Learn Practical Patent Analysis: A Case Study (Installment 4)

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Patent assignee data is a goldmine for conducting competitive intelligence. Want to know who the big players in a technology sector are? Follow the patent breadcrumb trail of patent assignee data. Researching and presenting company data is an important facet of patent analysis projects and may help interested parties understand where licensing opportunities exist. Today we’ll show you how to use different analyzation methods to find relevant companies in our chosen technology area.

Last time, in Learn Practical Patent Analysis: A Case Study (Installment 3), we discussed how classification analysis can inform a patent analysis project by narrowing the focus of the analyst and eliminating extraneous results. We ended up with a set of 1786 patent families focused on solar panels in the Mechanical Engineering specific IPC classes.

The patent assignee field on the face of a published patent indicates who had the rights to the patent at the time the patent was published. Most assignees are companies in one form or another (except for in the case of solo inventors). Intellogist has a great best practices article on assignment searching that is a must read for learning general assignee searching strategies. This best practices article is a wiki page, so feel free to sign up (for free) on Intellogist and contribute your suggestions to add to our community’s knowledge pool and show your expertise. This blog post will focus on how we can use a couple of these strategies through the prism of our case study.

To start we can do a simple assignee frequency analysis of our 1786 patent families—like our previous classification analysis, this can be done in many advanced patent search systems as simple statistical analysis. Doing so reveals the following top three assignees:

  • NASA– 16 hits
  • Exxon Research Engineering Co– 9 hits
  • Owens Illinois Inc – 9 hits

First we should ask ourselves: Does this data make sense? This is always a good “Vice President of Common Sense” move to execute during a patent analysis project. NASA and Exxon are well known and make sense as frequent assignees. What’s Owens Illinois Inc? To those unfamiliar, a quick Google search will reveal that they are a glass-making company that used to be listed in the S&P 500. It makes sense that they may have some patents related to glass surfaces or housings related to solar panels. At this point it may be a good idea to analyze a full list of popular patent assignees and check with the client to determine which companies should bear the brunt of the focus. Possible detailed analysis may include accessing financial data and shareholder reports to determine if an assignee is increasing or decreasing research and development funding or even if an assignee is a prime acquisition target.

At this stage it is important to note that there may be latent corporate subsidiary and hierarchical data that is obscuring our picture of the patent assignee landscape. Perhaps the 6th and 10th assignees are owned by the same parent company and once combined for statistical purposes would jump into the top three assignees. Good sources for corporate tree/hierarchy data include The Directory of Corporate Affiliations (DCA) (available on TotalPatent among other sources and produced by LexisNexis) and 1790 Analytics (which is partnered with Delphion). For more information on corporate trees, see our glossary entry on the topic.

One interesting aspect the assignee statistical analysis reveals is that the landscape of assignees is very broad with no dominating presence. This may be a sign that our patent data set is flawed, perhaps too broad, and at this point it would be wise to try to narrow our patent data set in an alternate way and see if we reach the same conclusions about assignee data. At worst, we would confirm the data and be more secure in making such an assessment.

Looking through another lens, it can be useful to compare assignees and filing date on the same graph. Doing such an analysis with our case study data reveals that NASA and Owens’ filings are largely from the 70’s! To focus solely on them at the suggestion of the assignee study alone would have left us with less relevant and dated patent documents. On the other hand, Solar Heat and Power PTY LTD is revealed as a 21st century player and worthy of a second look. Here’s an example chart, an equivalent of which can be generated in many patent search systems:

Example Assignee vs Publication Year Chart

An example of a simple chart that can help us identify assignee trends.

Assignee analysis is a detailed and nuanced technique—we haven’t even touched on missing assignment data, multiple name variants, or re-assignments! To get details on these problems and possible solutions/work-arounds, see the aforementioned Intellogist Assignment Best Practices article.

What is your favorite assignee analysis technique? What corporate tree/directory provider to you prefer? Let us know in the comments below.

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Patent Analysis from Landon IP

This post was contributed by Intellogist Team members Dan Wolka and Chris Jagalla.


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