“Cannabis trademarks represent the new frontier in the legal brand clearance process.”
In our last installment, we put a critical eye to COVFEFE as a potential brand and attempted to deconstruct it in terms of potential meaning. In this installment, we’ll look at how COVFEFE would have fared had it been cleared as a potential brand in the fashion and food/beverage industries.
Using our visualization tool, Corsearch FOCUS™, which determines phonetic and appearance-based similarity and relevancy algorithmically, let’s look at the preliminary clearance patterns for COVFEFE in the clothing and luxury goods industry. Corsearch FOCUS plots the mark on a radar-like visualization, giving an aerial view to pinpoint the most relevant data.
Interesting marks often come from unexpected places. Take the recent “COVFEFE” craze, based on an apparent typo in a tweet early May 31, 2017 by a certain “high profile” individual. In less than two weeks, there are now about 40 COVFEFE trademark applications filed worldwide, thousands of domains registered, and untold numbers of social media hits still happening around the clock.
Corsearch’s GeoMapping feature shows where known marks containing the term COVFEFE are currently filed throughout the world:
The COVFEFE mark is rapidly seizing the globe like a game of Risk®. We’re going to ignore COVFEFE’s humble origins for now and take a look at it from a pure “brand” perspective.
Let’s face it—poring through data is tedious. People who have jobs where they have to comb through long linear lists of data—like trademark practitioners—endure hours of intense, painstaking work.
Data on its own doesn’t provide insights—it’s the way it’s gathered, organized, analyzed, and presented that gives it value. Whether it’s sports statistics, sales figures, or trademark registrations, data tells a story. Today, more and more organizations are using data visualization to tell their stories.
The human brain processes visuals 60,000 times faster than text and it’s more accustomed to processing images since most of the information that’s sent to our brains is visual. So it should come as no surprise that we’re able to make sense of data faster from an image.
Back in late 2016, the US Food and Drug Administration (FDA) released a new version of the Phonetic and Orthographic Computer Analysis (POCA) program called POCA 4.0. For those of us in the pharmaceutical trademark clearance and/or branding industries, this sounded like a good thing.
Program version updates come with the expectation of improvement. The original POCA was released years ago, and while not perfect, it remains the pharma industry standard in terms of ranking pharmaceutical marks on name safety similarity to a proposed candidate. POCA isn’t a definitive tool, and it’s just one of many methods and tools in the FDA’s arsenal for determining name safety issues in the pharmaceutical industry.
The POCA 4.0 algorithm has indeed been dramatically changed from the original pre-4.0 version. According to the FDA, the orthographic component of the POCA algorithm was revised to better capture errors that are being reported due to the increased use of electronic prescribing. The algorithm has been revised to put more emphasis on the similarity that occurs at the beginning of a name — especially the first three letters and on exact letter matches — and also to emphasize where names share letters that are not consecutive.
The title says it all. This is a blog about trademarks and brands, expanding the expertise and resources you’ve come to expect from Corsearch. From expert research tips to the inside scoop on productivity solutions, join the conversation about trademarks and brands.
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