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Patent Monitoring

👉 Continuous tracking of patent data

🎙 IP Management Voice Episode: Patent Monitoring

What is patent monitoring?

Patent monitoring is based on patent information. Patent information refers to the technical knowledge contained in patent documents as well as all related legal and business-relevant data. Patent monitoring, also known as patent monitoring, is a process that serves to protect one’s own patent rights and increase one’s ability to innovate. Patent monitoring is important for innovative companies for the following reasons:

  • Avoidance of infringement of third-party rights
    Monitoring ensures that no patents are infringed that are already held by others.
  • Recognizing trends
    Trends in technology areas can be identified at an early stage, and this information can serve as a basis for your own strategic responses.
  • Competitor monitoring
    It is possible to monitor the technological activities of competitors and adjust their own strategy accordingly.
  • Timely detection of problematic competitor applications
    If a competitor files a patent that could affect its own business, an opposition can be filed in good time based on the information from the monitoring.
  • Detection of patent gaps
    Monitoring can be used to identify areas where you may want to apply for new patents yourself.

Patent monitoring can be divided into different areas:

  • Legal status monitoring
    In this case, the legal status of certain property rights is monitored. For example, the question of whether a particular patent application has been granted. Legal status monitoring is a convenient and cost-effective way to stay informed about the status and thus about the real effect of known IP applications.
  • Applicant surveillance
    This is mainly about the question of what competition does. Applicant monitoring not only provides property rights of directly known competitors, but also property rights of group companies, cooperation and project partners.
  • Technology field monitoring
    This allows you to keep an eye on developments in a technology field at all times. Monitoring specific CPC/IPC classes is one of the most common strategies in monitoring technology areas.

What is patent landscape analysis?

A patent landscape analysis is a strategic process that involves analyzing patent information to gain insights into the competitive environment, technological trends, and innovation potential within a particular industry or sector. This search is also called IP or patent mapping. The analysis can be used to identify trends, assess the competitive landscape, and inform decisions around product development and go-to-market strategies. This method can also be used to identify vacant areas in the patent landscape, the so-called white spots.

Patent landscaping can also be applied in the different phases of an innovation process. This can affect the idea orientation in the development phase in order to find technical solutions to problems.

The steps to perform a patent landscape analysis are:

  • Define research or knowledge goal
    Before starting the analysis, the actual goal, usually as a question, must be specified as precisely as possible.
  • Conduct a thorough patent search
    This involves using patent databases and search engines to conduct a thorough search for relevant patents. In this case, it may make sense to contact specialized experts for patent information.
  • Analyze and classify patent data
    Once a reasonably large number of patent documents and information have been collected, it is important to examine and organize the information.
  • Determine key patent trends and patterns
    The identified patent data is analyzed to find relevant trends and patterns.
  • Examine the quality and significance of the patent information
    The quality and relevance of the patent information found must be examined in relation to the original question.
  • Draw practical conclusions from the analysis
    The patent landscape analysis should be graphically prepared in order to gain useful insights and an overview.

What is patent analysis?

Patent analysis is based on the examination, preparation and presentation of patent information. Patent information refers to the technical, economic and legal knowledge contained in patent documents.

The patent information is based on the information stored in patent documents. A patent document usually consists of three parts:

  • the patent claims,
  • the patent description and
  • one or more drawings.

In addition, further information can be found on the cover page of the patent document, such as:

  • Title of the invention
  • Name of the inventor
  • Information about the applicant
  • Registration date
  • Date of publication and grant
  • Classification of the patent into patent classes
  • Countries where the patent has been applied for
  • Legal Representatives

In a patent analysis, all the information in the patent literature is used. Patent analysis refers to the collection and evaluation of patent information with the aim of making strategic use of the technical knowledge bound in patents.

Patent analysis can be used to observe competitor activities, to investigate interesting technology areas, to identify technology trends at an early stage and, through the analysis of one’s own and third-party patents, to be an important management tool for the realization of the freedom-to-operate (FTO)) of companies. The results of a patent analysis can help to make strategic decisions, such as resource investments regarding research and development.

Patent analysis, on the other hand, differs from patent monitoring in that the latter is a continuous process aimed at gathering up-to-date information about newly published patents and changes in patent status. It allows companies to stay up to date and react to new developments in a timely manner. Patent analysis, on the other hand, is a time-bound examination of the patent situation.

How do tools for patent monitoring and patent analysis differ?

Tools for patent analysis and patent monitoring have different focuses and serve different purposes:

Patent analysis tools

Focus on the collection and evaluation of patent information in order to strategically use the technical knowledge tied up in patents. They enable users to monitor competitor activities, investigate interesting technology areas, identify technology trends at an early stage and, by analysing their own patents as well as those of others, are an important management tool for realising the freedom-to-operate (FTO) of companies.

Patent monitoring tools

Focus on the continuous monitoring of patents and changes in the legal status of the patents. They allow users to gather up-to-date information about newly published patents and changes in patent status. They are important for ensuring the protection of one’s own patent rights, uncovering trends, monitoring the technological activities of competitors, detecting problematic competitor applications in good time, and identifying patent gaps.

How does AI improve patent analysis and monitoring?

Artificial intelligence (AI) has the potential to significantly change patent analysis and monitoring. Artificial intelligence (AI) is playing an increasingly important role in the use of patent information. Here are the key areas where AI is making an impact:

  • Increasing efficiency
    AI can help analyze large amounts of patent data more efficiently1. By using technologies such as machine learning, patterns and trends in the data can be identified that would be difficult for human analysts to detect.
  • Improving patent analysis
    AI models and methods, especially in core AI, such as neural networks and deep learning, can help improve patent analysis.
  • Supporting patent examiners
    AI tools and systems can be used to support patent examiners and improve the patent granting process.
  • Assignment of patent applications to technical fields
    AI can be helpful in assigning patent applications to technical fields or in cognitive searches in full-text areas.

For the patent analysis and patent monitoring use cases, the following effects can be distinguished:

Patent analysis

AI can help analyze large amounts of patent data more efficiently. By using technologies such as machine learning, patterns and trends in the data can be identified that would be difficult for human analysts to detect. In addition, AI models and methods, especially neural networks and deep learning, can help improve patent analysis and dramatically accelerate it. It is also possible to use cases that would not be economically feasible without the use of AI due to the amount of data and time required.

Patent monitoring

AI can also improve patent monitoring by helping to identify and track relevant patents more efficiently. AI tools and systems can be used to support patent examiners and improve the patent grant process. In addition, they can be helpful in assigning patent applications to technical fields or in cognitive searches in full texts.