This document provides an overview of structured data and how to plan and implement it effectively. It discusses the giant global graph and semantic web concepts. Schema.org is introduced as a way to add structured data tags to pages. The benefits of structured data like improved rankings and user experience are outlined. The document then covers how to plan structured data by auditing pages, identifying appropriate schema types and properties. Implementation tips around templating, testing and monitoring structured data are provided. Common pitfalls to avoid are also highlighted.

1. Integrating
Structured Data
(to an SEO Plan)
for the Win
WTSWorkshop ‘23
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2. About Begüm
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SEO Specialist @ BK Solutions & The Gray Dot Company
🌍 Technical SEO From Turkey to Global Sphere
Google Business Profile Gold Product Expert
GDS, RegEx, Structured Data Enthusiast
Hreflang="tr", ”en" & “ja”
@begumkayaseo
/in/begum-kaya
PE Program
Opinionated SEO Opinions

3. The Agenda for
Today
On The Way to Smashing
Structured Data
1. A bit of theory
2. Schema and why we care
3. Planning and implementation
4. Tools to use
5. Reporting
6. Wrapping it up
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4. Giant Global Graph (GGG) is a name coined in 2007 by Tim
Berners-Lee.
It is the natural evolution of networking: from computer (net) to
documents (web) to things (and friends).
It describes information objects like web pages and attributes
the relationships that conceptually or semantically link the
information objects to each other.
Giant Global Graph and Semantic Web
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Semantic Web (also referred to as Web 3.0) aims to make internet data machine-readable.
This is achieved by creating a sound HTML structure (take a peek at W3Schools’ HTML Tutorials) and adding
differentiating metadata to the HTML code, identifying nodes and links.

5. The nodes represent objects or concepts
(entities) and the links represent relations
between nodes.
We want to be intentional about defining the
relationship between different objects, thus
use a controlled vocabulary.
How to think of nodes and links
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Entities are uniquely identifiable objects, places,
organizations, or people* with individual properties.
e.g. Paris isn’t an entity but Paris, France is
*any subject that can be attached to a
Wikipedia/Wikidata article
Controlled vocabulary provides a consistent way to
describe data. This way, we aim to improve
findability and send trust signals to attain higher
rankings.
e.g. if A is B, then there shouldn’t be any data a SE can
find that says B isn’t A.

6. Schema.org (often called schema) is a semantic
vocabulary of tags (or microdata) that you can add to
your HTML to improve the way search engines read
and represent your page in SERPs.
Google, Yahoo!, Microsoft and Yandex got together
to create, maintain, and promote schemas for
structured data on the Internet, on web pages, in
email messages, and beyond.
How is schema related & why do we care?
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Schema markup helps search engines to look and understand the “things” and
relationships in between that we state.

7. How schema helps to improve search experience
By using schema markup, you can:
● build meaningful relationships between entities (helps with
knowledge graph),
● help search engines better understand your website,
● give users relevant information in an easy to consume/find
way,
● control how a brand appears in SERPs (rich snippet, PAAs,
etc.),
● increase click-through rate by rich results,
● empower an intelligent, data-driven content hub strategy,
● increase visibility due to the improved relationship
statements,
● increase relevancy by stronger internal & external linking
opportunities & short-form links in SERPs
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8. 1 - Brand POV: Entity recognition and The Knowledge Graph
How to prove schema’s importance to prioritize
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9. 2 - Generic POV: Building rapport in SERPs and moving towards semantic
web
How to prove schema’s importance to prioritize
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10. 3 - Content and Innovation POV: Interconnectedness and beyond
How to prove schema’s importance to prioritize
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11. 1 - Audit and structure your schema
Planning and implementation
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12. Planning and Implementation
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Preferably
JSON-LD
What does Schema look like?
● Independent Schema
● @graph Representation
● Nested Schema
Example Schema Codes
Schema paths

13. Top Schema Types:
● Organization
● Website
● Product
● Article
● Review
● Breadcrumb
● Video
● Event
● Recipe
● Local Business
2 - Identify schema types and properties to use
Planning and implementation
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Top Schema Properties:
● about
● knowsAbout
● mentions
● sameAs
● @id
● inLanguage
● mainEntity
● Publisher
● subjectOf
● URL
Structured Data Features

14. 3 - QA and maintain structured data
Planning and implementation
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● Be consistent with the syntax
● Audit the templatized pages’ schema
● QA the schema and resolve errors prior to go
live
● Dynamically implement the schema if possible
● Monitor and compare the performance of pages
where schema is applied & not.
● Periodically check the guidelines
● Integrate AI for automation & consistency

15. 1) Wrong or unnecessary schema types being used, such as
● Article schema implemented on content that isn't newsworthy (use BlogPosting schema instead!)
● HowTo schema implemented on recipe pages instead of Recipe schema
● LocalBusiness schema left too generic, lacking specification (e.g. Restaurant)
2) Schema types implemented in the wrong places (site-wide vs. page-level) – e.g. Organization schema improperly deployed globally versus being
implemented only on the homepage as it should be.
3) Not correctly nesting parent/child relationships – e.g. Reviews/Ratings not appropriately nested under Product schema or on actual product
pages. Using Product schema on eComm category pages instead of properly using CollectionPage or ProductCollection schema.
4) General missed opportunities – e.g. parent schema types lacking specification (what type of LocalBusiness?) or not including adequate detail. Not
implementing FAQ Schema on product detail pages.
Source: How to Plan & Implement Schema Markup, Avoiding Common Mistakes
4 - Common pitfalls to be aware of
Planning and implementation
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16. ● Rich Results Testing Tool (RRT)
● Schema Validator - Secondary to RRT
● TGDC Schema Template
● Merkle Markup Generator
● Schema Builder for Structured Data
● OpenLink Structured Data Sniffer
● Classy Schema Visualization
Other tools for entities:
● Entity Checker
● HTML5 Validator
● Knowledge Graph Finder
Tools to test & improve your schema
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17. Reporting the schema outcomes would vary depending on the organizational level
of the people you’re presenting to. WordLift has a good formula for a business
level:
Monitoring and Reporting
Reporting of structured data
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18. Monitoring and Reporting
Reporting of structured data
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Use the following ideas for monitoring & reporting on SEO level:
1. Use CASE WHEN to sort queries/LPs in Looker Studio
a. Number of schema types ranking
b. Clicks, Impressions and CTR time series charts of schema types
2. Number of keywords & entities ranking
3. Traffic by schema type and traffic share analysis
a. Divide traffic by the total search volume/traffic expectation by page
4. GSC Search Appearance filters

19. 1. Understand schema is supporting entity
recognition & improves visibility
2. Plan schema types and properties,
keeping entities and relationships in
mind
3. Scale your efforts by templatizing the
schemas to be implemented
4. Employ various tools to validate, don’t
settle for one
5. Periodically review and keep your
schema up to date
6. Monitoring and reporting is vital, make
sure to differentiate by the audience
Wrapping it all
up, for the win!
Smash Structured Data
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20. THANK YOU
One of the most powerful
earthquakes ever recorded in Turkey
(7.8) struck on 6 February, followed
by a second earthquake with a
magnitude of 7.5 and it affected 13
million people living in the area.
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https://ahbap.org/disasters-turkey

21. Q & A @begumkayaseo
/in/begum-kaya
PE Program
Opinionated SEO Opinions