Does your value proposition follow the two-pronged attack?
Creating AI products is difficult and risky. Looking at the industry reports and successful products like Aviso. We believe value needs to be delivered in two crucial ways to be impactful:
- Does not need time to deliver value to the customer
- Tackles a time-consuming or error-prone activity in a business-critical process for an industry
Recommended experiment vehicles
- Persona Interviews
- Data analysis
- Concierge experiments
Does your value proposition use its own data?
Customers are always looking for a compelling reason to buy your product. Investors are looking for the competitive edge your product will have over others. In an AI product, this is the source of your data. If you are using someone else's data, it's only a matter of time before a competitor catches catch-up. However, in Venture Design, start with broadly available data or even simulated data while working on a plan to generate your own data.
Recommended experiment vehicles
- PoCs
- Model Prototype
Does your value proposition work without data?
It is a given that your value proposition will only be as strong as your data. There will be use cases where your data will not provide any results. This is acceptable for your first version - and it is even expected from a venture design point of view. But that doesn't mean you should provide zero value if you don't have data for a specific use case. Your eventual solution should leverage intelligent logic-based reasoning to determine the outcome.
Recommended experiment vehicles
- PoCs
- No-code MVPs
- Letter of Intent
Does your value proposition work well with others?
Nobody wants to manage multiple applications. Customers today are looking for ecosystems and products that integrate well with the ecosystems already in the market. This means that from a venture design perspective, start with an API-first product that integrates with the Dynamics 365 ecosystem and then look to create a stand-alone product in the future.
Recommended experiment vehicles
- Big Idea MVP
- PoCs
Conclusion
True AI-based products are unique and they don't follow the same validation and de-risking criteria as software, hardware, or services. However, it is possible to framework a venture design approach that allows you to develop a business model and product in a continuous and incremental approach.