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AI Re-Ranking For Semantic Search

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AI Re-Ranking For Semantic Search

Search isn’t just about matching keywords – and that’s even more true when we talk about semantic search.

Semantic search is about finding the right information for the searcher at the right time.

That goes beyond finding the right keywords and concepts and speculating how searchers will interact with the results.

Artificial intelligence (AI) re-ranking will take information about the people who come to search and tailor search results to the individual.

That might be done on a cohort level, changing results based on trends, seasonality, and popularity.

It might also be done individually, changing results based on the current searcher’s desires.

While AI re-ranking is not easy to implement in a search engine, it brings outsized value for conversions and searcher satisfaction.

Re-Ranking With Artificial Intelligence

AI-driven re-ranking can improve search results, no matter the underlying ranking algorithm a search engine uses.

That’s because good search results are more than textual relevance and business metrics like raw popularity.

Good results take into account other signals and do so on a per-query level.

To see why this is important, let’s focus on the business metric of popularity.

It’s a good general ranking signal but can fall short for specific queries. A search query of “red dress” might bring up in the first results two different dresses: “backless dress with red accents” and “summer dress in bright red.”

The backless dress might be more popular as an overall dress and product.

But in this case, specifically, it’s not what customers want.

They want a red dress, not one with red accents, and they click and buy accordingly.

Shouldn’t the search engine take that as a signal to rank the summer dress higher?

Search Analytics

As the above example shows: Understanding what searchers are doing is necessary for re-ranking.

The two most common events to track are clicks and conversions.

Generally, those are the only two events necessary and must be events coming from search.

The example above also highlights another important consideration: the events should be tied to specific queries.

That allows the search engine to learn from the interplay between the different result sets and user interactions. It propels the summer dress higher in the search results for the “red dress” query.

The same product might be less popular for other queries than its neighbors.

When looking at your different events, you’ll want to weigh them differently, too.

Clicking on a result is a sign of interest while making a purchase (or any other conversion metric) is a sign of commitment.

The ranking should reflect that.

The weighting doesn’t need to be complex.

You can go as simple as saying that conversions are worth double clicks.

You should test the right ratio for your own search.

You may also want to discount events based on the result ranking at the time the searcher saw it.

We know that a result’s position influences its clickthrough rate (CTR).

Without discounting events, you may have a situation where the top results become even more entrenched because they get more interactions, which keep them ranked higher – and repeating infinitely.

Freshness And Seasonality

A simple way to combat this self-reinforcing loop is by discounting events based on the time passed since the event.

That happens because each event that occurred in the past has an increasingly small impact on re-ranking. That is, until, at some point, it has no impact at all.

For example, you might divide the impact of each event by two, each day, for 30 days. And after 30 days, stop using the event for ranking.

A nice benefit of using freshness in the re-ranking algorithm is that it also introduces seasonality into the results.

Not only do you stop recommending videos that were extremely popular years ago but are boring to people today; you also will recommend “learn how to swim” videos in the summer, and “learn to ski” videos in the winter.

YouTube has seasonality and freshness built into its algorithm precisely for this purpose.

Using Signals To Re-rank

Now that you’ve got the signals and decaying them over time, you can apply them to the search results.

When we see “artificial intelligence,” we often think of something incredibly complex and inscrutable.

AI, though, can also be as simple as taking data over time and using it to make decisions, like we’re doing here.

One easy approach is to take a certain number of results and simply re-rank them based on a score.

For performance reasons, this number of results will generally be fairly small (10, maybe 20). Then, rank them by score.

As we discussed above, the score could be as simple as adding up the number of conversions times two, plus the number of clicks.

Adding a decay function makes for more complexity, as does discounting based on result position – but the same general principle applies.

Learning To Rank

A drawback of this re-ranking system is that you are limited to re-ranking a smaller number of results.

If you have a result that would otherwise be popular but isn’t ranking high, that result won’t get the attention it warrants.

This system also requires events on the records and the queries you want to re-rank.

It won’t work for brand new product launches or user-generated content (UGC) that often comes in and out of the search index.

Learning to rank (LTR) can address these issues.

Much like the re-ranking we’ve discussed above, LTR also works based on the idea that the records searchers interact with are better than the ones they don’t.

The previous re-ranking method works by boosting or burying results directly when tied to a specific query.

Meanwhile, LTR is much more flexible. It works by boosting or burying results based on other popular results.

LTR uses machine learning to understand which queries are similar (e.g., “video games” and “gaming console”).

It can then re-rank results on the less popular queries based on interactions on the more common ones.

LTR doesn’t only generalize on queries; it generalizes on records, too.

The LTR model learns that a certain type of result is popular; for example, the Nintendo Switch game “Legend of Zelda: Breath of the Wild.”

Then, it can start to connect to other similar results (for example, “Legend of Zelda: Skyward Sword”) and boost those.

Why, then, not just use LTR if it appears to be much more powerful than your typical re-ranking and provides more query and record coverage?

(In other words: It generalizes better.)

In short, LTR is much more complex and needs more specialized in-house machine learning (ML) expertise.

Additionally, understanding why certain results are ranked in certain places is more difficult.

With the first type of re-ranking, you could look at the number of clicks and conversions over time for one record compared to another.

Meanwhile, with LTR, you have an ML model that makes connections that may not always be obvious.

(Are “Breath of the Wild” and “Sonic Colors” really all that similar?)

Personalization

While re-ranking works across all searchers, personalization is what it sounds like: personal.

The goal of personalization is to take results that are already relevant and re-rank them based on personal tastes.

While there is a debate on how much web search engines like Google use personalization in their results, personalization often impacts the performance of results in on-site search engines.

It is a useful mechanism for increasing search interactions and conversions from search.

Search Analytics

Just as with re-ranking, personalization depends on understanding how users interact with search results.

By tracking clicks and conversions, you’ll have a clearer idea of the kinds of results that the user wants to see.

One significant difference between re-ranking and personalization on this front is that, depending on your search, you might want to adjust how you apply personalization.

For example, if you sell groceries, you definitely want to recommend previously purchased products.

But if your website sells books, you won’t want to recommend a book that a customer has already bought. Indeed, you may even want to move those books down in the search results.

It’s also true, however, that you shouldn’t push personalization so hard that users only see what they’ve interacted with before.

Search empowers both finding and discovery. So, if they return to the search bar, you should be open to the possibility that they want to see something new.

Don’t rank results exclusively via personalization; make it a mix with other ranking signals.

Just as with re-ranking, personalization also benefits from event decay.

Decreasing the impact of older events makes a search more accurately represent a user’s current tastes.

In a way, you can think of it as personal seasonality.

Personalization Across Users

The kind of personalization we’ve seen so far is based on an individual’s own interactions, but you can also combine it with what others are doing inside search.

This approach shows an outsized impact on situations where the user hasn’t interacted with the items in the search results before.

Because the user doesn’t interact with the search result items, you can’t boost or bury based on past interactions, by definition.

Instead, you can look at users that are similar to the current user and then personalize based on what they have interacted with.

For example, say you have a user who has never come to you for dresses but has purchased many handbags.

Then, you can look for other users who have similar tastes and have also interacted with dresses.

Intuitively, other customers who like the same type of handbags as our searcher should also like the same dresses.

Re-Ranking And Personalization For Discovery

Search is only one example of where re-ranking and personalization can make an impact. You can use these same tools for discovery as well.

The secret is to think of your home page and category pages as search results.

Then, it’s clear that you can use the same tools you use for search and gain the same benefits.

For example, a home page is similar to a search page without a query, isn’t it? And a category landing page sure does look like a search page with a category filter applied to it.

If you add personalization and re-ranking to these pages, they can be less static. They will serve users what they prefer to see, and they can push items higher that are more popular with customers overall.

And don’t worry, personalization and re-ranking can mix with editorial decisions on these pages or inside search.

The best way to handle this is by fixing the desired results in certain places and re-rank around them.

We’ve seen that personalization and re-ranking are two approaches that take user interactions with relevant signals to make search better.

You can let your user base influence the result by using the interactions.

Little by little, these interactions tell the search engine what items should be ranking higher.

Ultimately, searchers benefit from a better search experience, and you benefit from more clicks and conversions.

More resources:


Featured Image: amasterphotographer/Shutterstock



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The 6 Biggest SEO Challenges You’ll Face in 2024

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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 Google.com

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

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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

Schema.org has been around since 2011. Back then, Google, Bing, Yahoo, and Yandex worked together to create the standardized Schema.org 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.

  • http://schema.org/ListItem (2,341,592,788 Entities)
  • http://schema.org/ImageObject (1,429,942,067 Entities)
  • http://schema.org/Organization (907,701,098 Entities)
  • http://schema.org/BreadcrumbList (817,464,472 Entities)
  • http://schema.org/WebSite (712,198,821 Entities)
  • http://schema.org/WebPage (691,208,528 Entities)
  • http://schema.org/Offer (623,956,111 Entities)
  • http://schema.org/SearchAction (614,892,152 Entities)
  • http://schema.org/Person (582,460,344 Entities)
  • http://schema.org/EntryPoint (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 Schema.org 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 Schema.org Types that are not found in Google’s structured data documentation (i.e. MedicalClinic, IndividualPhysician, Service, etc)?

The Schema.org 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 Schema.org 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 Schema.org 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.

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Google Quietly Ends Covid-Era Rich Results

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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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