Structured vs. unstructured data: which one is better for SEO?
The answer for TL;DR – structured data is the best option for SEO.
There you have it!
Want to know why?
Keep reading this article till the end.
Even though structured data is gaining popularity, the SEO ecosystem still has a long way to go. In fact, 56% of companies are still not employing structured data for SEO.
Image via Semrush
For you, as a marketer, this means that you have an opportunity to advance your SEO game and gain an edge over your competitors.
In this post, you’ll learn everything you need to know about structured data and how to use it for SEO.
Let’s get started.
Structured data, aka schema markup, is a way of organizing data that helps search engines better understand and categorize your website content.
The site Schema.org contains a standard list of markups that all search engines support.
Here is an example of the schema used to structure the unstructured web page data:
Image via Google
The best part about structured data for SEO is that you don’t need coding knowledge to create schema markups. In fact, you can quickly generate schema for any type of data using our schema markup generator.
Examples of structured data:
There are several advantages of using structured data, including higher click-through rates, increased search visibility, faster indexing, and voice search dominance.
Unstructured data is an undefined piece of information that has no standard format.
Most of the data produced every day is unstructured. Companies collect so much info, but if unstructured information is hard to analyze, then what good is it?
The good part is that we are getting better at handling unstructured data such as pictures, audio, and text that has not been organized in a specific manner.
But it is still challenging and requires machine learning and natural language processing technologies to extract insights from this data.
Search engines like Google have been attempting to comprehend unstructured data for a long time, sending bots to crawl websites and understand their content. They are constantly improving at this, but unstructured data is still hard to comprehend.
Examples of unstructured data:
There are many instances where we produce unstructured data. When you take a picture, send an email, or create a voice note, for example.
However, when it comes to SEO, you must always keep structure in mind because without it, Google might have a difficult time figuring out what your webpage is about.
Even when you don't use structured data, use semi-structured data in the form of meta descriptions, headers, H1s, and H2s.
Image via Attrock
Semi-structured data is a blend of structured and unstructured data.
Rather than relying on a rigid structure like structured data, this form of data uses tags, attributes, and metadata to quickly communicate information to search engines.
As stated previously, unstructured data is what we create on the web most of the time.
However, when we combine this unstructured data with an approach to organize or locate it—such as metadata on web pages or links—we get semi-structured data.
Examples of semi-structured data are:
Pro Tip: Use on-page optimization tools like Surfer SEO and Yoast to ease the content structuring process.
Structured data, in the broadest sense, refers to a format of storing data in an organized manner. However, in the context of SEO, structured data refers to one thing: Schema.org markup.
It’s worth noting that Schema.org isn’t the only SEO-fluent markup vocabulary. There are websites like Microformats.org that facilitate markup for specific data sets. Still, Schema.org is the most trusted and popular one.
An initiative to build a better semantic web, Schema.org is a community founded by Google, Microsoft, Yahoo, and Yandex. The four search engines collaborated to develop schema vocabularies for structured data markup across the internet.
Marketers and website developers can easily participate in this initiative thanks to a common vocabulary consisting of schema.org types and properties.
JSON-LD, Microdata, and RDFa are the most commonly used structured data markup languages and all are available on Schema.org.
Let’s get a quick look at the top three structured data markup languages for SEO:
Pro Tip: Use JSON-LD data format, as it’s preferred by most search engines.
Here are some of the common use cases of structured data for SEO.
When you search for a person, place, or company on Google, you will come across a knowledge graph or knowledge panel—a comprehensive summary of data sourced from reputable sources.
Image via Google
Having Google create a knowledge panel for your brand is out of your control. However, once they do, you can control the data they share by connecting them to structured data on your site.
You can click on “suggest an edit” to instruct Google on what information you want to be displayed on the panel.
Image via Google
Google provides rich results that go beyond the standard blue link. A carousel, an image, or other non-textual elements can be included as part of a rich result.
Here’s an example of rich snippets on Google SERP. See how they stand out.
Image via Google
Do not confuse rich snippets with featured snippets. Both are different in context and SERP placement.
There can only be one featured snippet for a search query and that too when Google considers your content so valuable that it displays it at the top of the search results, like this:
Image via Google
Google determines the most valuable content to display for featured snippets without the use of structured data.
Structured markup is used in rich cards to display SERP content in a more engaging and visual format. The focus is on delivering a better mobile user experience than rich snippets.
Just like rich snippets, rich cards are built on schema.org. They appear like this on the SERP:
Image via Google
For instance, if you have a recipe site, you can create a visual representation of each dish on the site to build a richer preview. Users who are searching for a recipe will be able to find it right away, thanks to this visual format.
However, we recommend using both rich cards and snippets to give users a comprehensive web browsing experience.
Google Search also supports a more interactive and enhanced type of rich result known as enriched search results.
A very common example of an interactive search result featuring an immersive pop-up experience or other advanced interaction technology is the results for ‘jobs in an area.'
Image via Google
Google uses structured data to create an advanced filter feature that includes thousands of websites.
If you want your job result to appear in this location, you must include the appropriate markup and ensure it is as comprehensive as possible. This also applies ro results for recipes, events, etc.
An Accelerated Mobile Page (AMP) is a lightning-fast and mobile-oriented version of your web page that can be substituted for the original page in mobile search results.
Image via Google
Google Search can show AMP pages as rich results, just like other web pages. To help Google comprehend your web page better, you need to add structured data to it.
However, Google does not guarantee that using structured data will result in a favorable outcome in search results. For more info, see Google’s Structured Data General Guidelines.
Structured data is predefined and can be arranged in a spreadsheet like a date, name, address, barcode, and other similar data.
Unstructured data, on the other hand, refers to raw information captured in its initial form (like text files, photos, audio files, etc.)
Here is a quick comparison of structured vs. unstructured data:
| Characteristics | Structured Data | Unstructured Data |
| Nature | Quantitative Data | Qualitative Data |
| Data Model | Predefined Data Model | None |
| Searchability | Easy and quick | Complex and Time-Consuming |
| Analytics | Easy to analyze | Nearly impossible to analyze |
| Storage Space Requirement | Less | More |
| Data Storage | Spreadsheets, Data Warehouses, and Relational Database | Data Lakes |
| Query Language | Structured Query Language | JSON, No-SQL |
| Examples | Name, Age, Profession, Addresses, etc. | Email text, images, generic descriptions |
Now that we’ve done the structured vs. unstructured data comparison, you know that the former is better. Now, let’s learn how to use structured data for SEO.
Here is a step-by-step process on how to use structured data for SEO:
1. Open our schema markup generator tool (it’s free to use) and select the data type you want to use.
2. Then, fill in the page elements and assign tags.
3. When you fill in the details, the HTML is generated in real-time. You can copy the HTML and add it to your web page. You can also choose a format, though we recommend JSON-LD.
That’s it.
Q1. What are the most common types of structured data or schema markups?
A. Following are the most commonly used schema markups to structure unstructured data:
Q2. Structured vs. unstructured data – what’s the difference?
A. Here is a comparison of structured vs. unstructured data and their key differences:
Q3. For what is structured data used in SEO?
A. You can use structured data formats for the following SERP features:
Q4. What is Schema markup?
A. Schema markup (Schema.org) is an initiative to build a better semantic web by helping search engines understand web content better using structured data.
Q5. What are examples of unstructured data?
A. Here are some examples of unstructured data:
Using schema markups will help your search results stand out on SERP and attract more clicks.
Also, given that implementing schema markups is quite easy, it’s imperative for you to leverage the power of structured data for SEO. And if you need to take your SEO game to the next level, leverage our search engine optimization services.
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