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7 Insights Into How Google Ranks Websites via @sejournal, @martinibuster

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Google’s algorithm is built around understanding content and search queries and making the answers accessible to users in the most convenient manner.

These seven insights show how to develop a winning SEO and content strategy by leveraging what we know about Google’s algorithms.

The following are insights developed by studying patents and research papers published by Google itself.

Insight 1: Follow the Correct Intent

There are some content writing systems that mine the top-ranked websites and provide content writing and keyword suggestions based on the analysis of the top ten to top thirty webpages.

Some people who have used the software have told me that the information isn’t always helpful. And that’s not surprising because mining all of the top-ranked webpages in any given search results page (SERP) is going to result in a noisy data set that’s inaccurate and is of limited usefulness.

One of the issues with identifying user intent is that almost every query contains multiple user intents.

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Google solves this problem by showing links to webpages about the most popular user intents first.

For example, in a research study about automatically classifying YouTube channels (PDF), the researchers discuss the role of user intent in determining which results to show first.

In the below quote, where it uses the word “entity,” it’s a reference to what you normally think of as a noun (a person, a place, or a thing):

“A mapping from names to entities has been built by analyzing Google Search logs, and, in particular, by analyzing the web queries people are using to get to the Wikipedia article for a given entity…

For instance, this table maps the name Jaguar to the entity Jaguar car with a probability of around 45 % and to the entity Jaguar animal with a probability of around 35%.”

In plain English, that means researchers discovered that 45% of people who search for Jaguar are looking for information about the automobile and 35% are looking for information about the animal.

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That’s user intent that is segmented by popularity.

The takeaway here is that if your content is about selling a product and the top-ranked pages are about how to make that product then it may be possible that the popular user intent for that keyword is how to make that product and not where to buy that product.

That insight may mean that new content is needed to target the underlying “how to make” latent question that is inherent in that search query.

Insight 2: Link Ecosystem Has Changed

Blogging was at an all-time high twelve years ago. Many people were going online to churn out content and link out to interesting websites.

Aside from the recipe niche, that is no longer the case and that may be affecting the link signal that Google uses for ranking purposes. This is super important to think about.

Fewer People Searching for WordPress

There are fewer and fewer people searching for WordPress every year. This indicates that WordPress is declining in popularity in the general population.

The search volume for the keyword “WordPress” has declined by 71% since September 2011.

WordPress popularity is declining.Screenshot from Google Trends, September 2021WordPress popularity is declining.

Fewer People Searching for Blogs

It’s not just WordPress usage that is going down. There are also fewer people searching for blogs, with a pattern that mirrors the decline in searches for WordPress.

Screenshot of Google Trends showing decline in blogging popularity.Screenshot from Google Trends, September 2021Screenshot of Google Trends showing decline in blogging popularity.

The Link Ecosystem in Decline

There may be many reasons why blogging has declined in popularity.

It could be social media or it could be the introduction of the iPhone and Android changed how the public interacts online.

Screenshot of Google Trends showing ascendant popularity of Instagram.Screenshot from Google Trends, September 2021Screenshot of Google Trends showing ascendant popularity of Instagram.

The Link Ecosystem Has Declined

One thing that is indisputable is that fewer people are blogging and the link ecosystem has suffered a strong decline. What caused it is beside the point.

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Gary Illyes of Google confirmed that the motivation for turning the nofollow link attribute directive into a hint was so that Google can use those links for ranking purposes.

“Yes. They had been missing important data that links had, due to nofollow. They can provide better search results now that they consider rel=nofollowed links into consideration.”

It’s not unreasonable to consider the use of nofollow links for ranking purposes was done because there are fewer natural links being generated.

With fewer links being naturally generated, it is highly likely that it’s going to affect how websites are ranked and that Google would be increasingly selective about the links it uses.

Today, it is increasingly clear that link strategies that rely on blog links are more easily detected as spam since fewer people are creating blogs.

The takeaway here is that when creating a link building strategy, it’s important to be aware that the link ecosystem is in decline.

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That means that freely given natural links are also in decline.

Link strategies must be more creative in terms of identifying who is left linking to websites and understanding why they are linking to websites.

Takeaway About Links

The time for being selective about getting links from so-called “authority” sites is long past.

Get what you can get as long as it is natural and freely given by any relevant website.

Insight 3: Link Drought Link Building Strategy

Because there are fewer natural links being freely given it’s time to rethink the race to obtain the right anchor text and massive amounts of links.

While a freely given link with a relevant anchor text is useful it’s rarely going to happen naturally.

So maybe it’s time to move away from old traditional link building focused on anchor text and guest posting (which today means paid links).

Instead, it may be useful to cultivate links from news and magazines, relevant organizations, and some educational organizations.

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Now more than ever it’s time to focus on outreach regardless of whether the outreach results in links. Just take the traffic.

Insight 4: Search Results Show What People Want to See

Ever walk down a supermarket cereal aisle and note how many sugar-laden kinds of cereal line the shelves? That’s user satisfaction in action. People expect to see sugar bomb cereals in their cereal aisle and supermarkets satisfy that user intent.

I often look at the Fruit Loops on the cereal aisle and think, “Who eats that stuff?” Apparently, a lot of people do, that’s why the box is on the supermarket shelf – because people expect to see it there.

Google is doing the same thing as the supermarket. Google is showing the results that are most likely to satisfy users, just like that cereal aisle.

Sometimes, that means showing newbie 101 level answers. Sometimes that means showing something incredibly racist and sad.

For example, in 2009, Google had to apologize for showing an image of Michelle Obama that was altered to resemble a monkey every time someone searched on her name.

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Why did Google show that result? Because most people searching on the name Michelle Obama were the kind of people who were satisfied seeing an image of her that resembled a monkey.

Click-through rates and other metrics of user satisfaction indicated that’s what people wanted to see. So Google’s user intent algorithm gave it to them.

Remember those sugar-laden cereals in the supermarket? That’s what those kinds of results are. It’s what I refer to as a “Fruit Loops algorithm,” a popularity-based algorithm that gives users what they expect to see.

Satisfying user intent is what Google means when they talk about showing relevant results. In the old days, it meant showing webpages that contained the keywords that a user typed. Now it means showing the webpage that most users expect to see.

Essentially, the search results pages are similar to the cereal aisle at your supermarket. That’s not a criticism, it’s an observation.

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I think it’s useful to think of the search results as a supermarket aisle and considering what kind of “cereal” is most popular. It may influence your content strategy in a positive way.

Insight 5: Expand the Range of Content

Google’s search results are biased to show the content that users expect to see.

This is why Google shows YouTube videos in the search results. It’s what people want to see.

It’s why Google shows featured snippets, it’s what satisfies the most people today who use mobile phones.

It’s not entirely accurate to complain that Google’s search results favor YouTube videos. People find video content useful, particularly for the how-to type of content. That’s why Google shows it.

It’s a bias in the search results, yes. But it’s a reflection of the users’ bias, not Google’s bias.

So if the user has a bias that favors YouTube videos, what should your online strategy response be?

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Write more content and build links to it? Or is the proper response to shift to the kind of content users want, in this case, video?

So if you see the search results are favoring a certain kind of content, pivot to producing that kind of content.

Learn to read the room in terms of what users want by paying close attention to what Google is ranking.

Insight 6: Drops in Ranking and NLP

Drops in ranking can sometimes be explained by a shift in how Google interprets what users mean when they search for something.

Google is increasingly using Natural Language Processing (NLP) algorithms which influences what Google believes users want when they search for something.

For example, I witnessed a near rewrite of what kind of content ranked at the top in a certain niche. Informational content zipped to the top, commercial content dropped to the bottom of the top 10.

There was nothing wrong with the commercial sites that dropped, other than how Google understood user intent changed.

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Trying to “fix” the commercial sites by adding more links, disavowing links, or adding more keywords to the page is unlikely to help the rankings.

Fixing something that isn’t broken never helps.

That’s why sometimes, it’s a good idea to study the search results first when diagnosing why a site lost ranking.

There might not be anything to fix. But there may be changes needing to be considered.

If your site has dropped in rankings, review what Google is ranking.

If the kinds of sites still ranking feature different content (focus, topic, etc) then the reason why your site dropped may not be about something that’s wrong.

It may be about something that needs changing.

Insight 7: Click Data Helps Determine User Intent

This is why I use the phrase “Fruit Loops Algo” to refer to Google’s user-intent-focused algorithm. It’s not meant as a slur. It’s meant to illustrate the reality of how Google’s search engine works.

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Many people want Fruit Loops and Captain Crunch breakfast cereals. The supermarkets respond by giving consumers what they want.

Search algorithms can operate in a similar manner.

A Better Definition of Relevance

That’s not keyword relevance to search terms you’re looking at — it’s relevance to what most users are expecting to see.

Sometimes that is expressed in how many links a site receives.

But I’m fairly confident that one of the ways user intent is understood is by click log data.

Here’s a patent filed by Google that discusses using click data to understand user intent, Modifying Search Result Ranking Based on Implicit User Feedback .

“Internet search engines aim to identify documents or other items that are relevant to a user’s needs and to present the documents or items in a manner that is most useful to the user. Such activity often involves a fair amount of mind-reading—inferring from various clues what the user wants.

…user reactions to particular search results or search result lists may be gauged, so that results on which users often click will receive a higher ranking. The general assumption under such an approach is that searching users are often the best judges of relevance, so that if they select a particular search result, it is likely to be relevant, or at least more relevant than the presented alternatives.”

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Understanding user intent is so important that Google and other search engines have developed eye-tracking and viewport time technologies to measure where on a search result mobile users are lingering. This helps to measure user satisfaction and understand user intent for mobile users.

Is Google or the User Biased Toward Brands?

Some people believe that Google has a big brand bias. But that’s not it at all.

If you consider this in light of what we know about Google’s algorithm and how it tries to satisfy user intent, then you will understand that if Google shows a big brand it’s because that is what users expect to see.

If you want to change that situation then you must create a campaign to build awareness for your site so that users begin to expect to see your site at the top.

Yes, links play a role in that. But other factors such as what users type into search engines also play a role.

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Someone once argued that Google should show results about the river when someone typed Amazon into Google. But that is unreasonable if what most people expect to see is Amazon the shopping site.

Again, Google is not matching keywords in that search query. Google is identifying the user intent and showing users what they want to see.

Key Takeaways

Understand the Search Results

The 10 links are not ordered by which page has the best on-page SEO or the most links. Those 10 links are ordered by user intent.

Write for User Intent

Understand what users want to accomplish and make that the focus of the content. Too often publishers write content focused on keywords, what some refer to as “semantically rich” content.

In 2015 I published an article about User Experience Marketing in which I proposed that focusing on user intent will put you in line with how Google ranks websites.

•What user intent is the content satisfying?
•What task or goal is the content helping the site visitor accomplish?”

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Understand Content Popularity

Content popularity is about writing content that can be understood by the widest audience possible. That means paying attention to the minimum grade level necessary for understanding your content.

If the grade level is high, this means your content may be too difficult for some users to understand.

I am not saying that Google prefers sites that a sixth-grader can understand. I am only stating that if you want to make your site easily understood by search engines and the most users, then paying attention to the difficulty of your content may be useful.

Google is not a keyword-matching search engine. Google is arguably a User Intent Matching Engine. Knowing and understanding this will improve everyone’s SEO.

There is a profound insight into understanding this and adapting your search marketing strategy to it.

Use What Is Known About Google’s Ranking Algorithms

Google publishes an astonishing amount of information about the algorithms used to rank websites. There are many other research papers that Google does not acknowledge whether or not the technology is in use.

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One can level up their SEO and marketing success by knowing what algorithms Google has admitted to using and what kinds of algorithms have been researched.

More Resources:


Featured image: Master1305/Shutterstock

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What Is Schema Markup & Why Is It Important For SEO?

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What Is Schema Markup & Why Is It Important For SEO?

Schema.org is a collection of vocabulary (or schemas) used to apply structured data markup to web pages and content. Correctly applying schema can improve SEO outcomes through rich snippets.

Structured data markup is translated by platforms such as Google and Microsoft to provide enhanced rich results (or rich snippets) in search engine results pages or emails. For example, you can markup your ecommerce product pages with variants schema to help Google understand product variations.

Schema.org is an independent project that has helped establish structured data consistency across the internet. It began collaborating with search engines such as Google, Yahoo, Bing, and Yandex back in 2011.

The Schema vocabulary can be applied to pages through encodings such as RDFa, Microdata, and JSON-LD. JSON-LD schema is preferred by Google as it is the easiest to apply and maintain.

Schema is not a ranking factor.

However, your webpage becomes eligible for rich snippets in SERPs only when you use schema markup. This can enhance your search visibility and increase CTR on your webpage from search results.

Schema can also be used to build a knowledge graph of entities and topics. Using semantic markup in this way aligns your website with how AI algorithms categorize entities, assisting search engines in understanding your website and content.

This means that search engines should have additional information to help them figure out what the webpage is about.

You can even link your entities directly to sites like Wikipedia or Google’s knowledge graph to build explicit connections. Using Schema this way can have positive SEO results, according to Martha van Berkel, CEO of Schema App:

By helping search engines understand content, you are assisting them in saving resources (especially important when you have a large website with millions of pages) and increasing the chances for your content to be interpreted properly and ranked well. While this may not be a ranking factor directly, Schema helps your SEO efforts by giving search engines the best chance of interpreting your content correctly, giving users the best chance of discovering it.

Listed above are some of the most popular uses of schema, which are supported by Google and other search engines.

You may have an object type that has a schema.org definition but is not supported by search engines.

In such cases, it is advised to implement them, as search engines may start supporting them in the future, and you may benefit from them as you already have that implementation.

Google recommends JSON-LD as the preferred format for structured data. Microdata is still supported, but JSON-LD schema is recommended.

In certain circumstances, it isn’t possible to implement JSON-LD schema due to website technical infrastructure limitations such as old content management systems). In these cases, the only option is to markup HTML via Microdata or RDFa.

You can now mix JSON-LD and Microdata formats by matching the @id attribute of JSON-LD schema with the itemid attribute of Microdata schema. This approach helps reduce the HTML size of your pages.

For example, in a FAQ section with extensive text, you can use Microdata for the content and JSON-LD for the structured data without duplicating the text, thus avoiding an increase in page size. We will dive deeper into this below in the article when discussing each type in detail.

JSON-LD encodes data using JSON, making it easy to integrate structured data into web pages. JSON-LD allows connecting different schema types using a graph with @ids, improving data integration and reducing redundancy.

Let’s look at an example. Let’s say that you own a store that sells high-quality routers. If you were to look at the source code of your homepage, you would likely see something like this:

Once you dive into the code, you’ll want to find the portion of your webpage that discusses what your business offers. In this example, that data can be found between the two

tags.

The following JSON-LD formatted text will markup the information within that HTML fragment on your webpage, which you may want to include in your webpage’s

section.



This snippet of code defines your business as a store via the attribute"@type": "Store".

Then, it details its location, contact information, hours of operation from Monday to Saturday, and different operational hours for Sunday.

By structuring your webpage data this way, you provide critical information directly to search engines, which can improve how they index and display your site in search results. Just like adding tags in the initial HTML, inserting this JSON-LD script tells search engines specific aspects of your business.

Let’s review another example of WebPage schema connected with Organization and Author schemas via @id. JSON-LD is the format Google recommends and other search engines because it’s extremely flexible, and this is a great example.



In the example:

  • Website links to the organization as the publisher with @id.
  • The organization is described with detailed properties.
  • WebPage links to the WebSite with isPartOf.
  • NewsArticle links to the WebPage with isPartOf, and back to the WebPage with mainEntityOfPage, and includes the author property via @id.

You can see how graph nodes are linked to each other using the"@id"attribute. This way, we inform Google that it is a webpage published by the publisher described in the schema.

The use of hashes (#) for IDs is optional. You should only ensure that different schema types don’t have the same ID by accident. Adding custom hashes (#) can be helpful, as it provides an extra layer of insurance that they will not be repeated.

You may wonder why we use"@id"to connect graph nodes. Can’t we just drop organization, author, and webpage schemas separately on the same page, and it is intuitive that those are connected?

The issue is that Google and other search engines cannot reliably interpret these connections unless explicitly linked using @id.

Adding to the graph additional schema types is as easy as constructing Lego bricks. Say we want to add an image to the schema:

{
   "@type": "ImageObject",
   "@id": "https://www.example.com/#post-image",
   "url": "https://www.example.com/example.png",
   "contentUrl": "https://www.example.com/example.png",
   "width": 2160,
   "height": 1215,
   "thumbnail": [
     {
        "@type": "ImageObject",
        "url": "https://example.com/4x3/photo.jpg",
        "width": 1620,
        "height": 1215
      },
      {
        "@type": "ImageObject",
        "url": "https://example.com/16x9/photo.jpg",
        "width": 1440,
        "height": 810
      },
      {
        "@type": "ImageObject",
        "url": "https://example.com/1x1/photo.jpg",
        "width": 1000,
        "height": 1000
      }
    ]
}

As you already know from the NewsArticle schema, you need to add it to the above schema graph as a parent node and link via @id.

As you do that, it will have this structure:



Quite easy, isn’t it? Now that you understand the main principle, you can build your own schema based on the content you have on your website.

And since we live in the age of AI, you may also want to use ChatGPT or other chatbots to help you build any schema you want.

2. Microdata Schema Format

Microdata is a set of tags that aims to make annotating HTML elements with machine-readable tags much easier.

However, the one downside to using Microdata is that you have to mark every individual item within the body of your webpage. As you can imagine, this can quickly get messy.

Take a look at this sample HTML code, which corresponds to the above JSON schema with NewsArticle:

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000, we have grown to a team of 200 dedicated employees.

Our slogan is: "Innovation at its best".

Contact us at +1-800-555-1212 for customer service.

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author: John Doe. Connect with John on Twitter and LinkedIn.

If we convert the above JSON-LD schema into Microdata format, it will look like this:

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000-01-01, we have grown to a team of 200 dedicated employees.

Our slogan is: Innovation at its best.

Contact us at +1-800-555-1212 for Customer Service.

Example Company Logo

Connect with us on: Facebook, Twitter, LinkedIn

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author:

Example image

This example shows how complicated it becomes compared to JSON-LD since the markup is spread over HTML. Let’s understand what is in the markup.

You can see

tags like:


By adding this tag, we’re stating that the HTML code contained between the

blocks identifies a specific item.

Next, we have to identify what that item is by using the ‘itemtype’ attribute to identify the type of item (Person).


An item type comes in the form of a URL (such as https://schema.org/Person). Let’s say, for example, you have a product you may use http://schema.org/Product.

To make things easier, you can browse a list of item types here and view extensions to identify the specific entity you’re looking for. Keep in mind that this list is not all-encompassing but only includes ones that are supported by Google, so there is a possibility that you won’t find the item type for your specific niche.

It may look complicated, but Schema.org provides examples of how to use the different item types so you can see what the code is supposed to do.

Don’t worry; you won’t be left out in the cold trying to figure this out on your own!

If you’re still feeling a little intimidated by the code, Google’s Structured Data Markup Helper makes it super easy to tag your webpages.

To use this amazing tool, just select your item type, paste in the URL of the target page or the content you want to target, and then highlight the different elements so that you can tag them.

3. RDFa Schema Format

RDFa is an acronym for Resource Description Framework in Attributes. Essentially, RDFa is an extension to HTML5 designed to aid users in marking up structured data.

RDFa isn’t much different from Microdata. RDFa tags incorporate the preexisting HTML code in the body of your webpage. For familiarity, we’ll look at the same code above.

The HTML for the same JSON-LD news article will look like:

vocab="https://schema.org/" typeof="WebSite" resource="https://www.example.com/#website">

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000-01-01, we have grown to a team of 200 dedicated employees.

Our slogan is: Innovation at its best.

Contact us at +1-800-555-1212 for Customer Service.

https://www.example.com Example Company Logo

Connect with us on: Facebook, Twitter, LinkedIn

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

https://www.example.com/about

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author: John Doe Profile Twitter LinkedIn

Example image

Unlike Microdata, which uses a URL to identify types, RDFa uses one or more words to classify types.

vocab=”http://schema.org/” typeof=”WebPage”>

If you wish to identify a property further, use the ‘typeof’ attribute.

Let’s compare JSON-LD, Microdata, and RDFa side by side. The @type attribute of JSON-LD is equivalent to the itemtype attribute of Microdata format and the typeof attribute in RDFa. Furthermore, the propertyName of JSON-LD attribute would be the equivalent of the itemprop and property attributes.

Attribute Name JSON-LD Microdata RDFa
Type @type itemtype typeof
ID @id itemid resource
Property propertyName itemprop property
Name name itemprop=”name” property=”name”
Description description itemprop=”description” property=”description”

For further explanation, you can visit Schema.org to check lists and view examples. You can find which kinds of elements are defined as properties and which are defined as types.

To help, every page on Schema.org provides examples of how to apply tags properly. Of course, you can also fall back on Google’s Structured Data Testing Tool.

4. Mixing Different Formats Of Structured Data With JSON-LD

If you use JSON-LD schema but certain parts of pages aren’t compatible with it, you can mix schema formats by linking them via @id.

For example, if you have live blogging on the website and a JSON-LD schema, including all live blogging items in the JSON schema would mean having the same content twice on the page, which may increase HTML size and affect First Contentful Paint and Largest Contentful Paint page speed metrics.

You can solve this either by generating JSON-LD dynamically with JavaScript when the page loads or by marking up HTML tags of live blogging via the Microdata format, then linking to your JSON-LD schema in the head section via “@id“.

Here is an example of how to do it.

Say we have this HTML with Microdata markup with itemid="https://www.example.com/live-blog-page/#live-blog"

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We can link to it from the sample JSON-LD example we had like this:



If you copy and paste HTML and JSON examples underneath in the schema validator tool, you will see that they are validating properly.

The schema validator does validate the above example.The schema validator does validate the above example.

The SEO Impact Of Structured Data

This article explored the different schema encoding types and all the nuances regarding structured data implementation.

Schema is much easier to apply than it seems, and it’s a best practice you must incorporate into your webpages. While you won’t receive a direct boost in your SEO rankings for implementing Schema, it can:

  • Make your pages eligible to appear in rich results.
  • Ensure your pages get seen by the right users more often.
  • Avoid confusion and ambiguity.

The work may seem tedious. However, given time and effort, properly implementing Schema markup is good for your website and can lead to better user journeys through the accuracy of information you’re supplying to search engines.


Image Credits

Featured Image: Paulo Bobita
Screenshot taken by author

 

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Gen Z Ditches Google, Turns To Reddit For Product Searches

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In this photo illustration, the Reddit logo is displayed on a smartphone screen.

A new report from Reddit, in collaboration with GWI and AmbassCo, sheds light on the evolving search behaviors of Generation Z consumers.

The study surveyed over 3,000 internet users across the UK, US, and Germany, highlighting significant changes in how young people discover and research products online.

Here’s an overview of key findings and the implications for marketers.

Decline In Traditional Search

The study found that Gen Z uses search engines to find new brands and products less often.

That’s because they shop online differently. They’re less interested in looking for expert reviews or spending much time searching for products.

There are also frustrations with mobile-friendliness and complex interfaces on traditional search platforms.

Because of this, traditional SEO strategies might not work well for reaching younger customers.

Takeaway

Companies trying to reach Gen Z might need to try new methods instead of just focusing on being visible on Google and other search engines.

Rise Of Social Media Discovery

Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Gen Z is increasingly using social media to find new brands and products.

The study shows that Gen Z has used social media for product discovery 36% more frequently since 2018.

This change is affecting how young people shop online. Instead of searching for products, they expect brands to appear in their social media feeds.

1719123963 547 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Because of this, companies trying to reach young customers need to pay more attention to how they present themselves on social media.

Takeaway

To succeed at marketing to Gen Z, businesses will likely need to focus on two main things:

  1. Ensure that your content appears more often in social media feeds.
  2. Create posts people want to share and interact with.

Trust Issues With Influencer Marketing

Even though more people are finding products through social media, the report shows that Gen Z is less likely to trust what social media influencers recommend.

These young shoppers often don’t believe in posts that influencers are paid to make or products they promote.

Instead, they prefer to get information from sources that feel more real and are driven by regular people in online communities.

Takeaway

Because of this lack of trust, companies must focus on being genuine and building trust when they try to get their websites to appear in search results or create ads.

Some good ways to connect with these young consumers might be to use content created by regular users, encourage honest product reviews, and create authentic conversations within online communities.

Challenges With Current Search Experiences

The research shows that many people are unhappy with how search engines work right now.

More than 60% of those surveyed want search results to be more trustworthy. Almost half of users don’t like looking through many search result pages.

Gen Z is particularly bothered by inaccurate information and unreliable reviews.

1719123963 785 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Takeaway

Given the frustration with search quality, marketers should prioritize creating accurate, trustworthy content.

This can help build brand credibility, leading to more direct visits.

Reddit: A Trusted Alternative

The report suggests that Gen Z trusts Reddit when looking up products—it’s their third most trusted source, after friends and family and review websites.

1719123963 403 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Young users like Reddit because it’s community-based and provides specific answers to users’ questions, making it feel more real.

It’s worth noting that this report comes from Reddit itself, which probably influenced why it’s suggesting its own platform.

Takeaway

Companies should focus more on being part of smaller, specific online groups frequented by Gen Z.

That could include Reddit or any other forum.

Why SEJ Cares

As young people change how they look for information online, this study gives businesses important clues about connecting with future customers.

Here’s what to remember:

  • Traditional search engine use is declining among Gen Z.
  • Social media is increasingly vital for product discovery.
  • There’s growing skepticism towards influencer marketing.
  • Current search experiences often fail to meet user expectations.
  • Community-based platforms like Reddit are gaining trust.

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Google Clarifies Organization Merchant Returns Structured Data

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Google updates organization structured data for merchant returns

Google quietly updated their organization structured data documentation in order to clarify two points about merchant returns in response to feedback about an ambiguity in the previous version.

Organization Structured Data and Merchant Returns

Google recently expanded their Organization structured data so that it could now accommodate a merchant return policy. The change added support for adding a sitewide merchant return policy.

The original reason for adding this support:

“Adding support for Organization-level return policies

What: Added documentation on how to specify a general return policy for an Organization as a whole.

Why: This makes it easier to define and maintain general return policies for an entire site.”

However that change left unanswered about what will happen if a site has a sitewide return policy but also has a different policy for individual products.

The clarification applies for the specific scenario of when a site uses both a sitewide return policy in their structured data and another one for specific products.

What Takes Precedence?

What happens if a merchant uses both a sitewide and product return structured data? Google’s new documentation states that Google will ignore the sitewide product return policy in favor of a more granular product-level policy in the structured data.

The clarification states:

“If you choose to provide both organization-level and product-level return policy markup, Google defaults to the product-level return policy markup.”

Change Reflected Elsewhere

Google also updated the documentation to reflect the scenario of the use of two levels of merchant return policies in another section that discusses whether structured data or merchant feed data takes precedence. There is no change to the policy, merchant center data still takes precedence.

This is the old documentation:

“If you choose to use both markup and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”

This is the same section but updated with additional wording:

“If you choose to use both markup (whether at the organization-level or product-level, or both) and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”

Read the newly updated Organization structured data documentation:

Organization (Organization) structured data – MerchantReturnPolicy

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