As seen on Forbes
By Kathleen Lucente
Cloud-based solutions. Big data. Network-centric.
Do these terms sound familiar? They should because there are very few tech verticals in which companies are truly differentiating themselves with language. In fact, most of it fills a reader with a preconceived notion of what a company is or what its products do.
In every industry, there are trendy terms marketing executives devise to separate themselves from the competition. While those words are initially used accurately for sharp, effective communication, they soon become ubiquitous, “must have” marketing words that saturate the market. What was once a contextual differentiator has become clickbait that caters to a particular audience’s expectations. The end result is a word or phrase that’s become a shadow of itself, overzealously used and meaningless.
In just the last couple years, we’ve entered a climate in which “artificial intelligence” has become overused and been rendered useless as a term. In response, companies swiftly swapped it out for “machine learning,” which is not interchangeable with artificial intelligence, and yet is used as a synonym.
Credit card companies and other financial services organizations have been using the term “machine learning” to describe the use of technology to identify human behavioral patterns. It’s not the new kid on the block like many people think. It’s the old guy with a receding hairline sitting on his porch sipping a beer, laughing at the new kid on the block for calling machine learning the “hot new trend.” (As a side note, machine learning actually uses technology known as neural networks, a term that has been relegated to pariah status by 20th-century overexposure.)
I find myself grimacing when I see “machine learning” forced into a press release like a parent forcing his kid to eat his vegetables when the banana split is sitting on the kitchen table. It just doesn’t work, and it certainly gets messy.
I get the same feeling when I see the term slapped onto websites, boldly (or blindly) printed on billboards or talked about incessantly in TV spots. That’s not to say “machine learning” doesn’t deserve its place in a company’s lexicon, but it shouldn’t be positioned as a shiny new object — because it’s not — when it can be used to deliver value to a customer. It then becomes a PR professional’s job to take the trendy new buzzword and determine how it can help further a client’s business goals in the media or among customers, rather than simply using the term for its own sake.
That’s because the average customer doesn’t care about how you’re using machine learning. He does care about what machine learning delivers to him, the user. Do you really think Netflix would be as successful if they marketed “machine learning” as its product instead of a set of recommended titles based on what you just finished watching? Hardly.
Responsible public relations professionals aren’t in the business of regurgitating marketing speak. They are in the business of delivering a healthy serving of skepticism when their clients use the same words as their competitors to describe their products. PR professionals should show their clients how a true wordsmith would describe products without leaning on the crutch of “big data solutions” or similar phrases. Some of the best PR pros are journalists and have no problem acting as a gatekeeper between what a client says and what a reporter hears.
We’re writing for industry analysts, journalists, clients and customers, potential investors and employees. If that writing raises more questions than it answers, we’ve failed at our jobs. If we use language that acts as a smoke signal but doesn’t point a reporter in the direction of the fire, we’ve failed at our jobs and burned a few bridges in the process. PR professionals need to start with the meaning of a word or term, articulate it and define it with a label that makes sense without being cliche. Others may cop the word, but that just means you’re doing something right and it’s time to start the process over. That’s true innovation.
The best words are like sharp tools. They’ll slice your finger open and require your undivided attention when using them. If overused without resharpening, a tool’s durability and effectiveness decrease, eventually becoming so useless it’s hung up on the garage wall and never reused.
