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AcclaimIP’s Quantitative Patent Score: A Guidepost to Patent Quality

One of the most popular features in AcclaimIP™ patent search and analytics software is our Patent Score, which we call the P-Score. This score ranks a patent by various statistical metrics that reflect its quality, allowing you to save hours of time in initial assessments. Within AcclaimIP, you will find the patent score shown for individual patents and also shown in reports such as the Annuity Decision Report.

Patents that rank high on the P-Score scale tend to be patents with a higher likelihood of being infringed, being used in a company’s products, or having current or future monetization potential.

The patent score comes into play essentially anytime you need to have insight into a patent’s quality, such as when making annuity decisions, assessing competitive patents, identifying licensing candidates, etc.  Additionally, you can chart the distribution of scores for different patent portfolios to assess the comparative strength of one portfolio to another.

How the AcclaimIP P-Score is Derived

Depending on how you define a “data point,” AcclaimIP uses from 30 to 30,000 data points to develop the patent score for each patent. To simplify the scoring concept, the P-Score is a weighted average of three contributing AcclaimIP component scores below, which are explained in detail later in this post: 

  • Patent Citation Score (C-Score) 
  • Patent Technical Score (T-Score) 
  • Patent Legal Score (L-Score) 

Each sub-score is calculated from several contributing factors, and each is included in the AcclaimIP interface so you can make better “at-a-glance” judgments on the statistical metrics that contributed to a patent’s score. 

Try sorting on a search result by the P-Score, and simultaneously view the other component scores to identify the areas in which the patent scored high and/or low, where it is statistically strong or weak. 

Figure 1: The AcclaimIP search results grid is both sortable and user defined, so you can view the various patent scores and sort by them

Normalization Method

The AcclaimIP team experimented with several methods to normalize the AcclaimIP patent score, but selected the method we believe is the most intuitive—and most useful. Basically, the three component parts of the full Patent Score (the C-Score, the T-Score, and the L-Score) are calculated and weighted, then compared to the rest of the patents in the system to create a percentage ranking as to where patents fall. 

Scores are then normalized from 00-99 corresponding to precise percentages. Therefore, if you have a patent that scores 99, you’ll know that it is a top “one percenter.” If your portfolio averages out to 50 or higher, you’ll know that your portfolio is above average. This way there is little guesswork on how your patents and portfolios stack up compared to the general population of patents. 

Which Data Points Contribute to AcclaimIP Patent Scores? 

Patent Citation Score 

A patent citation score is defined as the actual number of citations received in relation to the number expected given the age of that patent. You can imagine that two patents with the same number of forward citations could be ranked quite differently. There are lots of ways to tease out what makes a quality citation profile, which includes far more than just raw citation counts. This can include, but is not limited to: 

  • Cited by highly-cited patents 
  • Examiner citations 
  • Co-pending citations 
  • Citations that are a result of a forward 102 argument (that is, directly blocking someone else’s claims) 
  • Citations that are a result of a forward 103 argument (that is, used in an obviousness argument) 
  • Age weighted citation rate

 AcclaimIP Patent Citation Score (C-Score) 

AcclaimIP’s Patent Citation Score also includes citations to the simple family. Until your patent is published, your patent cannot receive any direct citations. But the family may have 20 or more citations. These citations can lead to unintentional infringement because the potentially infringing party may not have known about your un-published prior art when they made the decision to use the technology in their products. 

Figure 2: Citation visualization on AcclaimIP reports allow you to quickly pinpoint the important citation information.

AcclaimIP Patent Technology Score (T-Score) 

AcclaimIP’s patent technology score, or T-Score, does not score a patent directly, but rather scores the CPC classifications (technology classes) in which your patent is classified. We use statistics to determine which classes are strong and which are relatively weak. A strong classification is one that scores highly in each of the areas below: 

  • Growth of class 
  • Renewal rate of class 
  • Transaction rate of class 
  • Allowance rate of class 

The T-Score algorithm accounts for the hierarchical nature of the CPC class system, otherwise it would not work, since a parent class may have little activity when all the “action” is pushed down to its child classes. 

If a patent is classified in a class that is growing, with a high maintenance rate, with lots of recorded transactions or company acquisitions, AcclaimIP assumes that it covers a strong technology, and it then impacts the technical component of the patent’s P-Score. 

AcclaimIP Patent Legal Score (L-Score) 

The legal component is composed of several metrics that are indicative of a patent’s strength including the following measurements: 

  • Pendency (time between file date and grant date) 
  • Length of independent claims 
  • Number of claims 
  • Number of office actions 
  • Family size 
  • Remaining life

What is a Patent Metric? 

A patent metric is any quantitative data point (a number) associated with a patent. Metrics can relate to anything as long as it can be quantitatively measured. 

I like to break up patent metrics into two categories: 

  1. Those that apply to an individual patent
  2. Those that apply to a set of patents

For example, on an individual patent, the number of inventors can be explicitly measured, the pendency (in days) of the prosecution, the number of family members, the number of reverse citations, the number of office actions, number of examiner citations, the number of figures, the length of claims, the number of forward rejections… and the list goes on and on. 

Further metrics from a set of patents in the patent corpus at large can be measured and applied to a patent sharing characteristics of the set. 

For example, allowance rates, maintenance rates, growth rates and transaction rates can all be applied to patent classifications. In turn, each patent can inherit some quantitative measure based on the classifications in which it was assigned. 

How to Use and Interpret Patent Scoring Systems

Clearly the AcclaimIP P-Score is not something that is pulled out of thin air, but rather a result of a careful study of the academic literature, and years of experimenting with regression testing to confirm the metrics are indicative of a patent’s quality. 

Of course, there are outliers. A patent with characteristics of a quality patent can be useless, and, conversely, a patent with poor quality metrics can be outstanding, but these are the exceptions and not the rule. 

If you want 100% confidence that your scoring is accurate, you must read every patent and file wrapper, and make judgments to the quality in context of the problem that the patent may help solve. There is no way around that. 

Use the Patent Score as a Guidepost 

Nonetheless, patent scoring systems are valuable, because they focus the researcher on those patents that are most likely to be useful or important to the searcher. 

Scores also clue you in on what happened during prosecution. Let’s say you have a patent where the first independent claim was narrowed by 100 words. Immediately you should know that what the applicant filed and what was granted are quite different, and surely some investigation is required. Another example might be a patent that received a blind citation to your patent by an examiner making a 102-novelty argument. Clearly cases like these are great indicators of potential infringement. These important cases are reflected in the P-Score. 

Personally, I like to expose all four scores in my search results grids. Let’s say I have a patent whose score profile looks like this: 

Figure 3: Overall, it gets a high score, but you can see the primary contribution is from the citation score. The legal component and technology component are below average.

Querying Patent Scores 

Each of the four AcclaimIP scoring metrics can be queried using advanced syntax in our software.  Each score has its own easy-to-remember field code: 

  • PSCORE  –>  queries the Patent Score field 
  • CSCORE  –>  queries the Citation Score field 
  • LSCORE  –>  queries the Legal Score field 
  • TSCORE  –>  queries the Technology Score field 

Each field code supports a number from 0-99 or range queries.  For example: 

…AND PSCORE:[80-99] –>  Finds patents with a P-Score between 80-99, inclusive. 

Evolution of the AcclaimIP Patent Scores

I’d like to conclude this article by letting you know that the AcclaimIP scoring system is designed to be agile and improved as we learn more, add more data to the system, and get feedback from our users. Please weigh in, point out outliers, or suggest a new visualization, so we can continue to improve the scoring metrics and your reporting capabilities. 

Written by Matt Troyer, AcclaimIP Senior Director, Product & Innovation


Learn more: Patent Landscaping: Uncovering Strategic Insights


Categories: Patent Evaluation

Tags: patent scoring

Series: Patent Insights