With Fortune 500 experience as both a licensee and licensor, Ms. Harper knows a thing or two about licensing. This real world experience combined with years of experience providing licensing expert testimony can make all the difference to your case.
Licensing is a marketing practice in which a trademark owner allows another entity to license their mark in exchange for royalties. As a trademark owner, expert witness Ms. Harper has put together programs monitor the licensee’s actions related to the trademark, ensuring that the products provided by the licensee meet appropriate quality standards. If these measures aren't taken, the agreement may become a "naked license." Moreover, she may have lost the rights to the trademark if the licensee’s products failed to meet quality standards.
Licensing controls are required because consumers rely on trademarks to determine the source of a product. They rely on them in making purchases, since they trust a company that places a certain mark on its products to meet the standards associated with the mark. Failing to monitor the use of a trademark results in the loss of the trademark’s value in the marketplace. It no longer means anything about the products with which it is associated. This is sometimes known as the “abandonment” of a trademark.
Ms. Harper has opined in licensing cases involving:
Retained by more than 125 law firms, Ms. Rhonda Harper is courtroom proven in virtually every circuit along with JAMS and TTAB. Ms. Harper's 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, 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.