasingly focused on semantic search. Optimize for natural language queries and long-tail keywords to match user intent more accurately.

Content And Creativity

High-quality, creative content is more important than ever. Unique, valuable content that engages users will stand out in both traditional and AI-driven search results.

Expanded Role Of SEO

SEO now encompasses content creation, branding, public relations, and AIO. Marketers who can adapt to these roles will be more successful in the evolving search landscape.

Be The Source That Gets Cited

Ensure your content is authoritative and well-researched. Being a primary source will increase the likelihood of citations that drive traffic and enhance credibility.

Get Predictive

Anticipate follow-up questions and provide comprehensive answers. This will not only improve user experience but also increase the chances of your content being highlighted in AI-driven search results.

Brand Authority

Focus on areas where your brand excels. AI search engines prioritize authoritative sources, so build and maintain your reputation in key areas to stay competitive.

The Best Content That Provides The Best Experience Wins

Ultimately, the quality of your content will determine your success. Invest in creating the best possible user experience, from engaging visuals to informative text.

Key Takeaways

Today, search encompasses a dual purpose: It can serve as a standalone assistant-based application or integrate into search engines for AI-led conversational experiences.

This fusion presents marketers with a unique opportunity to elevate their brands by creating accurate and authoritative content that positions them as trusted sources in their respective fields.

Ranking on the first page and being recognized as the go-to source cited by AI engines is no less important than 10 or 20 years ago but is exponentially more difficult.

The good news is that whether it’s Google’s AI engine or newcomers like Perplexity, brands that establish themselves as authorities in their niche stand to benefit immensely.

Marketers need to embrace creativity and collaboration across omnichannel teams. Ensure that your website is visible and accessible to all types of engines, whether traditional or AI-driven.

I’d like to leave you with a few questions to consider as you find your way forward in this complex environment. Pardon the pun, but no one has all the right answers yet.

  • Are chatbots morphing into search engines?
  • How do social platforms differentiate as younger generations look to them as search engines?
  • How would you define a search engine?
  • Who will win the race for user loyalty – traditional search engines infused with AI or new entrants built on generative AI from the beginning?
  • How would you redefine your role as an SEO – are you AI first?

While you consider that, stay proactive and adaptable and position yourself and your company to leverage the diversity and complexity of the search ecosystem to your advantage. In a world of ChatGPT, chatbots, and AI in search, you’re not optimizing for one channel, such as Google or Bing.

Successful optimization in this multifaceted landscape calls for a holistic approach. It’s not about keyword rankings or click-through rates; it’s about unraveling the intricacies of each platform and adjusting your strategies accordingly.

This means optimizing your content for conversational search, tapping into the capabilities of AI to tailor user experiences, and seamlessly integrating across different channels and devices.

Leverage the strengths of each platform to amplify your message by use case and engage with your audience on a deeper level, and you’ll ultimately drive more meaningful results for your business.

More resources: 

Featured Image: Memory Stockphoto/Shutterstock

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The 6 Biggest SEO Challenges You’ll Face in 2024



The 6 Biggest SEO Challenges You'll Face in 2024

Seen any stressed-out SEOs recently? If so, that’s because they’ve got their work cut out this year.

Between navigating Google’s never-ending algorithm updates, fighting off competitors, and getting buy-in for projects, there are many significant SEO challenges to consider.

So, which ones should you focus on? Here are the six biggest ones I think you should pay close attention to.

Make no mistake—Google’s algorithm updates can make or break your site.

Core updates, spam updates, helpful content updates—you name it, they can all impact your site’s performance.

As we can see below, the frequency of Google updates has increased in recent years, meaning that the likelihood of being impacted by a Google update has also increased.

How to deal with it:

Recovering from a Google update isn’t easy—and sometimes, websites that get hit by updates may never fully recover.

For the reasons outlined above, most businesses try to stay on the right side of Google and avoid incurring Google’s wrath.

SEOs do this by following Google’s Search Essentials, SEO best practices and avoiding risky black hat SEO tactics. But sadly, even if you think you’ve done this, there is no guarantee that you won’t get hit.

If you suspect a website has been impacted by a Google update, the fastest way to check is to plug the domain into Ahrefs’ Site Explorer.

Ahrefs Site Explorer screenshotAhrefs Site Explorer screenshot

Here’s an example of a website likely affected by Google’s August 2023 Core Update. The traffic drop started on the update’s start date.

Website impacted by Google's August 2023 Core UpdateWebsite impacted by Google's August 2023 Core Update
Hover over the G circles on the X axis to get information about each update.

From this screen, you can see if a drop in traffic correlates with a Google update. If there is a strong correlation, then that update may have hit the site. To remedy it, you will need to understand the update and take action accordingly.

Follow SEO best practices

It’s important your website follows SEO best practices so you can understand why it has been affected and determine what you need to do to fix things.

For example, you might have missed significant technical SEO issues impacting your website’s traffic. To rule this out, it’s worth using Site Audit to run a technical crawl of your website.

Site Audit screenshot, via Ahrefs Site AuditSite Audit screenshot, via Ahrefs Site Audit

Monitor the latest SEO news

In addition to following best practices, it’s a good idea to monitor the latest SEO news. You can do this through various social media channels like X or LinkedIn, but I find the two websites below to be some of the most reliable sources of SEO news.

Even if you escape Google’s updates unscathed, you’ve still got to deal with your competitors vying to steal your top-ranking keywords from right under your nose.

This may sound grim, but it’s a mistake to underestimate them. Most of the time, they’ll be trying to improve their website’s SEO just as much as you are.

And these days, your competitors will:

How to deal with it:

If you want to stay ahead of your competitors, you need to do these two things:

Spy on your competitors and monitor their strategy

Ok, so you don’t have to be James Bond, but by using a tool like Ahrefs Site Explorer and our Google Looker Studio Integration (GLS), you can extract valuable information and keep tabs on your competitors, giving you a competitive advantage in the SERPs.

Using a tool like Site Explorer, you can use the Organic Competitors report to understand the competitor landscape:

Organic competitors screenshot, via Ahrefs' Site ExplorerOrganic competitors screenshot, via Ahrefs' Site Explorer

You can check out their Organic traffic performance across the years:

Year on Year comparison of organic traffic, via Ahrefs' Site ExplorerYear on Year comparison of organic traffic, via Ahrefs' Site Explorer

You can use Calendar to see which days changes in Positions, Pages, Referring domains Backlinks occurred:

Screenshot of Ahrefs' Calendar, via Ahrefs' Site ExplorerScreenshot of Ahrefs' Calendar, via Ahrefs' Site Explorer

You can see their Top pages’ organic traffic and Organic keywords:

Top pages report, via Ahrefs' Site ExplorerTop pages report, via Ahrefs' Site Explorer

And much, much more.

If you want to monitor your most important competitors more closely, you can even create a dashboard using Ahrefs’ GLS integration.

Google Looker Studio integration screenshot,Google Looker Studio integration screenshot,

Acquire links and create content that your competitors can’t recreate easily

Once you’ve done enough spying, it’s time to take action.

Links and content are the bread and butter for many SEOs. But a lot of the time the links that are acquired and the content that is created just aren’t that great.

So, to stand the best chance of maintaining your rankings, you need to work on getting high-quality backlinks and producing high-quality content that your competitors can’t easily recreate.

It’s easy to say this, but what does it mean in practice?

The best way to create this type of content is to create deep content.

At Ahrefs, we do this by running surveys, getting quotes from industry experts, running data studies, creating unique illustrations or diagrams, and generally fine-tuning our content until it is the best it can be.

As if competing against your competitors wasn’t enough, you must also compete against Google for clicks.

As Google not-so-subtly transitions from a search engine to an answer engine, it’s becoming more common for it to supply the answer to search queries—rather than the search results themselves.

The result is that even the once top-performing organic search websites have a lower click-through rate (CTR) because they’re further down the page—or not on the first page.

Whether you like it or not, Google is reducing traffic to your website through two mechanisms:

  • AI overviews – Where Google generates an answer based on sources on the internet
  • Zero-click searches – Where Google shows the answer in the search results

With AI overviews, we can see that the traditional organic search results are not visible.

And with zero-click searches, Google supplies the answer directly in the SERP, so the user doesn’t have to click anything unless they want to know more.

Zero Click searches example, via Google.comZero Click searches example, via

These features have one thing in common: They are pushing the organic results further down the page.

With AI Overviews, even when links are included, Kevin Indig’s AI overviews traffic impact study suggests that AI overviews will reduce organic clicks.

In this example below, shared by Aleyda, we can see that even when you rank organically in the number one position, it doesn’t mean much if there are Ads and an AI overview with the UX with no links in the AI overview answer; it just perpetuates the zero-clicks model through the AI overview format.

How to deal with it:

You can’t control how Google changes the SERPs, but you can do two things:

Make your website the best it can be

If you focus on the latter, your website will naturally become more authoritative over time. This isn’t a guarantee that your website will be included in the AI overview, but it’s better than doing nothing.

Prevent Google from showing your website in an AI Overview

If you want to be excluded from Google’s AI Overviews, Google says you can add no snippet to prevent your content from appearing in AI Overviews.

nosnippet code explanation screemshot, via Google's documentationnosnippet code explanation screemshot, via Google's documentation

One of the reasons marketers gravitated towards Google in the early days was that it was relatively easy to set up a website and get traffic.

Recently, there have been a few high-profile examples of smaller websites that have been impacted by Google:

Apart from the algorithmic changes, I think there are two reasons for this:

  • Large authoritative websites with bigger budgets and SEO teams are more likely to rank well in today’s Google
  • User-generated content sites like Reddit and Quora have been given huge traffic boosts from Google, which has displaced smaller sites from the SERPs that used to rank for these types of keyword queries

Here’s Reddit’s traffic increase over the last year:

Reddit's organic traffic increase, via Ahrefs Site ExplorerReddit's organic traffic increase, via Ahrefs Site Explorer

And here’s Quora’s traffic increase:

Quora's organic traffic increase, via Ahrefs Site ExplorerQuora's organic traffic increase, via Ahrefs Site Explorer

How to deal with it:

There are three key ways I would deal with this issue in 2024:

Focus on targeting the right keywords using keyword research

Knowing which keywords to target is really important for smaller websites. Sadly, you can’t just write about a big term like “SEO” and expect to rank for it in Google.

Use a tool like Keywords Explorer to do a SERP analysis for each keyword you want to target. Use the effort-to-reward ratio to ensure you are picking the right keyword battles:

Effort to reward ratio illustrationEffort to reward ratio illustration

If you’re concerned about Reddit, Quora, or other UGC sites stealing your clicks, you can also use Keywords Explorer to target SERPs where these websites aren’t present.

To do this:

  • Enter your keyword in the search bar and head to the matching terms report
  • Click on the SERP features drop-down box
  • Select Not on SERP and select Discussions and forums
Example of removing big UGC sites from keyword searches using filters in Ahrefs' Keywords ExplorerExample of removing big UGC sites from keyword searches using filters in Ahrefs' Keywords Explorer

This method can help you find SERPs where these types of sites are not present.

Build more links to become more authoritative

Another approach you could take is to double down on the SEO basics and start building more high-quality backlinks.

Write deep content

Most SEOs are not churning out 500-word blog posts and hoping for the best; equally, the content they’re creating is often not deep or the best it can possibly be.

This is often due to time restraints, budget and inclination. But to be competitive in the AI era, deep content is exactly what you should be creating.

As your website grows, the challenge of maintaining the performance of your content portfolio gets increasingly more difficult.

And what may have been an “absolute banger” of an article in 2020 might not be such a great article now—so you’ll need to update it to keep the clicks rolling in.

So how can you ensure that your content is the best it can be?

How to deal with it:

Here’s the process I use:

Steal this content updating framework

And here’s a practical example of this in action:

Use Page Inspect with Overview to identify pages that need updating

Here’s an example of an older article Michal Pecánek wrote that I recently updated. Using Page Inspect, we can pinpoint the exact date of the update was on May 10, 2024, with no other major in the last year.

Ahrefs Page Inspect screenshot, via Ahrefs' Site ExplorerAhrefs Page Inspect screenshot, via Ahrefs' Site Explorer

According to Ahrefs, this update almost doubled the page’s organic traffic, underlining the value of updating old content. Before the update, the content had reached its lowest performance ever.

Example of a content update and the impact on organic traffic, via Ahrefs' Site ExplorerExample of a content update and the impact on organic traffic, via Ahrefs' Site Explorer

So, what changed to casually double the traffic? Clicking on Page Inspect gives us our answer.

Page Inspect detail screenshot, via Ahrefs' Site ExplorerPage Inspect detail screenshot, via Ahrefs' Site Explorer

I was focused on achieving three aims with this update:

  • Keeping Michal’s original framework for the post intact
  • Making the content as concise and readable as it can be
  • Refreshing the template (the main draw of the post) and explaining how to use the updated version in a beginner-friendly way to match the search intent

Getting buy-in for SEO projects has never been easy compared to other channels. Unfortunately, this meme perfectly describes my early days of agency life.

SEO meme, SEO vs PPC budgetsSEO meme, SEO vs PPC budgets

SEO is not an easy sell—either internally or externally to clients.

With companies hiring fewer SEO roles this year, the appetite for risk seems lower than in previous years.

SEO can also be slow to take impact, meaning getting buy-in for projects is harder than other channels.

How long does SEO take illustrationHow long does SEO take illustration

How to deal with it:

My colleague Despina Gavoyannis has written a fantastic article about how to get SEO buy-in, here is a summary of her top tips:

  • Find key influencers and decision-makers within the organization, starting with cross-functional teams before approaching executives. (And don’t forget the people who’ll actually implement your changes—developers.)
  • Adapt your language and communicate the benefits of SEO initiatives in terms that resonate with different stakeholders’ priorities.
  • Highlight the opportunity costs of not investing in SEO by showing the potential traffic and revenue being missed out on using metrics like Ahrefs’ traffic value.
  • Collaborate cross-functionally by showing how SEO can support other teams’ goals, e.g. helping the editorial team create content that ranks for commercial queries.

And perhaps most important of all: build better business cases and SEO opportunity forecasts.

If you just want to show the short-term trend for a keyword, you can use Keywords Explorer:

Forecasting feature for keywords, via Ahrefs' Keywords ExplorerForecasting feature for keywords, via Ahrefs' Keywords Explorer
The forecasted trend is shown in orange as a dotted line.

If you want to show the Traffic potential of a particular keyword, you can use our Traffic potential metric in SERP overview to gauge this:

Traffic potential example, via Ahrefs' Site ExplorerTraffic potential example, via Ahrefs' Site Explorer

And if you want to go the whole hog, you can create an SEO forecast. You can use a third-party tool to create a forecast, but I recommend you use Patrick Stox’s SEO forecasting guide.

Final thoughts

Of all the SEO challenges mentioned above, the one keeping SEOs awake at night is AI.

It’s swept through our industry like a hurricane, presenting SEOs with many new challenges. The SERPs are changing, competitors are using AI tools, and the bar for creating basic content has been lowered, all thanks to AI.

If you want to stay competitive, you need to arm yourself with the best SEO tools and search data on the market—and for me, that always starts with Ahrefs.

Got questions? Ping me on X.

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Why Now’s The Time To Adopt Schema Markup




Why Now's The Time To Adopt Schema Markup

There is no better time for organizations to prioritize Schema Markup.

Why is that so, you might ask?

First of all, Schema Markup (aka structured data) is not new.

Google has been awarding sites that implement structured data with rich results. If you haven’t taken advantage of rich results in search, it’s time to gain a higher click-through rate from these visual features in search.

Secondly, now that search is primarily driven by AI, helping search engines understand your content is more important than ever.

Schema Markup allows your organization to clearly articulate what your content means and how it relates to other things on your website.

The final reason to adopt Schema Markup is that, when done correctly, you can build a content knowledge graph, which is a critical enabler in the age of generative AI. Let’s dig in.

Schema Markup For Rich Results has been around since 2011. Back then, Google, Bing, Yahoo, and Yandex worked together to create the standardized vocabulary to enable website owners to translate their content to be understood by search engines.

Since then, Google has incentivized websites to implement Schema Markup by awarding rich results to websites with certain types of markup and eligible content.

Websites that achieve these rich results tend to see higher click-through rates from the search engine results page.

In fact, Schema Markup is one of the most well-documented SEO tactics that Google tells you to do. With so many things in SEO that are backward-engineered, this one is straightforward and highly recommended.

You might have delayed implementing Schema Markup due to the lack of applicable rich results for your website. That might have been true at one point, but I’ve been doing Schema Markup since 2013, and the number of rich results available is growing.

Even though Google deprecated how-to rich results and changed the eligibility of FAQ rich results in August 2023, it introduced six new rich results in the months following – the most new rich results introduced in a year!

These rich results include vehicle listing, course info, profile page, discussion forum, organization, vacation rental, and product variants.

There are now 35 rich results that you can use to stand out in search, and they apply to a wide range of industries such as healthcare, finance, and tech.

Here are some widely applicable rich results you should consider utilizing:

  • Breadcrumb.
  • Product.
  • Reviews.
  • JobPosting.
  • Video.
  • Profile Page.
  • Organization.

With so many opportunities to take control of how you appear in search, it’s surprising that more websites haven’t adopted it.

A statistic from Web Data Commons’ October 2023 Extractions Report showed that only 50% of pages had structured data.

Of the pages with JSON-LD markup, these were the top types of entities found.

  • (2,341,592,788 Entities)
  • (1,429,942,067 Entities)
  • (907,701,098 Entities)
  • (817,464,472 Entities)
  • (712,198,821 Entities)
  • (691,208,528 Entities)
  • (623,956,111 Entities)
  • (614,892,152 Entities)
  • (582,460,344 Entities)
  • (502,883,892 Entities)

(Source: October 2023 Web Data Commons Report)

Most of the types on the list are related to the rich results mentioned above.

For example, ListItem and BreadcrumbList are required for the Breadcrumb Rich Result, SearchAction is required for Sitelink Search Box, and Offer is required for the Product Rich Result.

This tells us that most websites are using Schema Markup for rich results.

Even though these types can help your site achieve rich results and stand out in search, they don’t necessarily tell search engines what each page is about in detail and help your site be more semantic.

Help AI Search Engines Understand Your Content

Have you ever seen your competitor’s sites using specific Types that are not found in Google’s structured data documentation (i.e. MedicalClinic, IndividualPhysician, Service, etc)?

The vocabulary has over 800 types and properties to help websites explain what the page is about. However, Google’s structured data features only require a small subset of these properties for websites to be eligible for a rich result.

Many websites that solely implement Schema Markup to get rich results tend to be less descriptive with their Schema Markup.

AI search engines now look at the meaning and intent behind your content to provide users with more relevant search results.

Therefore, organizations that want to stay ahead should use more specific types and leverage appropriate properties to help search engines better understand and contextualize their content. You can be descriptive with your content while still achieving rich results.

For example, each type (e.g. Article, Person, etc.) in the vocabulary has 40 or more properties to describe the entity.

The properties are there to help you fully describe what the page is about and how it relates to other things on your website and the web. In essence, it’s asking you to describe the entity or topic of the page semantically.

The word ‘semantic’ is about understanding the meaning of language.

Note that the word “understanding” is part of the definition. Funny enough, in October 2023, John Mueller at Google released a Search Update video. In this six-minute video, he leads with an update on Schema Markup.

For the first time, Mueller described Schema Markup as “a code you can add to your web pages, which search engines can use to better understand the content. ”

While Mueller has historically spoken a lot about Schema Markup, he typically talked about it in the context of rich result eligibility. So, why the change?

This shift in thinking about Schema Markup for enhanced search engine understanding makes sense. With AI’s growing role and influence in search, we need to make it easy for search engines to consume and understand the content.

Take Control Of AI By Shaping Your Data With Schema Markup

Now, if being understood and standing out in search is not a good enough reason to get started, then doing it to help your enterprise take control of your content and prepare it for artificial intelligence is.

In February 2024, Gartner published a report on “30 Emerging Technologies That Will Guide Your Business Decisions,”  highlighting generative AI and knowledge graphs as critical emerging technologies companies should invest in within the next 0-1 years.

Knowledge graphs are collections of relationships between entities defined using a standardized vocabulary that enables new knowledge to be gained by way of inferencing.

Good news! When you implement Schema Markup to define and connect the entities on your site, you are creating a content knowledge graph for your organization.

Thus, your organization gains a critical enabler for generative AI adoption while reaping its SEO benefits.

Learn more about building content knowledge graphs in my article, Extending Your Schema Markup From Rich Results to Knowledge Graphs.

We can also look at other experts in the knowledge graph field to understand the urgency of implementing Schema Markup.

In his LinkedIn post, Tony Seale, Knowledge Graph Architect at UBS in the UK, said,

“AI does not need to happen to you; organizations can shape AI by shaping their data.

It is a choice: We can allow all data to be absorbed into huge ‘data gravity wells’ or we can create a network of networks, each of us connecting and consolidating our data.”

The “networks of networks” Seale refers to is the concept of knowledge graphs – the same knowledge graph that can be built from your web data using semantic Schema Markup.”

The AI revolution has only just begun, and there is no better time than now to shape your data, starting with your web content through the implementation of Schema Markup.

Use Schema Markup As The Catalyst For AI

In today’s digital landscape, organizations must invest in new technology to keep pace with the evolution of AI and search.

Whether your goal is to stand out on the SERP or ensure your content is understood as intended by Google and other search engines, the time to implement Schema Markup is now.

With Schema Markup, SEO pros can become heroes, enabling generative AI adoption through content knowledge graphs while delivering tangible benefits, such as increased click-through rates and improved search visibility.

More resources: 

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Google Quietly Ends Covid-Era Rich Results




Google Quietly Ends Covid-Era Rich Results

Google removed the Covid-era structured data associated with the Home Activities rich results that allowed online events to be surfaced in search since August 2020, publishing a mention of the removal in the search documentation changelog.

Home Activities Rich Results

The structured data for the Home Activities rich results allowed providers of online livestreams, pre-recorded events and online events to be findable in Google Search.

The original documentation has been completely removed from the Google Search Central webpages and now redirects to a changelog notation that explains that the Home Activity rich results is no longer available for display.

The original purpose was to allow people to discover things to do from home while in quarantine, particularly online classes and events. Google’s rich results surfaced details of how to watch, description of the activities and registration information.

Providers of online events were required to use Event or Video structured data. Publishers and businesses who have this kind of structured data should be aware that this kind of rich result is no longer surfaced but it’s not necessary to remove the structured data if it’s a burden, it’s not going to hurt anything to publish structured data that isn’t used for rich results.

The changelog for Google’s official documentation explains:

“Removing home activity documentation
What: Removed documentation on home activity structured data.

Why: The home activity feature no longer appears in Google Search results.”

Read more about Google’s Home Activities rich results:

Google Announces Home Activities Rich Results

Read the Wayback Machine’s archive of Google’s original announcement from 2020:

Home activities

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