In an era when search engines increasingly rely on semantic understanding and AI to generate results, Schema Markup has emerged as a vital SEO tactic for website owners striving to maintain visibility and relevance in search.
However, Schema Markup is a very technical aspect of SEO, and navigating the complexities requires technical expertise, ongoing effort, and costs. As a result, we frequently encounter questions from our customers, digital marketers, and IT teams alike, seeking clarity on Schema Markup.
This article addresses some of these common questions head-on, providing insights to help you understand Schema Markup’s role in your SEO strategy to help you confidently implement it on your pages.
Let’s start with one of the most pressing questions newcomers to Schema Markup often ask…
Does Schema Markup help SEO?
Yes. Schema Markup contributes to SEO by improving click-through rates (CTR), which can indirectly support conversions. It aids SEO efforts in two main ways.
Firstly, it helps search engines comprehend and contextualize page content. Schema Markup enhances search engine understanding by identifying and describing entities on a page, which improves comprehension of the page’s topics and their connections within the site and across the web. This precision leads to more relevant search results, driving qualified traffic to your site.
In the context of AI search, where most search engines are powered by Large Language ****** (LLMs) prone to errors and hallucinations, this understanding becomes even more critical. Schema Markup can ground and train the Large Language ****** (LLMs) with factual information. This, in turn, allows them to provide more accurate search results and helps you control how the AI search engine interprets your brand and content, conveying that information accurately within search results.
Secondly, Schema Markup facilitates the generation of rich results. Rich results enable your content to stand out on the SERP as an enhanced organic search result, making it more attractive and engaging to users. This enhancement often leads to higher user engagement and CTR.
Specific types of rich results, such as Review Snippets, also play a crucial role in bolstering trust and credibility for your brand by fostering trust and positive brand perception through reviews and star ratings. For example, physician pages with Review Snippets tend to have higher CTRs than those without. Similarly, products featuring pricing information in the SERP through Product rich results typically garner more clicks.
Our customer, Baptist Health, saw a 491% increase in CTR for physician pages with review snippets compared to those without. Similarly, our customer Avid Technology experienced a substantial 241% increase in CTR for product pages with rich results compared to those without.
Is Schema Markup a search ranking factor?
No. Implementing Schema Markup does not directly impact your search rankings. However, it can indirectly impact rankings in certain ways.
While Schema Markup is not a direct ranking factor – like quality content, page speed, or backlinks – implementing Schema Markup can enhance your website’s appearance in the SERP by providing search engines with more clarity about your content, your organization and other associated entities.
This structured data enables search engines to better comprehend the content on your web pages. As a result, the search engine can more accurately align your page with the intent and meaning behind users’ relevant search queries, which could potentially improve your page’s ranking.
Can bad Schema Markup cause ranking loss?
Yes, it’s possible. Incorrect or poorly implemented Schema Markup can negatively affect your website’s search rankings.
What constitutes “bad” Schema Markup?
It could be markup that…
- Doesn’t accurately reflect the content on your page, aka schema drift.
- Goes against Google’s Content Guidelines – i.e. marking up invisible, irrelevant, or misleading content or engaging in other manipulative behaviors, which can be considered problematic.
If search engines encounter Schema Markup that is inaccurate, unclear, or violates their guidelines, they may ignore it or even penalize your site.
Some ways incorrect Schema Markup can impact your rankings include:
- Penalties: If search engines determine that your Schema Markup is manipulative or deceptive, they may penalize your website, resulting in lower rankings or even removal from search results.
- Misinterpretation: Incorrect Schema Markup can confuse search engines about your web pages’ content and context. This can lead to misinterpretations and may cause search engines to display your site less prominently or inaccurately in search results.
- User Experience: “Bad” Schema Markup can result in inaccurate or irrelevant information displayed on the SERP. This can lead to poor user experience, indirectly impacting your rankings as search engines aim to provide the most relevant and helpful results to users.
Can duplicate Schema Markup affect rankings?
While duplicate Schema Markup may not have a direct impact on rankings, it can diminish the effectiveness and clarity of your Schema Markup.
What is duplicate markup?
Duplicate markup refers to having two separate sets of markup describing the same entity, like a product, on a single page. If both markup sources provide identical content, such as the same product name and price, it’s typically not an issue. However, if the content differs between the two sources, for example, one block of Product markup shows a price of $15 while the other lists it as $15.99, it can confuse search engines like Google.
This confusion may reduce the likelihood of your page being awarded that result, resulting in uncertainty and potentially incorrect information on the SERP.
To conclude, duplicate markup may make your markup less effective if:
- The intent of the page is unclear
- There is conflicting information
Can there be two Schema Markup blocks on one page?
Yes, but let’s clarify. It is acceptable to have two primary entities that are neither identical nor nested and accurately describe the page. Ideally, the markup should be connected and/or nested, but this isn’t always possible given the hierarchy of entities on a page.
For instance, a Product Detail Page may have Product markup alongside BreadCrumb markup as primary entities. Since the breadcrumb isn’t related to the product entity, nesting it under the top-level Product markup doesn’t make sense.
However, if the page contains reviews and ratings related to the product, it’s advisable to nest the Review and AggregatingRating markup under the top-level Product markup. This accurately reflects the relationship between the product and these additional elements.
Ultimately, the goal is to clarify what’s on the page and how these content elements relate to each other. If there’s a connection, nesting is recommended; if not, having separate markup on a page is acceptable.
While Google won’t penalize you for failing to nest your markup, nesting is crucial for accurately representing relationships on your site and building a useful content knowledge graph.
How can I measure the performance of Schema Markup on my website?
How you measure performance may depend on the kinds of markup you’re adding to your page and your desired outcomes. You can assess performance either by individual URLs or by aggregating multiple URLs into groups, such as sitewide results or all pages within a specific subfolder.
There are a variety of tools you can use for this purpose, such as:
Google Search Console
Google Search Console (GSC) provides insights into how Google indexes your markup, quality improvements, and offers limited ROI reporting. Let’s dive into the feature within GSC that best helps you monitor and maintain Schema Markup.
Search Results Performance Report by Search Appearance
The Search Appearance dimension report in Google Search Console will show you the clicks, impressions, click-through rates, and ranking by rich result. You can dive deeper into each rich result to see which URLs are achieving it and how the URLs with rich results are performing.
There are some limitations when using GSC. Namely, their 1000-row user interface limitation. This impacts websites with a large number of pages and those that rank for a large volume of queries. Additionally, creating the complex groupings required for strong ROI reporting can be a challenge in the GSC’s UI. It can be hard to isolate URLs without the use of regular expressions and complex queries that look for specific patterns in a text string.
Schema Performance Analytics
The Schema App team created Schema Performance Analytics (SPA) for in-depth markup performance reporting. It combines the markup performance data from Google Search Console and the Schema App Highlighter and Editor, and gives users more filtering options to analyze their markup by page level or line of business.
Additionally, SPA’s Page Level Report is not limited to 1000 rows of data. Our team imports the entire set of metrics using Google Search Console’s API so you can analyze the entirety of your dataset with ease.
A recent addition to Schema Performance Analytics is the “Incremental Clicks from Rich Results” feature.
This feature divides the results for an individual URL into instances where a rich result was attained versus when it appeared solely as a standard blue link. It calculates distinct clicks, impressions, and CTR for each group.
By leveraging this data, we can assess the frequency of achieving a rich result, the percentage change in CTR when a rich result is achieved, and extrapolate insights into the additional clicks achieved due to the enhanced appearance. For further details, refer to this documentation.
You can combine these platforms and methods to get a well-rounded overview of your Schema Markup’s performance. By assessing its impact on your website’s performance, you can make informed decisions to optimize its implementation for better results.
You can learn how to calculate ROI from Schema Markup by reading this article.
When will I start to see the impact of Structured Data in organic search?
The timeline for observing results from structured data in organic search depends on your markup strategy and the result you want to achieve.
For rich result-eligible markup, the impact can be evident quite quickly as soon as Google indexes your markup. There are a few key steps that must occur in order to see results:
- Markup deployment: Your team’s changes to your markup are reflected in our system within 5 minutes of making changes in the Schema App Editor or Highlighter. If your website uses caching technology, it could take longer for the JSON-LD to appear in your rendered HTML. For more info, refer to this support document.
- Markup indexing: After deployment, Google needs to index the Markup, which depends on how frequently Google crawls your site. This point in the process is also when we may discover technical limitations preventing Google from seeing and using your markup. These discoveries could cause further delays.
- Google may begin awarding Search Features as soon as it indexes your results. The shortest time period for this is 2-3 days, but this process typically takes closer to a week or more.
When evaluating the impact of using structured data for semantic or entity-related objectives, it becomes more challenging to measure the direct impact of implementing Schema Markup. Over time, you may notice your page appearing on the SERP for more relevant keywords and observe an increase in click-through rates.
However, as per information from this Google SEO Starter Guide, these outcomes may take weeks or months to materialize. Unlike Rich Results, semantic efforts do not have a performance report filter in GSC. To report on results, we recommend a combination of approaches, including monitoring the SERP for key queries and in-depth data analysis on performance metrics.
How can we separate the impact of Schema Markup from other SEO initiatives?
Identifying the distinct impact of Schema Markup can be relatively straightforward because implementing Schema Markup is typically the primary method of achieving a rich result. However, there are exceptions, such as Merchant Listing Results, which can originate from markup or a Google Merchant Center account.
To separate the impact effectively, you can utilize Schema Performance Analytics tools like Page Level Analysis and Incremental Rich Result Clicks. However, in cases where other initiatives target the same group of URLs as the markup, isolating the direct impact becomes challenging.
There are, however, some strategies to consider:
- Clear Team Communication! To isolate the impact of Schema Markup from the work of your content team, it’s important to know what your team is working on that could impact results, including URLs, types of content and site improvements made, etc.
- Do A/B Testing or use control groups: Try to create equal groups of URLs with similar traffic volumes and formatting. You can use Schema Performance Analytics to compare the results over time between the experimental group (with Schema Markup) and the control group and assess any significant differences.
- Acknowledge Challenges: Sometimes, it might be challenging to completely isolate Schema Markup’s impact from other initiatives. SEO is a cross-functional industry, and accepting the reality that shared efforts lead to shared results may be necessary.
Supporting you on your Schema Markup journey
Understanding the significance of Schema Markup is crucial for optimizing website content and driving success in SEO, AI, and semantic search initiatives. Digital teams must understand and measure the impact of Schema Markup on their SEO goals to craft and implement an effective strategy tailored to their organization’s goals.
If you’re looking to develop and implement an advanced Schema Markup strategy at scale and build your knowledge graph, Schema App offers an end-to-end solution that combines our semantic Schema Markup platform with High Touch Support services to drive results. Contact our team to get started.
Ruby Ross is the Learning and Enablement Customer Success Manager at Schema App. She specializes in empowering Schema App customers to author structured data using the Schema.org ontology and deploy JSON-LD markup to their websites. Ruby is dedicated to providing professionals with the resources and support they need to succeed in both their careers and personal endeavors.