Others might give you a patent number and Title, or cut & paste Abstracts from a Patent Office, or provide a machine generated custom Abstract.  All of these approaches leave plenty of work for the potential licensee.

IPmart’s first step: prepare a readable, digestible Summary of the technology.  Our Summaries are written by experts that understand the patent’s field of technology, understand patents and can communicate their knowledge.  Our goal is moving a potential licensee closer to understanding the technology and patent.  This is already more than others provide.  But, IPmart does not stop there.

As we write a Summary we create a “Framework”; an intangible scaffolding for further understanding.  One output is our Technology Tree, a schematic representation of where the patent fits with respect to its technology neighbours.  It is front and centre.  Look for the tree icon and quickly visualize a patent’s place in the world.  Again, we strive to make a patent understandable.

The Framework also allows us to build context around a patent.  IPmart looks around to see what is currently happening in the patent’s technology space. Are there alternate approaches to solving the problem? Are there other problems that might be addressed by the technology?  These questions; this type of information adds perspective, putting the technology in context.

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today’s baseline

The patent analytics vendors represent today’s baseline. They make valuation look easy and are often seen as the go to valuation source. Simply move the cursor over a “flag” in a patent landscape and a value for that patent appears. It is quick and it appears convincing because the process outputs a very specific number. Right or wrong the number sticks in your head.

Generally, they use a large equation that weights all sorts of data associated with a patent. This might include the number of citations, the word count of the Description, the word count of the Claims, the Inventor, filing trends in Classification Codes etc. It is all very complicated, but the power of data makes quick work of the task and a value pops out. But, is valuation that simple? Is the value all there in the data, ready for extraction?

the example

In the summer of 2022 I consumed marketing literature from one of these patent analytics vendors. More specifically, it was a brochure discussing how their services provide insights into the semiconductor industry. Nice, a field I know quite well. One table presented a well known integrated semiconductor manufacturer’s five most valuable patents. The second patent in this table was assigned a very precise value of $11,970,000. The table also indicated the patent would be alive for two years from that time i.e. it would expire in 2024.


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