Assessing the Pros and Cons of Structured Data Implementation
In today’s era of the semantic web, understanding the pros and cons of implementing structured data is giving businesses a lead advantage.
Many SEOs are passionate about the power of implementing structured data (SD) but need help with convincing executives to implement it. This article and the handy table in it will help you get buy-in. We’ll look at both the Pros and Cons of implementing structured data.
Table of Contents
- Assessing the Pros and Cons of Structured Data Implementation
- What are the Pros of Implementing Structured Data Markup?
- Converts unstructured data into structured data
- Adds detail-rich relational attributes
- Improves your presence on SERPs
- May provide position zero visibility
- Increases CTR and organic revenue
- Schema markup is first-party data
- Increases your brand presence
- Organizes a site’s taxonomy
- Assists with indexing issues
- Schema matches query intent better
- It is easy to automate updates
- Improves voice search domination
- Potential customers get more information
- Table Showing the PROS VS CONS of Structured Data Markup
- What are the Cons of Using Structured Data Markup?
- Microdata can end up messy
- SD requires a time investment
- Schema markup plugins may conflict
- Risks of schema duplication from multiple apps
- Placement of the wrong type of schema
- Issues with time sensitive data
- Displaying different structured data based on user detection
- Delayed AngularJS or Ajax populating site content
- Google’s General Categories of Search results
- New Rich Result Types Empowered by Structured Data
Having proof, more marketers now believe that structured data is essential for enhanced SERP presence. This includes getting noticed for a lot more than your Brand SERP. Significant advantages are gained in making structured data the foundation for your SEO strategies. The implementation of Schema Markup is necessary to be competitive for both e-commerce sites and service-based businesses. Let’s clear up a few questions and then dive in.
What are Structured data vs Unstructured Data Rich Results?
Many featured snippets are drawn from structured data code. When it comes to structured versus unstructured data, structured data is more understandable and useable.
Search engines discover and may display this structured information on their results pages. Too many digital marketers and SEOs have underestimated the value of using these semantic annotations. Before we go further, let’s define this.
What is semantic annotation?
Semantic annotation or tagging is the process of using schema markup to attach metadata about concepts to a text document or other unstructured content. This may be structured data about people, events, reviews, places, organizations, products, relationships, or relevant topics.
What is the difference between schema, rich snippets & structured data?
Many terms are used interchangeably. Essentially, schema markup is the same as structured data. We are focused on structured data here. It lets you provide clear, organized data about your content so that search engines understand it better.
Schema.org is a vast organizer of structured data. Google cares about this type, but rich snippets are only generated by the ones that its search engine incorporates. OpenGraph is another structured data format; it’s used almost exclusively for social media sites such as Facebook, Twitter, and Pinterest.
Rich Snippets are the visually compelling widgets that Google displays in search engine result pages (SERPs) using your data. Google has absolute control over its rich snippet displays, but implementing structured data increases chances of winning rich snippets.
What are the Pros of Implementing Structured Data Markup?
- Converts unstructured data into structured data.
- Adds detail-rich relational attributes.
- Improves your presence on SERPs.
- May provide position zero visibility.
- Increases Click-Through-Rate and organic revenue.
- Schema markup is first-party data.
- Increases your brand presence.
- Organizes a site’s taxonomy.
- Assists with indexing issues.
- Schema matches query intent better.
- It is easy to automate updates.
- Improves voice search domination.
- Potential customers get more information versus just a URL and meta description.
- Google indicates that using structured data may help its crawler identify product reviews, which in turn is helpful for indexing.
Since there are many more structured data pros than cons, let’s take a look at each one more in-depth. With so much to gain from implementing structured data, we can assume that Google is dangling a carrot to entice more sites to use it. In this way, Google may be “forcing our hand” to utilize structured data more. If the benefits far out-weigh not using it, why not dive in deeper to schema markup?
Pros of Using Structured Data:
1. Converts unstructured data into structured data
One of the benefits of structured data is that its basic types can be used by the average SEO professional with a working understanding of how the data assists search. This makes your content more machine readable. It communicates with the search bots and aids them in assigning meaning and value to a web page. When this occurs, content created for the user is more understandable by search engines so they can surface it faster.
Once in structured format, it assists Google’s ability to identify content’s relevancy. This helps to solve language barrier issues on a search engine.
Google tells us, “Structured data is a standardized format for proving information about a page and classifying the page content”. A big advantage is to start with identify the main entity of a page. This is the main concept that you want to get across. Then, looking at what structured data type exists that you can leverage to make this more machine readable. Structured data markup provides contextual signals that attract potential customers. Next, we recommend adding factual content with ClaimReview structured data can enable a summarized fact check to display in Google Search results.
Schema markup lets you be more granular when informing search engines of your pages content. For example, help your events be more discoverable and attended by adding schema markup to your event pages. Also, author schema markup demonstrates author topic expertise.
2. Adds detail-rich relational attributes
By using about schema, nested mentions, and adding detail-rich relational attributes, you can gain the benefits of semantic annotation. This assists in meeting your audience’s intent when searching. The relational attributes connect concepts and meaning. This in turn created a better user experience because more often they gain the right answers to their questions.
Rich snippets typically reduce high bounce rates because people gain more information before clicking through to a site. Your code is helping search engines display details that lets users assess what your page is about before navigating there. It helps to relate content entities to other pages and the internet as a whole.
3. Improves your presence on SERPs
Image structured data adds that eye catching element that nabs your audience. It increased your chances to get a nice looking SERP. This gives your business extra exposure and attracts interested visitors to your website. Schema markup’s rich result potential to build a quasi-knowledge graph on your site and relate key entities together. Off site, business owners have never before been so empowered to influence the Google Knowledge Graph.
4. May provide position zero visibility.
Most rich results that are triggered by schema are shown on top of the SERP. Meaning your potential customers who don’t scroll down have a higher chance of seeing you. On average, “will give you an advantage of 4 average positions on SERP” – merkle “Schema for SEO: What, Why, and How?”
To increase your chances on winning position zero, you need an effective schema strategy in place. Identify what’s most important to the reader and the purpose of each page. Content represented on a page may not be important enough to build into your internal knowledge graph.
5. Increases CTR and organic revenue
Structured can help your pages rank higher on SERP. For example, people can click through to your site via a link in People Also Ask and People Also Ask SERPs. Your business can gain better CTRs, which equals improved organic search traffic and ultimately volume. Additionally, once on your website, the Call-to-Action (CTA) of the webpage simultaneously increases.
6. Schema markup is first-party data
Meaning, you don’t have to ask to use. It’s open source. Anyone can use it and customize it to amplify your content. Schema structured data is clean code. Plugins tend to make a site end up with loads of unhelpful markup.
By owning your data, you can gain prominence in How-To Content. Clear steps demonstrating your knowledge can show up right in immediate SERPs.
7. Increases your brand presence
These visual eye-candy rich snippets make your brand stand out. Increased SERP-rich snippets significantly differentiate one business from the other. It provides a strong competitive edge over others who want to be discovered by the same search queries.
You can use schema markup to highlight information about a corporation or person. It can improve your brand’s “findability” in search when you add schema markup to webpages correctly. For example, your about page can use
About structured data which can be rich with your brand details. This is one way in which you can manage your brand SERP.
Also, structured data implementation has a key hand when it comes to influencing your Knowledge Graph.
8. Organizes a site’s taxonomy
Structured data is helpful for organizing topics, which is conveniently stored in data warehouses.
A content taxonomy is a scheme of classification that is made up of more than titling and folder organizing. Meta tagging is another important way of organizing content that aids in your content marketing’s discoverability, content marketing strategy, and content marketing distribution.
It helps organize content by entities. It can support the categories you are already using. It helps the content-writing processes come together. For example, schema can provide local business NAP on location-specific pages, or go more in-depth on a topic with a full Question Answer page. Data warehouses are optimized to save storage space and encourage easy data access. Conversely, unstructured data which is much less defined is stored in data lakes with much greater storage capacity.
It creates high-quality search data that Artificial Intelligence understands. This creates a better on-site experience because they can quickly find the content they want. There are different schema intents. Use the right one for transactional intent versus informational. Choosing the best schema intent and metadata for each page helps keep your content’s taxonomy clear.
9. Assists with indexing issues
Structured Data can help with indexing because Google understands that page better. by making content more readable, Google can more easily understand it. It is less likely to index confusing content that is unclear who or how it might be used.
Some pages are more nuanced but they don’t need to be confusing to Google. When creating a more industry specific page, it often doesn’t fall within a perfect Schema.org representation. By using a catch-all
Thing markup, you’re able to use structured data to represent an industry specific entity. Within your
Article schema, you have a chance to more fully define it. Then by using
sameAs you can add external definitions such as Wikipedia to further expound on that industry correlation.
10. Schema markup matches query intent better
When your data is in structured format it can match query intent both better and faster. For example, it can trigger local relevance for the maps pack. Or help the searcher find a particular organization in Google real estate.
11. It is easy to automate updates
You can write a script to pull new data files into the markup. Code needs to populate from the actual information that the user can read on that page. Dynamic product schema is essential eCommerce structured data.
Ways that product information commonly changes:
- If the price of the product updates.
- If a product review’s ratings updates; or the number of reviews increases.
- If stock availability changes.
- If an additional product color, size, or sales package is offered.
Larger retail sites with many products must rely on schema automation to keep current and accurate schema. Not only is a product page updated, but also the code should populate with updates to match what is on the page. Again, a script can pull the updated text into the Schema that is generated for that page.
Have you ever tried to buy something that comes in multiple formats and cannot easily select and order the one you want? In the same way, schema improves the user experience. When a GTIN is assigned to a specific product version, that item is easily findable on the web, and it’s faster to check out the product you want.
12. Improves voice search domination
Your business should use
Speakable schema markup to help drive SEO performance and respond to voice-activated searches. As fewer businesses are on board with this markup type, you can take lead advantage by being an earlier adopter. This is known as “data retrieval,” which improves on traditional and bandwidth-taxing of “information retrieval” methods.
Structured data is a foundational way to help machines understand your content. As people speak their queries using natural language, your structured data assist you in controlling how your information is worded. Your SEO needs to align with how search engines are in for the long game with structured data. It is a reliable means of providing s a more efficient way to effectively answer search queries. Search results can be spoken, as well as visual. Speakable lets you gain more personalized and factual results.
13. Potential customers get more information versus just a URL and meta description
Traditional blue links in SERPs still typically provided limited information. The rich results that you can gain for high-value structured data are vast. You may gain an entire table in SERPs, a detailed listicle, or a richly populated knowledge panel. It offers so many visually appealing ways to have prominence in search results.
Now let’s look at the other side of implementation, its challenges, and potential cons. But first, let’s put both in a table format for easy comparison.
Table Showing the PROS versus CONS of Structured Data Markup
|Assessing the PROS & CONS of Structured Data Implementation|
|Converts unstructured data into structured data.||Microdata can end up messy.|
|Adds detail-rich relational attributes.||It requires a time investment.|
|Improves display on SERPs.||Schema markup plugins may conflict.|
|May provide position zero visibility.||Risks of schema duplication from multiple apps.|
|Increases Click-Through-Rate and organic revenue.||Placement of the wrong type of schema.|
|Schema markup is first-party data.||Issues with time sensitive data.|
|Increases your brand presence.||Displaying different structured data based on user detection.|
|Organizes a site’s taxonomy.||Delayed AngularJS or Ajax populating site content.|
|Assists with indexing issues.|
|It matches query intent better.|
|It is easy to automate updates.|
|Improves voice search domination.|
|Potential customers get more information versus just a URL and meta description.|
What are the Cons of Using Structured Data Markup?
There are good reasons to implement schema markup cautiously. Artificial Intelligence (AI) powered SEO can automate your schema markup.
With the right strategy, you can overcome the following cons. Converting vast, potentially valuable complex data into useful, findable, accessible information can maximize your data-driven systems and processes. It means you need the right approach to implementing structured data. Error can occur without being noticed. It’s better to be aware of what’s happening on site.
- Microdata can end up messy.
- SD requires a time investment.
- Schema markup plugins may conflict.
- Risks of schema duplication from multiple apps.
- Placement of the wrong type of schema.
- Issues with time sensitive data.
- Displaying different structured data based on user detection.
- Delayed AngularJS or Ajax populating site content.
- Fairing poorly in price comparrisons.
1. Microdata can end up messy
Microdata that annotates HTML tags is machine readable but can end up messy. Microdata needs to be used with every HTML tag within the webpage documents’ body. This is one reason we like JSON-LD schema better. It reduces risks of code bloat as it doesn’t need to be in every HTML tag. You can also learn how to partition JSON data batches and execute basic queries on loaded JSON data, and optionally remove repeated values.
The good news is that Google can recognize mixed formats of microdata, JSON-LD, and RDFa. Ultimately, being consistent and understanding where your markup is coming from is the best approach to implementation and maintenance. By having a semantic markup expert manage your schema you can avoid structured data markup drift.
Messy microdata can be a big problem. Ensure that your metadata is descriptive, meaningful, and represents the on-page content. Avoid repeating the same or similar meta descriptions. Make sure that your metadata is not deceptive.
2. SD requires a time investment
Many people may argue that implementing structured data markup can be easy and fast. At a basic level, this may be true. However, like all superior SEO, you can take it to a higher level to be more effective. While this takes both time to learn and maintain, studies show that the payoffs are worth it. The competitive edge, clicks, and revenue that you are likely to loose without being too high.
Some consider implementing structured data markup is like striking SEO gold for your SEO. I’d say, like all things if you want an exceptional return on investment, it will require some time to do expertly. And that time is worth it.
3. Schema markup plugins may conflict
This is a real possibility. It partly depends on the skill of your plugin developers and how quickly they update and solve issues. It may conflict with a WordPress theme or other code.
Wrong or conflicting structured data that triggers manual actions will also see subsequently lower rankings. Google’s general structured data guidelines are updated to state that structured data markup issues alone DON’T impact rankings in Search. Previous wording made it sound like pages or sites that violate these content guidelines may receive less favorable rankings, but Google clarified that’s not the case.
4. Risks of schema duplication from multiple apps
Many sites are not only using Yoast but additional plug-ins in hopes to add more useful structured data. Multiple apps can be used, like adding Wordlift, but you need an experienced schema markup auditor or you can end up duplicating schema types. You want to avoid duplicate the exact same property, and providing redundant information that only adds unnecessary code.
When useful, we custom add markup code as an additive sort of implementation. You should always be testing and watching your Google Search Console reports for structured data errors. It is worthwhile to build in time to clean things up. In the end, use a consistent tool or method for consistent implementation for fewer issues.
5. Placement of the wrong type of schema
Not only do audits often reveal that the wrong type schema markup is used, but it is also often placed on the wrong page. A common example is someone using Product structured data incorrectly by placing it on a category or collections page, versus the dedicate page where shoppers add it to their shopping cart. Hiring an expert Schema SEO person will remove these worries.
A consistent and correct schema implementation plan is better than trying to mix formats. When you have multiple pages of one markup type, like How-To, its best not to blend with
FAQ code. You are telling Google what is most important about your page. It can digest both markup types, but then it is up to the search engine which one it selects to use.
Avoid placing a wrong type on a page. Period. You need to stay current on updates, such as how AggregateRatings Schema for Reviews can be used. A novice schema implementer can even get you a manual action. Here is another “mix” to avoid; do not put
Course on the same page. If questions persist on what that type is, go back and review what the major class is.
6. Issues with time sensitive data
This is only an issue if you are manually updating your markup. For enterprise sites, it is critical to adopt a solution that actually populates and updates when the actual information changes. Static options on the website can be replaced with core data automation.
Sale prices are typically offered for a period of time. When the sale ends and that offer is removed from a web page, automation will immediately reflect the current price not the sale price. If the domain is brand-centric, it is likely to show up in Popular Products and other product carousel types. Your structure data markup can inform search engines so that they pull the right price, stock availability, and other details, like shipping information.
International websites frequently need to adapt prices based on a specific IP address or make content changes based on the demographic information of their user. A manual process takes more time and can leave you getting unwanted comments or emails. Know that incorrect or poor update implementation can be perceived as a manipulative action. The ideal scenario is that the markup remains the same cross sites, in different locations, and what is on the page is in your schema code.
7. Displaying different structured data based on user detection
You want to build Expertise, Authoritativeness, and Trustworthiness (E-A-T) for your site. That means providing consistent data and avoiding what my be perceived as a manipulation step. This means you need to be careful with what you automate.
“Often, data management is about attempting to amend the page’s content based on user detection. International sites often need to adapt prices based on a specific IP address and even update content based on the demographic information of their user,” according to seoClarity .
No matter the sector or size of the organization, keeping a business’s data organized, discoverable, actionable and compliant is paramount. Implementing AI and Machine Learning (ML) for managing unstructured data in Data Lakes helps improve the intuition of data processes, maintaining flexibility in the wake of constant change. Automating tasks also reduces strain on data engineers, allowing them to focus more on general value-add projects.
8. Delayed AngularJS or Ajax populating site content
Domains relying of AngularJS need to always add schema markup into the header, passed through the DOM, or add a third-party script. Then the code can be rendered on the page faster. Google penalizes websites if inserting attributes and content into schema markup that differs to content on the page. This is very granular; schema should precisely reflect what is on the page.
If there are significant delays in the time it takes for the content to render, Google may have already drawn its page conclusions and miss that schema markup. Check code load times so that if you are relying on AngularJS or Ajax, your markup loading so that it is valuable.
People often step back when we’re talking about code. However, many apps and plugins can take care of structured data for you. With the right marketing stack and team, you having to worry about coding or HTML.
9. Fairing poorly in price comparrisons
One con might be if your prices are higher than others without providing reasons why your products are a better value. Google Search is now showing “Cheaper Options” in it’s Product Detail Overlay. One thing you can do to counter this is to find ways to add more value by providing more and better FAQ schema on your product pages. For example, add a query like “How much should I pay for a new car?”. You might answer something like, “It depends on how long you want the car to last, what you’ll use it for, and how much maintenance you can provide on your own.”
Now lets step back and see why this conversation is so important for your SEO.
What are the Main Categories of Search Results?
Google’s General Categories of Search results
Implementing structured data markup improves your chances of gaining search features that provide visually appealing Google search results. This makes your content more engaging to users and typically encourages them to interact more with your website.
Google Search results currently offer many types of display features. Their display changes over time and the tech giant tests and tweaks its SERPs. Expect to see different results on a desktop computer versus a phone, the searchers’ location, or other factors. Google attempts to return a result in the most useful format for the searcher.
According to Google, here are the general categories of SERP displays :
- Plain blue link.
- Rich result.
- Knowledge panel entry.
- Featured snippet.
- OneBox result.
New Rich Result Types Empowered by Structured Data
If you are a retail merchant seeking to maximize your SERP space, implementing as many schema types will bring more value to page visitors. You can then show up more often in Google Shopping Results. We discovered that one new account had this Google Ads Message: “Add structured snippets to your account. Your ads are ’t as prominent as they could be if you used structured snippets, which can improve your CTR. Structured snippets are missing from 1 campaign.”
Structured snippets let consumers see a preview of your products and services before they click your ad. You may see positive changes in clicks, CTR, and the cost of paid search – if you add structured snippets.
Bring development to data with a team approach
Leverage speed, automation, concurrency, and extensibility to develop and run your data applications, models, and pipelines where dataset are useful. We can partner with you to use schema to gain more online traffic and organic sales.
“Approximately less than one-third of webpages on google use schema which leaves us with a lot of room to take advantage of schemas over our competitors to improve ranking and gain visibility,” according to merkle.
Rishabh Raj also stated in the June 4, 2021, Schema for SEO: What, Why and How? article that “this implementation will give you an advantage of 4 average positions on SERP”. These are remarkable benefits.
“Google Search works hard to understand the content of a page. You can help us by providing explicit clues about the meaning of a page to Google by including structured data on the page. Structured data is a standardized format for providing information about a page and classifying the page content.
Google Search also uses structured data to enable special search result features and enhancements. As Google continues to implement more rich search result features, the importance of structured data markup will only increase.
You must include all the required properties for an object to be eligible for appearance in Google Search with enhanced display. In general, defining more recommended features can make it more likely that your information can appear in Search results with enhanced display. However, it is more important to supply fewer but complete and accurate recommended properties rather than trying to provide every possible recommended property with less complete, badly-formed, or inaccurate data. – Understand how structured data markup works by Google 
SUMMARY: Deciding to Implement Structured Data
Consider the complexity, cost, and constraints inherent with available schema markup solutions and move forward. The pros far outweigh the cons of structured data. You don’t want to miss out. We can help your business develop data-driven marketing strategies beyond SEO. Data integration and interoperability can maximize how your content is consumed.
Partner with Hill Web Marketing and we’ll ensure you Stay Current with New Schema Opportunities