When launching an innovative product, the cost of educating consumers is a direct hit to margins. Many great products fail not because they are inferior, but because the expense of explaining their value is too high to sustain profitability, a concept described as "education eats margins."
For a true AI-native product, extremely high margins might indicate it isn't using enough AI, as inference has real costs. Founders should price for adoption, believing model costs will fall, and plan to build strong margins later through sophisticated, usage-based pricing tiers rather than optimizing prematurely.
The Browser Company found that Arc, while loved by tech enthusiasts for its many new features, created a "novelty tax." This cognitive overhead for learning a new interface made mass-market users hesitant to switch, a key lesson that informed the simplicity of their next product, Dia.
Use gross margin as a quick filter for a new business idea. A low margin often indicates a lack of differentiation or true value-add. If a customer won't pay a premium, it suggests they have alternatives and you're competing in a commoditized space, facing inevitable margin compression.
Creating products customers love is only half the battle. Product leaders must also demonstrate and clearly communicate the product's business impact. This ability to speak to financial outcomes is crucial for getting project approval and necessary budget.
Unlike SaaS, where high gross margins are key, an AI company with very high margins likely isn't seeing significant use of its core AI features. Low margins signal that customers are actively using compute-intensive products, a positive early indicator.