Using AI to identify product-market fit
- Daniella, a product marketer who’s worked at Canva and Atlassian, shares an AI-driven framework to help startups assess product-market fit.
- This approach can help to quickly identify key segments and use cases, saving time and resources.
- Entrepreneurs, startup consultants, and product managers might find this framework particularly useful.
- Daniella highlights the benefits of AI in discovering overlooked opportunities and suggests using tools like Perplexity for enhanced insights.
Exploring segmentation and use cases
Imagine you're a startup consultant with 10 years of experience. Your client is a SaaS company who has built a new bug-reporting technology for software developers in the USA. Your client's technology provides a multi-platform bug-reporting software so users can record screencasts to capture videos of bugs, crashes, and errors.
Your client is asking to understand what opportunity to target within the IT industry. They want you to consider all types of processes, segments, and use cases. You need to:
1. Provide a list of potential segments to target with this technology. Define a segment as the type of IT or SaaS company and the audience's role.
2. Provide a list of potential use cases or applications to target with this technology. An application can match a problem to be solved within the segment you listed in step 1. The best way to think about use cases is to identify the different processes in the segments outlined in step 1 and identify problems to solve.
Response:
Scoring the segments and use cases
Prompt used:
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I used this framework and detailed AI prompts to identify new segments, audiences, use cases, and competitors for a SaaS startup who were in the process of understanding if they had product-market fit.
The goal with this framework was to start broad to understand the scope of the opportunity, then slowly focus onto a particular audience and set of use cases to understand which to prioritize. I’ve included both prompts and responses (where useful) to provide greater context.
In terms of the prompting process, I’m a fan of the RISEN framework as a basis which I modify based on my needs. This comprises of:
Role: Define your role, from what perspective should AI tailor its response?
Instruction: Specify what you want AI to accomplish. What's the task at hand?
Steps: Outline the necessary steps AI needs to take. What are the steps?
End goal: Identify target audience and your expectations. What do you hope to achieve? What is the success criteria?
Narrow (optional, but recommended): Set boundaries. Are there any parameters of your request?
You don’t have to feature these elements in sequential order—I play around with different approaches myself—but having this as a baseline for prompting has been invaluable and now it’s almost muscle memory for me. I recommend bookmarking particular prompt formats that worked well for you in a repository to refer to.
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