Category archives: SEO Case Studies

Local Business Schema Optimization Guide

A local business schema is a type of schema markup that provides structured data about a particular physical business or branch of an organization.

By implementing local business schema markup on a website, businesses can provide search engines with clear and consistent information about their business.

This can help search engines display accurate and relevant information and increase the business's visibility to potential customers in the local area.

LocalBusiness schema provides several benefits, including improved search engine visibility, increased click-through rates, consistent information, better customer experience, and a competitive advantage over larger, national brands.

By implementing a high quality and semantic local business schema, businesses can improve their online presence, attract more customers in their local area, and make informed decisions about whether to visit or contact the business.

Here is how to Improve your local business schema for better performance:

• Educate yourself about local business properties
• Avoid repeating the same local business schema on the same page
• Avoid repeating the same schema on every page
• Pick the right local business schema type
• If you can't find the right type for your local business, use additional type
• Link your local business schema with your Google Business Profile
• Utilize reviews and aggregate rating markup
• Use DefinedTerm to declare your keywords
• Use the hasOfferCatalog relation to add an OfferCatalog to your local business
• Use the knowsAbout property
• Use the address and areaServed fields correctly
• Use the brand property to showcase your brand
• Regularly monitor and update your schema
• Consider including a founder field
• Connect all your entities in one schema
• Remove the pre-existing schemas on the page
• Check your local business schema with rich result testing tools

Entity-based SEO is a method used by search engines to deliver the most relevant and accurate results to users by understanding the context and intent behind their searches. While machines can process phrases literally, they may not always grasp the nuances of language that humans do.

Its important to note that knowledge graphs and semantic quality are key concepts for semantic-based SEO because they help search engines understand the relationships between different entities and the meaning and context of a website's content. This can lead to improved search rankings, more accurate and useful search results, and a better search experience for users.

In this case study, I am going to demonstrate how entity-based SEO takes into account the relationships between entities and the context in which they are used to provide more meaningful search results.

This semantic SEO study is going to cover the followings:

• What is an entity?
• What is entity based SEO?
• What is the difference between SEO and entity-based SEO?
• What are entity types?
• Can an entity have more than one type?
• What are entity properties?
• Do I have to mark up all entities on the page?
• What are the important properties needed for interlinking in entity based SEO?
• How do you optimize your content for semantic SEO?
• What are semantic schema markups?
• Case Study: Semantic SEO Improves Search Engine Rankings and User Experience