Tenth Circuit Likelihood of Confusion Factors
Tenth Circuit Likelihood of Confusion Factors
Get the expertise you need plus the experience you want.
Each of the thirteen federal courts of appeal have their own test for evaluating whether a likelihood of confusion exists between two trademarks. Although the tests are not identical, most of them are substantially similar and use many of the same factors. And, the factors are non-exclusive.
The Tenth Circuit
The Tenth Circuit includes the following jurisdictions:
- District of Colorado
- District of Kansas
- District of New Mexico
- Eastern District of Oklahoma
- Northern District of Oklahoma
- Western District of Oklahoma
- District of Utah
- District of Wyoming
The Tenth Circuit uses the Six Factors in likelihood of confusion cases:
- The degree of similarity between the marks
- The intent of the alleged infringer in using the mark
- Evidence of actual confusion
- Similarity of products and manner of marketing
- The degree of care likely to be exercised by purchasers
- The strength or weakness of the mark
Rhonda Harper MBA, Likelihood of Confusion Survey Expert, Expert Witness
In the Tenth Circuit, Ms. Harper has been engaged twice in the District of Colorado, Denver.
Retained by 100+ law firms since 2005, Ms. Harper is courtroom proven. She has been engaged to provide 65+ surveys, 80+ reports, 30+ rebuttals, 45+ depositions, and serve in 20+ trials. She has provided services to both Plaintiffs (60%) and Defendants (40%) across trademark and trade dress, packaging, merchandising, defamation, licensing, breach of contract, advertising, and commercial reasonableness. She has provided services in virtually every Circuit as well as JAMS and TTAB.
Ms. Harper's 30+ year career includes serving as a Fortune 100 Chief Marketing Officer. Having authored two books, she is a former Adjunct MBA Marketing Professor.
Ms. Harper is routinely retained to formulate expert surveys, conduct rebuttal critiques, or construct rebuttal surveys to show the potential difference in results with properly designed and executed surveys. She has extensive experience and a deep understanding of survey design, sampling, question construction, data analysis, and methodological pitfalls that introduce bias or systematic error.
