This video features Jonathan Parra, lead designer at Superwall, sharing insights from designing over 4,000 app paywalls. He discusses counterintuitive findings and best practices for paywall design, A/B testing, and optimizing conversion rates, emphasizing that design and packaging are crucial conversion levers, often more so than pricing.
The strategies and examples discussed in this video are specifically for mobile apps and their associated paywalls. Jonathan Parra's experience and the data he references are primarily from the mobile application space. While some principles of conversion optimization might be transferable, the context and specific tactics are tailored to the mobile app environment.
Jonathan discusses prompts in the context of AI-powered applications. He notes that users are willing to pay more for apps that offer custom prompts, especially if these prompts are tailored to a specific niche or problem. This personalization, or "prompt engineering," is seen as a key value proposition that allows these apps to command higher prices, even compared to more general AI tools like ChatGPT or Claude. He explains that users are paying for the convenience and effectiveness of a well-defined prompt that solves their specific needs without requiring them to develop it themselves. This is particularly relevant for "AI rapper" apps and other AI-driven consumer applications.
Yes, that's essentially what Jonathan is saying. He highlights that users are willing to pay for custom prompts within apps because it saves them the effort of figuring out how to prompt the AI effectively for their specific needs. It's about the convenience and the tailored results they receive with just a click, rather than having to develop those prompts themselves. This is a significant part of the value proposition for many AI-driven consumer apps.
