Events
Event schema is used to mark up details about virtual or physical events, such as concerts, conferences, webinars or local meetups.
It provides specifics like the date, location, start and end times, ticket availability, and performers. This information can be included in Google’s event listings, enhancing visibility in local or event-related searches.
Newly supported properties for BroadcastEvent and ScreeningEvent enhance how live events and screenings are presented in search.
Dig deeper: How to deploy advanced schema at scale
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How to use structured data in 2025
While the applications below are not entirely new, their importance is set to increase through 2025 as user behaviors continue to shift.
Entity-based search
Entity-based search is where search engines prioritize entities – people, places, things and concepts – over individual keywords.
Instead of focusing on isolated words and relationships between them, search engines now better understand connections between entities and how they fit into a broader context.
Structured data like Person, Organization or Place schema can clearly define relevant entities, enhancing their visibility in Knowledge Graphs and entity-based results.
Likewsie, SameAs schema can be used to help search engines understand that an entity mentioned on one page is the same as an entity mentioned elsewhere.
By marking up an entity with SameAs and linking it to trusted external sources, such as Wikidata, Wikipedia or authoritative social media profiles, it’s possible to reinforce the association and improve its recognition and reach in Knowledge Graphs and rich search results.
Dig deeper: How to use entities in schema to improve Google’s understanding of your content
Speakable
Speakable schema (in beta at Google) is an important tool for optimizing content for voice search results.
It helps search engines identify which sections of a webpage are best suited for audio playback, including Google Assistant-enabled devices using TTS.
The goal is to provide concise, clear answers to users’ questions in spoken format. This is especially useful for news websites and publishers, as they can mark up critical content to be featured in voice responses.
Multimodal search
Multimodal search allows users to query search engines using various forms of input, such as text, images and voice, sometimes combined in a single query.
This is largely driven by AI models designed to process multiple data types simultaneously.
Structured data like VideoObject and ImageObject ensure that multimedia content is properly understood, indexed and ranked.
Schema nesting
Schema nesting allows for the representation of more complex relationships within structured data.
By nesting one schema type within another – such as a Product schema within an Offer schema, further nested within a LocalBusiness schema – it’s possible to communicate layered information about product availability, pricing and location.
This enables search engines to understand not just individual data points but how they are connected, leading to more contextually rich search results, like specific local availability and offers tied to individual businesses.
Another example might be a Recipe schema nested within a HowTo schema, further nested within a Person schema.
This communicates that a specific person (author or chef) created the recipe, which in turn contains step-by-step instructions on how to prepare the dish.
Person schema would include the chef’s name, bio and social profiles.
HowTo schema would describe the cooking process, including the steps and required materials.
Recipe schema provides details like the list of ingredients, preparation time and nutritional information.
This setup would enable search engines to display rich snippets that include the recipe’s creator, ingredients and cooking instructions in a clear and organized manner.
While the primary benefits of schema nesting include improved contextual understanding and enhanced rich results, nesting also adds flexibility for meeting different search intents, allowing search engines to prioritize information based on the query.
Maximize your search visibility with structured data
Structured data is already a critical driver of SEO success for many websites, both large and small.
With hundreds of schema types, dozens of Google SERP features and increasing applications in AI and voice search, its importance will only continue to grow in 2025.
As Google and other search platforms continue to change, carefully and creatively leveraged structured data can provide a significant competitive edge, allowing to gain visibility in existing features and prepare for future opportunities.
Dig deeper: How schema markup establishes trust and boosts information gain
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