From: redpointai
The business model and pricing strategy for AI music platforms are still in their nascent stages, with companies like Suno navigating uncharted territory [00:18:26]. While there’s broad discussion across the AI industry about optimal pricing, the specifics for AI music remain largely undefined [00:18:08].
Current Approaches and Challenges
Suno, a prominent AI music platform that recently raised 500 million valuation [00:00:17], currently operates with a freemium model [00:18:12]:
- Free Tier: Users can generate a set number of songs for free [00:18:12].
- Paid Tier for Power Users: Advanced users are charged as they generate more songs [00:18:14].
However, this model is acknowledged as a temporary solution. The industry is in such early stages that the long-term enjoyment and use cases for AI music are expected to evolve significantly [00:18:34]. Suno’s current focus is on product innovation, not on innovating its business model [00:18:40].
A primary challenge stems from founders and investors adapting traditional SaaS pricing models to AI, where the marginal cost of generating a song is not zero [00:19:08]. This means that unlike SaaS, where usage doesn’t significantly add to underlying costs, each song generated on an AI music platform incurs a compute cost [00:56:09]. This direct correlation between usage and underlying cost makes traditional subscription models less straightforward [00:56:28].
The ideal pricing strategy is expected to be highly dependent on the specific product and its use case, varying across music, text, and video AI applications [00:19:40].
Metrics and Future Considerations
Suno tracks several metrics to gauge user engagement and satisfaction, which implicitly inform their business model:
- Number of users making songs [00:24:50].
- Daily active users returning to create songs [00:24:52].
- Probability of users exhausting their free tier, indicating enjoyment even if they don’t pay [00:24:56].
- Sharing activity, as music creation is increasingly a social experience [00:25:10].
The company’s substantial fundraise is primarily allocated to scaling in multiple areas [00:35:11]:
- Model Training: While music models may not require the same level of compute as the largest text models, they still demand significant resources and specialized data [00:35:13].
- Research and Development: Developing the correct way to model music is still ongoing [00:35:42].
- Hiring Talent: Attracting and retaining top talent is crucial for growth [00:36:16].
Ultimately, the capital is deployed to “pull forward the future of music” that Suno envisions, focusing on expanding the market for music and bringing more joy to people’s lives through accessible creation [00:39:40]. The long-term vision is that as AI transformation in the music industry matures, and user behaviors around music creation with AI and user experiences become clearer, more sustainable and tailored business models will emerge [00:19:28]. This is part of the broader evolution of AI startup strategies and investment strategies in the AI landscape.