WIPO eTutorial on Patent Analytics (DL178)

This self-paced e-tutorial introduces the fundamentals of patent analytics and demonstrates how patent data can be transformed into actionable insights for innovation, research, business, and policy decision-making. Learners explore the key stages of the patent analytics workflow, from data collection and analysis to visualization and reporting.
Duration: 6 Hour(s)
Not Tutored
Certificate
Course admin: DL178e.academy@wipo.int
1418 Registrations
animation
training-image
DL178E26S2
REGISTER NOW
Registration dates:
09-Sep-2026 to 01-Dec-2026
Training date:
19-Oct-2026 to 07-Dec-2026
Register now

Welcome to Patent Analytics, a self-paced e-tutorial that explores how patent information can be transformed into meaningful insight through structured analysis, visualizations, and clear narrative.

The course follows the patent analytics workflow from start to finish. You will begin by exploring what patents are and how patent documents are structured, before looking at why patent analytics matters and how it supports different policy, research, business, and innovation objectives. You will then learn how to define your data needs, search patent databases, obtain relevant data, clean and structure datasets, analyze trends and patterns, and communicate findings through reports, presentations, and visual stories.

Throughout the course, you will work with practical examples and tools such as PATENTSCOPE, Excel, OpenRefine, Flourish, Datawrapper, and PowerPoint. Interactive exercises and knowledge-check questions will help you test your understanding as you move through the modules.

By the end of the course, you should have a clear understanding of the full patent analytics process—and the confidence to begin applying it in your own context, using tools and approaches that match your objectives, your data, and your audience.

To support learning in this course and maximize learning experience, learners are expected to have foundational knowledge of patents and patent information.

It is recommended to complete the DL170 – Specialized Course on the Essentials of Patents and DL177 – e-Tutorial on Using Patent Information courses prior to taking this course.

This self-paced e-tutorial introduces the fundamentals of patent analytics and demonstrates how patent data can be transformed into actionable insights for innovation, research, business, and policy decision-making. Learners explore the key stages of the patent analytics workflow, from data collection and analysis to visualization and reporting. 

This e-tutorial is ideal for anyone interested in applying patent analytics in their work. It is especially useful for:

  • Technology and Innovation Support Center (TISC) Staff
  • Patent Professionals
  • Intellectual Property Managers
  • Researchers
  • Inventors
  • Intellectual Property Intensive Small Medium Enterprises (SMEs).

Register via the WIPO Academy platform.

This course is free of charge, there are no registration or tuition fees.

No document required.
Course overview
schedule
20 Minute(s)

This module introduces the foundations of patents—what they protect, how patent documents are structured, and why they provide valuable technical, legal, and commercial information for analysis.

Learning Outcome

By the end of this module, you will be able to: 

  1. Define what a patent is and explain its purpose.
  2. Identify the core requirements for patentability, including novelty, inventive step, and industrial application.
  3. Describe the structure and main data fields of a patent document.
  4. Interpret key information in patent documents, such as dates, numbers, and patent family relationships.
  5. Recognize the value of patents as sources of technical, legal, and commercial information.

This module introduces the foundations of patents—what they protect, how patent documents are structured, and why they provide valuable technical, legal, and commercial information for analysis.

Learning Outcome

By the end of this module, you will be able to: 

  1. Define what a patent is and explain its purpose.
  2. Identify the core requirements for patentability, including novelty, inventive step, and industrial application.
  3. Describe the structure and main data fields of a patent document.
  4. Interpret key information in patent documents, such as dates, numbers, and patent family relationships.
  5. Recognize the value of patents as sources of technical, legal, and commercial information.
schedule
25 Minute(s)

This module explains how patent analytics transforms patent information into meaningful insights that support decision-making across different innovation, business, policy, and research contexts.

Learning Outcome

By the end of this module, you will be able to: 

  1. Explain the strategic purpose and benefits of patent analytics.
  2. Identify different motivations and objectives for conducting patent analysis.
  3. Match specific patent search types to given business or innovation scenarios.
  4. Describe the types of analyses and reports produced from patent data.
  5. Recognize best practices for presenting patent analytics to support decision-making.

This module explains how patent analytics transforms patent information into meaningful insights that support decision-making across different innovation, business, policy, and research contexts.

Learning Outcome

By the end of this module, you will be able to: 

  1. Explain the strategic purpose and benefits of patent analytics.
  2. Identify different motivations and objectives for conducting patent analysis.
  3. Match specific patent search types to given business or innovation scenarios.
  4. Describe the types of analyses and reports produced from patent data.
  5. Recognize best practices for presenting patent analytics to support decision-making.
schedule
45 Minute(s)

This module guides you through the process of defining your data needs, identifying suitable patent data sources, building search strategies, and downloading patent data for further analysis.

Learning Outcome

By the end of this module, you will be able to: 

  1. Describe the main stages of the patent analysis process.
  2. Formulate and refine the scope of a patent data search based on an analytical objective.
  3. Identify key sources of patent data.
  4. Apply basic patent search strategies to retrieve relevant data.
  5. Construct search queries using keywords, classifications, and Boolean operators.
  6. Refine search queries to improve the relevance of results.
  7. Download patent data for further analysis and reporting.

This module guides you through the process of defining your data needs, identifying suitable patent data sources, building search strategies, and downloading patent data for further analysis.

Learning Outcome

By the end of this module, you will be able to: 

  1. Describe the main stages of the patent analysis process.
  2. Formulate and refine the scope of a patent data search based on an analytical objective.
  3. Identify key sources of patent data.
  4. Apply basic patent search strategies to retrieve relevant data.
  5. Construct search queries using keywords, classifications, and Boolean operators.
  6. Refine search queries to improve the relevance of results.
  7. Download patent data for further analysis and reporting.
schedule
2.5 Hour(s)

This module focuses on preparing raw patent data for analysis by identifying common data quality issues and applying practical techniques to clean, structure, and standardize datasets using tools such as Excel and OpenRefine.

Learning Outcome

By the end of this module, you will be able to:

  1. Describe why data cleaning is essential for analysis
  2. Apply data cleaning techniques using Excel
  3. Apply data cleaning techniques using OpenRefine
  4. Identify and structure concatenated data fields
  5. Explain the different formats found in different datasets

This module focuses on preparing raw patent data for analysis by identifying common data quality issues and applying practical techniques to clean, structure, and standardize datasets using tools such as Excel and OpenRefine.

Learning Outcome

By the end of this module, you will be able to:

  1. Describe why data cleaning is essential for analysis
  2. Apply data cleaning techniques using Excel
  3. Apply data cleaning techniques using OpenRefine
  4. Identify and structure concatenated data fields
  5. Explain the different formats found in different datasets
schedule
2 Hour(s)

This module shows how to analyze cleaned patent data, identify trends and geographical patterns, and present results through clear visualizations that support interpretation and communication.

Learning Outcome

By the end of this module, you will be able to: 

  1. Apply simple frequency counts to analyze patent data
  2. Select appropriate visualization types for different kinds of data
  3. Prepare patent data for trend analysis using publication years and patent counts
  4. Create basic visualizations to show patent trends over time
  5. Prepare patent data to analyze first-filing offices as a proxy for geographical origin
  6. Create basic visualizations to compare patent activity by geographical origin

This module shows how to analyze cleaned patent data, identify trends and geographical patterns, and present results through clear visualizations that support interpretation and communication.

Learning Outcome

By the end of this module, you will be able to: 

  1. Apply simple frequency counts to analyze patent data
  2. Select appropriate visualization types for different kinds of data
  3. Prepare patent data for trend analysis using publication years and patent counts
  4. Create basic visualizations to show patent trends over time
  5. Prepare patent data to analyze first-filing offices as a proxy for geographical origin
  6. Create basic visualizations to compare patent activity by geographical origin
schedule
75 Minute(s)

This module brings the patent analytics process together by showing how to prepare, present, and share findings through structured reports, presentations, interactive stories, and other communication formats, while also considering future directions such as AI-powered tools.

Learning Outcome

By the end of this module, you will be able to: 

  1. Identify the main considerations for preparing a patent analytics report tailored to a specific audience.
  2. Describe the essential components that constitute a comprehensive patent analytics report.
  3. Explain the role of presentations, visual narratives, dashboards, or other storytelling formats in effectively communicating patent analytics findings.
  4. Utilize Flourish stories to create patent data visualizations accompanied by a coherent narrative.
  5. Discuss the integration of AI-powered tools in various stages of the patent analytics process, while emphasizing the analyst's role in guiding, interpreting, and validating outcomes.

This module brings the patent analytics process together by showing how to prepare, present, and share findings through structured reports, presentations, interactive stories, and other communication formats, while also considering future directions such as AI-powered tools.

Learning Outcome

By the end of this module, you will be able to: 

  1. Identify the main considerations for preparing a patent analytics report tailored to a specific audience.
  2. Describe the essential components that constitute a comprehensive patent analytics report.
  3. Explain the role of presentations, visual narratives, dashboards, or other storytelling formats in effectively communicating patent analytics findings.
  4. Utilize Flourish stories to create patent data visualizations accompanied by a coherent narrative.
  5. Discuss the integration of AI-powered tools in various stages of the patent analytics process, while emphasizing the analyst's role in guiding, interpreting, and validating outcomes.
certificate

This course does not have an exam. View all modules and complete the required activities to earn your certificate of completion. 

chatbot clickable icon