You can use jargon in your startup pitch

The pitch determines your positioning and positioning determines the success of your startup. Of course, there’s plenty of advice on how to pitch your startup. Among this advice, a common suggestion is to avoid using jargon. In fact, experts will tell you not only to avoid jargon, but also that your tone should be understood by a five-year-old child. Unless your customers are five years old, this is bad advice. Jargon is the shortest and most accurate way to explain a problem. The key is to make sure your target audience understands it. If you’re marketing to customers in a niche, you can use domain-specific jargon that they’re familiar with. This will make them feel that you speak their language.

Why jargon has a bad reputation

When I was a developer, I used jargon a lot when talking to other developers. They appreciate it because it gets the point across and saves everyone’s time. But when I became a founder, that became a problem. We developed a machine learning algorithm that works without training data. When I put it to fellow developers, I would say that we are solving the cold start of machine learning problems. The developers understand this. But when I brought it up to the customers, none of them understood what I meant. I followed the common advice and tried to simplify my tone by saying, “You can build machine learning algorithms like Google even if you don’t have as much data as Google.” It still didn’t sound. Finally, an e-commerce promoter told us that their product recommendation algorithm doesn’t work for new users because they don’t have much information about it. He asked us if our technology could solve that problem. We said yes and changed our pitch to “product recommendation engine for new users.” It works.

Jargon is the shortest and most accurate way to explain a problem. The key is to make sure your target audience understands it.

The issue is not the jargon itself; it’s about using jargon that matters to your customers. “Product recommendation engine” is also jargon, but it addresses a problem that customers care about, while “machine learning algorithm that works without training data” does not explain what available to customers. This assumes that the problem we are dealing with (“cold start problem” in our case) is something that customers are also concerned about, which is often not the case.

Image Credits: Mani Doraisamy

When jargon is best

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