The Best Trademark Lawyers in the US 2022 - 2024:

The first data-driven ranking based on millions of USPTO trademark application records

0. Executive Summary

Registering a trademark is an important first step for brand owners to claim ownership of their creations, build market awareness, and protect their brands. As the trademark authority in the world’s largest economy, the United States Patent and Trademark Office (USPTO) receives millions of applications to register trademarks each year. The majority of applications are diligent works submitted by attorneys practicing trademark law in the US. Therefore, it is worthwhile to identify the best attorneys for trademark registration.

While there are some publications on this subject [1-7], none of them are data-driven which applies big data analytical algorithms on the millions of USPTO trademark applications throughout the years and scores candidates according to their performance indicators.

As an AI-first company, Huski.ai possesses the industry’s largest knowledge graph for trademark law [8]. Accordingly, we depart from more traditional approaches to ranking lawyers [1-7] and take a fully-data driven approach, applying big data analytical algorithms to the millions of USPTO trademark applications throughout the years. We then score candidates according to a weighted index of objective performance metrics including registration success rate, office action response success rate, registration speed, total filings, and more.

We hereby report our findings along with all scoring metrics and the ranking methodology as detailed at the math equation level. This is the first of a series of research on attorney profiling and trademark insights discovery [9]. We hope the data-driven approach can inspire similar discussions in the industry and provide guidance for trademark related issues.

1. Introduction

Trademark prosecution data is well-regarded as a reliable indicator of economic performance, with a direct correlation between filing volume and economic prosperity [9, 10, 11]. The United States Patent and Trademark Office (USPTO) receives millions of trademark applications each year from applicants across the globe. Most of these applicants are good-faith brand owners that are represented by hard-working trademark attorneys who devote their careers to the protection of their clients’ intellectual property.

Some of these hard-working attorneys are recognized by industry awards such as “top attorney/law firm rankings in trademark law” [1-7], but despite thorough due diligence and explicit evaluation criteria, many existing publications rely on self- or peer-nomination, general reputation, and may be restricted behind paywalls or membership subscription fees. Nevertheless, rankings are a valuable tool for attorneys to be recognized for their work and demonstrate their value to colleagues, employers, and clients. But what if there were a way to rank attorneys based on objective, quantitative metrics?

At Huski.ai, data is our passion, and we believe in using our advanced artificial intelligence (AI) technology to unearth the treasure trove of valuable information that resides within trademark prosecution data and share our findings with our community. Being that the volume of data (millions of UPSTO trademark application records) is near impossible to process and analyze without the proper tools, we are proud to use our AI and big data technology to produce the industry’s first fully data-driven trademark attorney ranking.

2. Methodology

2.1. Data source

USPTO trademark application records are the sole data source for the scope of this project. We analyzed trademark applications from the past 10 years – about 5 million in total. This resulted in about 40,000 US trademark lawyers being considered for this ranking.

2.1.1. Inclusion/Exclusion Criteria

• Attorney must be US-licensed and in good standing with the USPTO.
• Attorney must have filed at least two applications to register in 2022.
• Attorney must represent at least one live trademark.
• Attorney must have filed more than 400 applications to register to date.
• Representation of China-domiciled applicants at the USPTO is a specialized area of focus which will be discussed in a future report. For inclusion in the present study, less than 70% of an attorney’s filing activity could be in representation of China-domiciled applicants.

2.2. Success Indicators

We have identified 7 unique indicators of attorney success across metrics related to filing activity, successful registrations, and the ability to avoid and overcome detrimental Office Actions.

The success indicators are described in the table below.

Term	Notation	Controls	Weight	Huski Index Score Calculation
Total Applications	Na	C0 = 1000	w1 = 0.1
The total number of applications filed by an attorney, capped at 1,000.
Total Registrations	Nr	C1 = 500	w2 = 0.1
The total number of trademarks registered by an attorney, capped at 500.
Registration Success Rate	Pr		w3 = 0.2
The proportion of successful registrations out of the total number of filings with a decision (i.e., total number of applications filed, less any pending applications).
Registration Processing Time	Tr	C2 = 500	w4 = 0.2
The average number of days it takes for an attorney to get a trademark registered with the USPTO, capped at 500. This is considered to be an indicator of attorney efficiency and is a metric that is very important for clients.
Office Actions Incurred Rate	Pi		w5 = 0.1
The rate at which an attorney receives detrimental Office Actions compared to the total number of applications they file.
Office Action Avoidance Rate	Pa		w6 = 0.1
The rate at which an attorney registers trademarks without incurring any detrimental Office Actions.
Office Action Survival Rate	Ps		w7 = 0.1
How frequently an attorney can overcome an Office Action and successfully register their client’s trademark.

2.3. Weighting (The Huski Index)

Individual success indicators do not paint a complete picture of the overall quality of a trademark attorney’s work performance. However, when considered together, a more holistic understanding is possible. Therefore, we propose the following equation to consider all 7 indicators together and produce a score between [0, 1]. Later, we normalized it to [0, 100]. We refer to this score as the Huski Index.

2.3.1. Huski Index Formula

where C₀ = 1000, C₁ = 500, C₂ = 500. These are the controlling constants to cap the values of certain terms. For example, the more trademarks you register, the more experienced you tend to be; however, the extra experience you gain becomes more and more marginalized as your applications accumulate.

w₁–w₇ are weights that sum to 1. They are to make sure Huski Index (H) is always within [0, 1].

The table below lists the values of the weight assignments that informed final rankings. Note that adjusting the weight assignment value can change the overall ranking, but to our findings, did not make a significant impact.

Per this equation, the higher the score, the better the attorney.

3. Results: The Top 50 Trademark Attorneys in the US 2022

View the full list of the top 50 attorneys>>

4. Limitations

While the goal of this study was to rank trademark attorneys using a fully data-driven approach, the approach is not foolproof or definitive. Relying solely on quantitative data for something as subjective as determining the “best” attorneys has its own inherent limitations. For example, leadership and scholarship in trademark prosecution may limit the amount of filing a particular attorney does. Throughout their careers, many talented trademark attorneys will pursue avenues such as professorship, government appointments, and more. Similarly, life circumstances may interrupt someone’s practice temporarily; for example: maternity or paternity leave or caring for a loved one affected by illness. It is very likely that there are excellent practitioners who have had to take temporary leaves of absence and were thus excluded from this list.

Other important limitations include law firm filing protocols and accommodating your clients’ wishes. First, at some firms, all attorneys file under one attorney’s name, such as all associates filing under a partner’s name. This can skew attorney of record data in favor of said partners and leaves us no way of acknowledging the associates whose hard work contributed to the overall success. The next limitation is the delicate balance of legal opinion and expertise and customer service. It is not uncommon for an attorney to advise a client against applying to register a particular mark, but the client wishes to proceed regardless. In fact, many attorneys will require their clients to acknowledge this in writing before proceeding to ensure full understanding. Relatedly, it may not be worth it to argue against an Office Action in this situation, and it may be in your client’s best interest to try again with a new mark. This will also affect rankings. Should attorneys who warn their clients against filing but agree to “try anyways” be penalized? No, not necessarily, but trademark application data cannot reflect these situations.

Finally, the available data does not allow us to specifically acknowledge the hard work of paralegals and other legal support staff who are often the backbone of trademark prosecution practices. Their hard work on initial searches, application preparation, and deadline management plays a huge part in attorneys’ success and happy client outcomes. While we don’t have the data to acknowledge these critical players, we do wish to acknowledge their work.

5. Conclusion

Despite these limitations, we still feel that this study provides valuable insight to the field, and we are excited to recognize and celebrate hard work. While we intend no criticism or condescension towards other rankings, we know that many are gatekept by requiring applications or subscription fees. As a result, many attorneys who spend less time on marketing themselves but work hard and achieve desirable outcomes for their clients can miss out on opportunities for recognition. Therefore, we are proud to serve the field with this entirely data-based study informed by a weighted index of seven different success indicators and hope that this work could be a stepping stone for future studies.

6. Acknowledgement

We want to thank USPTO for providing support to make their records accessible to the general public. We also want to thank Huski.ai’s engineering team for their extensive work on data preparation, cleaning, and visualization.

7. References