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Top 7 SEO Keyword Research Tools For Agencies

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Top 7 SEO Keyword Research Tools For Agencies

All successful SEO campaigns rely on accurate, comprehensive data. And that process starts with the right keyword research tools.

Sure, you can get away with collecting keyword data manually on your own. But while you may be saving the cost of a premium tool, manual keyword research costs you in ot

her ways:

  • Efficiency. Doing keyword research manually is time intensive. How much is an hour of your time worth?
  • Comprehensiveness. Historical and comprehensive data isn’t easy to get on your own. It’s too easy to miss out on vital information that will make your SEO strategy a success.
  • Competition. Keyword research tools allow you to understand not only what users are searching for but also what your competition focuses on. You can quickly identify gaps and find the best path to profitability and success.
  • Knowledge. Long-time SEO experts can craft their own keyword strategies with a careful analysis of the SERPs, but that requires years of practice, trial, and costly errors. Not everyone has that experience. And not everyone has made enough mistakes to avoid the pitfalls.

A good SEO keyword research tool eliminates much of the guesswork. Here are seven well-known and time-tested tools for SEO that will get you well on the way to dominating your market.

1. Google Keyword Planner

Screenshot from Google Keyword Planner, January 2023

Cost: Free.

Google Keyword Planner is a classic favorite.

It’s free, but because the information comes directly from the search engine, it’s reliable and trustworthy. It’s also flexible, allowing you to:

  • Identify new keywords.
  • Find related keywords.
  • Estimate the number of searches for each variation.
  • Estimate competition levels.

The tool is easy to access and available as a web application and via API, and it costs nothing; it just requires a Google Ads account.

You must also be aware of a few things when using this tool.

First, these are estimates based on historical data. That means if trends change, it won’t necessarily be reflected here.

Google Keyword Planner also can’t tell you much about the SERP itself, such as what features you can capitalize on and how the feature converts.

Because it’s part of Google Ads, PPC experience can help you gain more insights. You’ll find trends broadly across a demographic or granular level, like a city, region, or major city.

Google Keyword Planner also tends to combine data for similar keywords. So, if you want to know if [keyword near me] is better than [keywords near me], you’ll need a different tool.

Lastly, the tool uses broad definitions of words like “competition,” which doesn’t tell you who is ranking for the term, how much they’re investing to hold that ranking, or how likely you are to unseat them from their coveted top 10 rankings.

That being said, it’s an excellent tool if you just want to get a quick look or fresh ideas, if you’d like to use an API and create your own tools, or simply prefer to do the other tasks yourself.

2. Keyword.io

Cost: Free, $29 per month, and $49 per month.

If Google’s Keyword Planner isn’t quite enough, but you’re on a tight budget, Keyword.io may be the alternative you need. It also has different features.

Keyword.io uses autocomplete APIs to pull basic data for several sites and search engines, including Google, Amazon, eBay, Bing, Wikipedia, Alibaba, YouTube, Yandex, Fiverr, and Fotolia. This is perfect for niche clients and meeting specific needs.

It also has a Question/Intent Generator, an interactive topic explorer, and a topical overview tool.

In its user interface (UI), you’ll find an easy-to-use filter system and a chart that includes the competition, search volume, CPC, and a few other details about your chosen keywords.

It does have some limits, however.

You can run up to 20,000 keywords per seed with a limit of 100 requests per day (five per minute) or 1,000 requests per day (10 per minute) on its paid plans.

Its API access, related keywords tool, Google Ad data, and other features are also limited to paid accounts.

3. Semrush

Semrush's keyword toolScreenshot from Semrush

Cost: $119.95 to $449.95 per month.

In its digital marketing suite, Semrush offers a collection of six keyword tools and four competitive analysis tools with a database of more than 21 billion keywords.

You can get a full overview of the keywords you’re watching, including paid and organic search volume, intent, competition, CPC, historical data, SERP analysis, and more.

You’ll get related keywords and questions, as well as a ton of guidance, ideas, and suggestions from the Semrush Magic, Position Tracking, and Organic Traffic Insights tools.

The Keyword Planner, however, is where much of the magic happens.

The organic competitor tab makes it easy to spot content and keyword gaps. Expand them and develop clusters that will help you grab traffic and conversions.

You can also see long-tail keyword data and other data to see what Page 1 holds regarding competition, difficulty, and opportunities at a broad or hyperlocal level.

The full suite of tools is a huge benefit. Teams can collaborate, share insights, and plan.

The seamless integration allows you to integrate your data, meaning teams can easily collaborate, share insights, and strategize.

And when you’re done, it can track everything you need for a successful digital marketing strategy.

Some of the tools they offer include:

  • On-page SEO tools.
  • Competitive analysis suite.
  • Log file analysis.
  • Site auditing.
  • Content marketing tools.
  • Marketing analysis.
  • Paid advertising tools.
  • Local SEO tools.
  • Rank tracking.
  • Social media management.
  • Link-building tools.
  • Amazon marketing tools.
  • Website monetization tools.

Semrush’s best features when it comes to keyword research are its historical information and PPC metrics.

You can deep dive into campaigns and keywords to unlock the secrets of the SERPs and provide agency or in-house teams with priceless information they don’t usually access.

4. Moz Keyword Explorer

Keyword Research Tool From MozScreenshot from Moz, January 2023

Cost: Free for 10 queries per month. $99-$599 per month.

With a database of more than 500 million keywords, Moz Keyword Explorer may be a great option if you’re looking to build a strategy rather than get a quick view of the data for a few keywords.

Moz has long been a leader in the SEO space.

Constantly updating and improving its Keyword Explorer Tool and its other core services, Moz keeps up with the trends and is well known for providing SEO professionals with the latest tools. And it has done so for more than a decade.

Like the Google Keyword Tool, Moz’s keyword planning tool provides information on the difficulty and monthly search volume for terms. It also lets you drill down geographically.

When you start, you’ll find the Keyword Overview, which provides monthly search volumes, ranking difficulty, organic click-through opportunities, and an estimated priority level.

You can also:

  • Find new relevant keywords you should be targeting but aren’t.
  • Learn how your site performs for keywords.
  • Find areas where you can improve your SEO (including quick wins and larger investments).
  • Prioritize keywords for efficient strategy creation.
  • Top SERP analysis and features.
  • Competitor analysis.
  • Organic click-through rates.

Unlike the Google Keyword Tool, however, Moz supplies you with data beyond the basics. Think of it like keyword research and SERP analysis.

Moz does tend to have fewer keyword suggestions. And like Google’s Keyword Planner, it provides range estimates for search data rather than a specific number.

However, the database is updated frequently, so you can feel confident that you’re keeping up with the constant change in consumer search habits and rankings.

Plus, it’s easy to use, so teams can quickly take care of marketing tasks like finding opportunities, tracking performance, identifying problem areas, and gathering page-level details.

Moz also offers several other tools to help you get your site on track and ahead of the competition, but we really like it for its keyword research and flexibility.

5. Ahrefs Keyword Explorer

Cost: $99-$999 per month.

If I had to describe Ahrefs in one word, it would be power.

Enter a word into the search box, and you’re presented with multiple panels that can tell you everything you want to know about that keyword.

Total search volume, clicks, difficulty, the SERP features, and even a volume-difficulty distribution. And while it may look like a lot, all the information is well-organized and clearly presented.

Ahrefs provides terms in a parent-child topic format, providing the terms with context, so you can easily learn more about the terms, such as intent, while identifying overlap and keeping it all easy to find and understand.

These topics appear when you search for a related term, including the term’s ranking on the SERP, SERP result type, first-page ranking difficulty scores, and a snapshot of the user-delivered SERP. You can stay broad or narrow it all down by city or language.

Ahrefs can get a bit expensive. Agencies may find it difficult to scale if they prefer several user or client accounts, but it’s still one of the best and most reliable keyword research tools on the market.

What I really like about Ahrefs is that it’s thorough. It has one of the largest databases of all the tools available (19.2 billion keywords, 10 search engines, and 242 countries at the time of writing), and it’s regularly updated.

It makes international SEO strategies a breeze and includes data for everything from Google and Bing to YouTube and Amazon.

Plus, they clearly explain their metrics and database. And that level of transparency means trust.

Other tools in the suite include:

  • Site Explorer.
  • Site auditing.
  • Rank tracking.
  • Content Explorer.

6. SERanking

SERanking's Keyword Research ToolScreenshot from SERanking, November 2022.

Cost: $23.52-$239 per month, depending on the ranking check and payment frequency.

SERanking shines as a keyword research tool within an all-around SEO toolkit. SERanking helps you keep costs down while offering features that allow agencies to meet clients’ unique needs.

One of the first things you’ll notice when you log in is its intuitive user interface. But this tool isn’t just another pretty online tool.

Its database is robust.

SERanking’s U.S. database includes 887 million keywords, 327 million U.S. domains, and 3 trillion indexed backlinks. And this doesn’t include its expansive European and Asian databases.

The overview page provides a solid look at the data, which includes search volume, the CPC, and a difficulty score.

SERanking also provides lists of related and low-volume keywords if you need inspiration or suggestions, as well as long-tail keyword suggestions with information about SERP features, competition levels, search volume, and other details you need to know to identify new opportunities.

Of course, identifying keywords is only the start of the mystery. How do you turn keywords into conversions? SERanking provides keyword tools that help you answer this question.

You can find out who the competition is in the organic results and see who is buying search ads, as well as details like estimated traffic levels and copies of the ads they’re using.

This allows you to see what’s working, gain insights into the users searching for those terms, and generate new ideas to try.

SERanking offers agency features, such as white labeling, report builders, lead generator, and other features you’ll find helpful.

However, one of the features agencies might find most helpful in keyword research is SERanking’s bulk keyword analysis, which lets you run thousands of keywords and download full reports for all the terms that matter.

Other tools in the SERanking Suite include:

  • Keyword Rank Tracker.
  • Keyword Grouper.
  • Keyword Suggestions and Search Volume Checker.
  • Index Status checker.
  • Backlink Checker.
  • Backlink monitoring.
  • Competitive research tool.
  • Website auditing tool.
  • On-page SEO Checker.
  • Page Changes Monitor.
  • Social media analytics.
  • Traffic analysis.

SERanking is more affordable than some of the other tools out there, but it does come at a cost.

It isn’t as robust as some of its competitors and doesn’t get as granular in the same way, but it still provides the features and data you need to create a successful SEO strategy.

And with its flexible pricing, this tool is well worth considering.

7. BrightEdge Data Cube

Cost: Custom pricing model.

If you’re looking for an AI-powered digital marketing tool suite that includes a quality research tool, BrightEdge may be the right option for you.

Unlike other tools that focus on supplying you with data and ways to analyze that data, BrightEdge looks to do much of the time-consuming analysis for you.

Among its search, content, social, local, and mobile solutions, you’ll find Data Cube – an AI-backed content and keyword tool that uses natural language processing to find related topics and keywords.

You’ll also encounter DataMind, an AI that helps you find search trends, changes in consumer behaviors, and important competitor movements you need to know about.

The two together make it quick and easy to perform keyword research, build out topics, create content strategies, and strengthen your SEO plans.

Once you enter a topic or broad keyword, the tool will provide you with relevant keywords, the search volume, competition levels, keyword value, it’s universal listing, and the number of words in the phrase.

Filter the results by a custom set of criteria to narrow the list down and get the necessary information.

Once you have a list, select the ones you want to keep and download them or use them with BrightEdge’s other tools to create full strategies and gain more insights.

This could include competitor analysis, analyzing SERP features, intent, or other tasks.

For agencies that provide local SEO, BrightEdge also offers HyperLocal, which helps you find and track keywords and keyword performance at the local level.

When you’re done, give the Opportunity Forecasting and tracking tools a try to monitor your progress and provide clients with the information they care about.

Perhaps the nicest feature for agencies is its Storybuilder – a reporting tool that allows you to create rich client reports that provide clients with targeted overviews and the data they’re most interested in.

If this sounds like the right tool for you, the company gives demos, but there are a few things you should consider.

First, it only updates once per month. And while the company keeps its pricing close to the chest, this digital marketing tool suite is a significant investment. It may not be the best choice if keyword research is the only thing you need.

Secondly, while the tools are highly sophisticated and refined, there is a learning curve to get started.

You’ll also discover that there are limits on features like keyword tracking, and it can be time-consuming to set up, with some adjustments requiring technical support.

Lastly, BrightEdge’s keyword research tool doesn’t let you get too far into the weeds and doesn’t include PPC traffic.

That aside, agencies and larger brands will find that it scales easily, has a beautifully designed UI, and makes you look great to clients.

The Best Agency SEO Keyword Research Tools

This list only contains seven of the many tools available today to help you get your keyword research done to an expert degree.

But no matter how many of the tools we share with you or which ones, it’s important to understand that none are flawless.

Each tool has its own unique strengths and weaknesses, so selecting a platform is very much dependent on the types of clients that you typically work with and personal preference.

In reality, you’ll likely find that you prefer to work between a few tools to accomplish everything you’d like.

Google Keyword Planner and Keyword.io are top choices when you want a quick look at the data, or you’d like to export the data to work on elsewhere. You may even want to use this data with the other tools mentioned in this chapter.

Ahrefs, Moz, Semrush, and BrightEdge are far more robust and are better suited to agency SEO tasks.

While not free (although they offer free plans or a trial period except BrightEdge), they allow you to really dig into the search space, ultimately resulting in higher traffic, more conversions, and stronger SEO strategies. These benefits require more time and often come with a learning curve.

By far, the most important keyword research tool you have access to is you.

Keyword research is more than simply choosing the keywords with the biggest search volume or the phrase with the lowest Cost Per Click (CPC).

It’s your expertise, experience, knowledge, and insights that transform data into digital marketing you can be proud of.


Featured Image: Paulo Bobita/Search Engine Journal



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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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Chuck Price

Founder at Measurable SEO

Looking for a Content Marketing Solution to Increase Traffic and Revenue? I’m the founder of Measurable SEO and former COO ...

Advanced Technical SEO: A Complete Guide



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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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