To identify the most qualified attorneys, law firms and companies in each intellectual property sub-category, we apply a proprietary ranking methodology. This methodology acts as a framework for measuring activity, success and overall performance. Once all relevant data is collected, we use a custom algorithm to calculate a final score for each stakeholder. These scores form the basis of our rankings. This section outlines how those scores are determined.
Entity Name Resolution
Cleaning up entity names is one of the most challenging aspects of the ranking process. It requires a team of highly skilled engineers and data scientists, supported by powerful computational resources. The difficulty stems from the significant noise present in the raw data, which makes sorting and standardization a time-consuming and complex task. Accurate name resolution is essential, as companies and law firms often operate under various names, including subsidiaries and parent organizations, which can create confusion and inconsistencies in the data. Mergers and acquisitions further complicate matters by altering the size and activity of companies in ways that are not organic. In addition, filing errors can obscure the correct entity name, increasing the complexity of the process. For attorneys, the challenge is even greater. Similar or identical names, varying filing formats, and frequent moves between law firms make it difficult to confidently match records to the correct individual. Addressing these issues is critical to producing accurate, reliable rankings.
The Entity Name Resolution algorithm has been a key area of focus for the Patexia Data Science team for several years. While the algorithm is not yet perfect, we have made significant progress in improving its quality over time. Our approach combines advanced Natural Language Processing (NLP) techniques with Machine Learning algorithms, allowing us to continuously refine the accuracy and consistency of our data.
Defining and Measuring Important Qualities
In addition to ensuring a clean and accurate dataset, it is essential to identify and extract key parameters from the perspective of various stakeholders—namely corporations, trademark owners, trademark law firms, and individual attorneys. Our evaluation framework is built around four overarching factors, which form the foundation of our analysis:
- Activity – The number of registered trademarks obtained by the trademark owners, law firms or attorneys during the period of our study.
- Success – The process of getting the trademark registered successfully and efficiently.
- Performance – The overall quality of work performed by the attorney, or law firm (or the trademark owner) which is a function of both activity and success.
- Cost – The overall cost, including attorney’s fees and USPTO fees, for obtaining and maintaining the trademark.
We defined the Performance and Success for each of the stakeholders as a weighted average of the other factors. For example, we define the Performance Score of law firms or attorneys as:
Performance (law firm / attorney) = a1. Success + a2. Activity
Important Signals
To construct our model and calculate key parameters related to success and performance, the Patexia Data Science team extracted a wide range of signals from the raw trademark data. Prior to finalizing this report series, these signals were evaluated and validated through a survey conducted within the trademark community. Below are some of the core signals we identified and incorporated into our assessment:
- Activity Count – A count of the number of registered trademarks per trademark owner, attorney, or law firm for the period of the study.
- Applications Filed – The number of trademark applications filed during the period of the study.
- Applications Concluded – The sum of all trademark applications registered or abandoned during the period of the study.
- Registration Rate – The ratio of trademarks registered to all trademark applications concluded (either registered or abandoned) during the period of the study.
- Number of Office Actions – Average number of Office Actions per trademark application that was handled by the law firm or attorney during the period of study.
- Pendency – The number of days from the filing date to registration or abandonment date of the trademark application.
- Number of Time Extensions – The total number of times the attorney or law firm requested an extension of time per application
- Opposition – The total number of oppositions that the trademark attorney, law firm or the trademark owner has received for the entire portfolio during the period of the study.
We defined success as a weighted average of Registration rate, Office Actions and Oppositions. We are constantly adding new signals to improve our measurements and make them more relevant.
Normalization of Scores Using Regression Model
After calculating the initial Success and Performance Scores, we normalize them based on their deviation from the mean and scale the results to a 100-point percentage format. However, in order to accurately evaluate the success of an attorney, law firm, or company, it is critical to isolate their individual performance from external influences. To achieve this, we developed a regression model that adjusts for these external variables, allowing us to derive a more accurate and independent measure of success for each stakeholder.
This model quantifies the influence of various factors on an individual attorney’s, law firm’s, or company’s success or failure. For example, when assessing an attorney’s performance, we consider not only the success of the companies they represent but also the potential influence of the trademark examiners involved. Similarly, when evaluating a law firm, we account for the performance of their client companies and the examiners assigned to their cases. In the case of companies, our model considers the law firms and attorneys they work with, as well as the examiners reviewing their applications.
The application of this multifaceted approach has significantly improved the accuracy and fairness of our rankings. It enables us to provide our clients with deeper insights and a more objective representation of success in the trademark space. Through ongoing refinement of our methodology, we remain committed to delivering industry-leading, data-driven rankings that offer meaningful and actionable intelligence.
Scope of Analysis and Timeline
As noted earlier, our evaluation is based on a five-year period rather than a single year. This approach is grounded in several key considerations. Most notably, the trademark registration process often extends beyond one year, meaning a shorter timeframe would fail to capture the full arc of an attorney’s or law firm’s performance. Furthermore, annual fluctuations in workloads can distort year-over-year comparisons, making single-year data unreliable for assessing long-term success.
By extending the evaluation window to five years, we are able to identify meaningful trends and patterns across a larger and more stable dataset. This broader scope allows us to reduce the effect of anomalies or incomplete data for any given year and deliver a more accurate, consistent, and fair analysis of each stakeholder’s activity and success. The result is a ranking system that offers deeper insights and a clearer picture of long-term performance.
For this year’s report, we analyzed 2,738,833 trademark applications that reached a conclusion—either registered or refused—between January 1, 2020, and December 31, 2024. Due to the size of this dataset, we limited our performance evaluation to the top 10,000 most active companies, law firms, and attorneys. Entities ranked below this threshold were excluded from performance assessments to ensure the focus remained on those with sufficient activity to warrant meaningful analysis.
Data Sources
The data source used in this report is the USPTO Bulk Trademark Data, which is a comprehensive collection of XML files containing essential metadata of trademarks registered in the United States. The USPTO, being the primary agency responsible for granting patents and registering trademarks, maintains a rich collection of data that serves as a valuable resource for conducting empirical research and drawing meaningful insights. By utilizing this data, we were able to conduct a rigorous analysis of trademark activity, and provide valuable insights to our clients.
