Founders often mistakenly market "AI" as the core offering. Customers don't buy AI; they buy solutions to their long-standing problems (e.g., more leads, better service). Frame your product around the problem it solves, using AI as the powerful new tool in your solution space that makes it possible.
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Before launch, product leaders must ask if their AI offering is a true product or just a feature. Slapping an AI label on a tool that automates a minor part of a larger workflow is a gimmick. It will fail unless it solves a core, high-friction problem for the customer in its entirety.
Most users don't want abstract tools like 'agents' or 'connectors.' Successful AI products for the mainstream must solve specific, acute pain points and provide a 'golden path' to a solution. Selling a general platform to non-technical users often fails because it requires them to imagine the use case.
Successful AI strategy development begins by asking executives about their primary business challenges, such as R&D costs or time-to-market. Only after identifying these core problems should AI solutions be mapped to them. This ensures AI initiatives are directly tied to tangible value creation.
SMB owners are not asking for technologies like AI by name. They are asking for outcomes and efficiency. B2B marketers should position advanced features not as 'AI' or 'video tools,' but as embedded, invisible solutions that make a marketing hour more impactful. The goal is to provide tools that a business owner can naturally use to get a return, without needing to become a technology expert.
Don't let the novelty of GenAI distract you from product management fundamentals. Before exploring any solution, start with the core questions: What is the customer's problem, and is solving it a viable business opportunity? The technology is a means to an end, not the end itself.
Frame your product's value not around the underlying AI, but around the premium insight it unlocks. The key is to instantly provide an answer—like a valuation or diagnosis—that previously required significant time, money, or human expertise.
Moonshot AI's CEO effectively sells his product by "vision casting"—framing it not as an e-commerce tool but as a partner that enables businesses to thrive. This focus on the ultimate outcome, rather than product features, resonates deeply with customers and powerfully articulates the value of a complex AI solution.
In the rush to adopt AI, teams are tempted to start with the technology and search for a problem. However, the most successful AI products still adhere to the fundamental principle of starting with user pain points, not the capabilities of the technology.
Instead of focusing on AI features, understand the two mental shifts it creates for customers. It either offers a superior method for an existing, tedious task ("a better way") or it makes a previously unattainable goal achievable ("now possible"). Your product must align with one of these two thoughts.
A common marketing mistake is being product-centric. Instead of selling a pre-packaged product, first identify the customer's primary business challenge. Then, frame and adapt your offering as the specific solution to that problem, ensuring immediate relevance and value.
