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Seventh Circuit Likelihood of Confusion Factors

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Seventh Circuit Likelihood of Confusion Factors

Seventh Circuit Likelihood of Confusion Factors

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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 Seventh Circuit

The Seventh Circuit includes the following jurisdictions:

  • Central District of Illinois
  • Northern District of Illinois
  • Southern District of Illinois
  • Northern District of Indiana
  • Southern District of Indiana
  • Eastern District of Wisconsin
  • Western District of Wisconsin

The Seventh Circuit uses Seven Factors in considering likelihood of confusion cases:

  1. The similarity between the marks in appearance and suggestion
  2. The similarity of the products
  3. The area and manner of concurrent use
  4. The degree of care likely to be exercised by consumers
  5. The strength of the plaintiff’s mark
  6. Any evidence of actual confusion
  7. The intent of the defendant to palm off his product as that of another

Sorensen v. WD-40 Co., 792 F.3d 712, 726 (7th Cir. 2015).

Rhonda Harper MBA, Expert Witness

Serving the Seventh Circuit, Ms. Rhonda Harper has been retained for many filed in the Northern District of Illinois, the District of Illinois Eastern Division, and the Northern District of Indiana.

Retained by more than 140 law firms, Ms. Harper is courtroom proven in virtually every circuit along with JAMS and TTAB.  Her 30+ year career includes serving as a Fortune 100 chief marketing officer and an adjunct marketing professor. In addition to providing litigation consulting and research in the areas of business, licensing, marketing, advertising, in-store merchandising, and strategy, 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 the methodological pitfalls that can introduce bias or systematic error.

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