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Why You Need Schema to Optimize for Google’s Search Generative Experience

Mar 20, 2024   |   Schemas
Role of Schema in AI-Search

While Google’s Search Generative Experience (SGE) is imminent, the pertinent question arises: how can businesses optimize for search visibility in this new landscape? To start, it’s important to understand the current search trends and the measures your business needs to take to optimize your content.  Google emphasizes the paramount importance of content optimization for users, emphasizing the pillars of Experience, Expertise, Authority, and Trustworthiness (EEAT). In fact, Google’s March core update has been focused on content helpfulness.

Content must align with user intent in search queries and undergo refinement for entities through schema or structured data – highlighting the significance of entity optimization in the era of AI-driven search.

Pre-SGE, Benu Aggarwal, Milestone Inc’s President & Founder, wrote this article “Why entity search is your competitive advantage”, and the fundamentals mentioned in the article, with AI-Search, still hold. 

Why Schema will be instrumental in driving SGE Visibility

While the role of schema or structure data is questioned with the volatility in Google’s rich results of late – some being deprecated while others losing traffic – its role in driving the recognition of your content by search engines in AI-Search will be critical.

Quoting Google and covered by SEO roundtable as well, “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; for example, on a recipe page, what are the ingredients, the cooking time and temperature, the calories, and so on.”

Furthermore, Google has made advancements to the schema vocabulary, which gives us insight into the type of content it wishes to recognize with SGE.

Google is enhancing schema vocabulary

ProductGroup schema:

It’s important to note that eCommerce queries seem to be Google’s core focus in SGE, with a staggering 92% coverage as of July 30th, 2023 (an increase from 79% on July 1st, 2023)1. Google recently announced the  ProductGroup schema.  In their words, “Many types of products such as apparel, shoes, furniture, electronic devices, and luggage are sold in different variations (for example various sizes, colors, materials, or patterns). To help Google better understand which products are variations of the same parent product, use the ProductGroup class with associated properties variesBy, hasVariant, and productGroupID to group such variants together, in addition to Product structured data.”

Carousels (Beta)

In addition, they have released documentation for schema implementation of their beta-rich result – Carousels – which is more in line with the experience offered in their SGE. This rich result resembles a list, allowing users to horizontally scroll through various entities from a particular website, commonly referred to as a host carousel. Each tile within the carousel may display information sourced from your website, such as pricing, ratings, and images associated with the entities featured on the page.

An illustration of the Carousel rich result:

Carousels (Beta)

To qualify for participation in this beta program and potentially feature in the rich result, it is necessary to incorporate ItemList structured data alongside at least one supported structured data item from the following list:

  • LocalBusiness and its derivatives, such as Restaurant, Hotel, VacationRental
  • Product
  • Event

With Google’s focus on recognizing content using schema to deliver the most relevant result established. We’ll now show you how using schema has improved visibility in terms of rich results and universal search results for businesses.

Driving SGE Visibility & Rich Result Growth Using Schema

Let’s take a couple of examples of success stories of how Google is using schema to derive the most relevant answer to a query on SGE:

Example 1: The goal was to ensure the publisher gets their visibility on search and on the website of the author, we deployed NewsArticle Schema implemented nested with Author and Publisher with Organization.

As a result, SGE displayed the content + the rich result for a non-branded relevant search:

Example 2: For a certain product, we deployed Product schema nested with Organization using Provider Attribute

As a result, SGE displayed the product as a chatbot result for a non-branded query.

Post schema deployment, the business saw an exponential increase in rich result impressions and clicks. For the YOY comparison (2023 Vs. 2022) impressions grew by 193.7% while clicks grew by 94.8%.

Total Universal Results for the same period increased by an average of 51.2% with individual rich results such as Local Pack grew by 500%, Reviews by 40.7%, and Image by 105.5%.

What to remember when optimizing your content for AI-Search using schema

We’ve established that schema implementation to prepare your business for the era of AI-Search is an absolute must to have a competitive edge. However, while creating a perfect knowledge graph of your business with nested schema, there are a few considerations.

When deploying schema at scale, there are 3 phases – Pre-deployment, Deployment, and Post-deployment that businesses need to follow which is well documented in the article “How to deploy advanced schema at scale”.  The key takeaway is that while going through the process of schema deployment, you’re already readying your website with foundational SEO to meet all the right signals to rank on search.


  • Once you’ve identified your content topically that meets the intent of users which can be done using Content Intelligence – which helps you identify ‘what to write’ based on search trends data, traffic, competitor content ranking, etc., the next step is to deploy the right schema and map entities on your web pages to enable the search engine’s recognition of your content
  • Schema management is a cyclic process – URL Discovery, Deployment, Maintenance, Performance Analysis, Repeat!
  • Analyzing your performance post schema deployment is your signal for iteration to improve content visibility as rich results and general relevance to queries.

Using Milestone Schema Manager to streamline entity optimization

While schema deployment and management might seem like an enormous task, with Milestone Schema Manager, this process is streamlined – from URL discovery to deployments, maintenance & performance analysis – and at scale.

  • URL Discovery: Discover up to 1 million URLs in one go
  • Deployment: Point & click and auto-generate schema to deploy schema at scale
  • Maintenance: Real-time error and warnings notifications with content drift and updates notifications
  • Visualizer: See how we’ll you’ve mapped your schema or created a perfect nested schema architecture for each URL
  • Performance analysis: How well you’re performing on search as rich results, universal results, and the cost savings – organic visibility achieved just by deploying schema against opting for a paid campaign.


In the evolving landscape of AI-powered search, schema emerges as a cornerstone for enhancing content visibility and relevance. As search engines strive to deliver more personalized and insightful results with SGE in sight, leveraging schema becomes imperative for businesses aiming to stand out and gain a competitive edge in the digital realm.

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