Descriptive marks are not ordinarily protectable as trademarks. If they have acquired a secondary meaning, however, they may be able to be protected. Secondary meaning is achieved when relevant consumers come to identify a mark with a certain product or service over time. When this happens, a descriptive mark that a business would not have been able to register initially, because it related to the class of products and not the specific brand, may achieve protected trademark status.
Although each of the eleven circuits have formulated some version of a multi factor test to assess whether a mark has acquired secondary meaning, the Federal Circuit has clarified its own test, identifying the following factors that should be “weighed together”:
If your case involves a trademark that has possibly achieved secondary meaning, HLCR's trademark survey expertise may be the difference in winning and losing. Survey evidence is a common way of proving secondary meaning, a crucial step in trademark litigation. Specifically, a secondary meaning survey typically seeks to assess whether relevant consumers associate a trademark or trade dress with a single source. If relevant consumers associate the mark with a single source (rather than associating the mark with the class of products as a whole), this provides strong evidence that the mark has acquired secondary meaning.
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.