Solutions
Solutions are the features, products, or approaches we create to address customer problems or needs.
Why do we naturally jump to solutions?
Solutions represent how our brains naturally work. When we encounter a problem, we immediately jump to "what to build"—whether that's a specific design, a new feature, or a change to an existing product.
This is true for everyone:
- Customers ask for feature requests (solutions)
- Stakeholders suggest specific approaches (solutions)
- Product teams brainstorm ideas (solutions)
That's okay. That's how our brains work. But the key is recognizing when we're jumping to solutions and gently bringing the conversation back to understanding the underlying problem.
Where do solutions fit in product analysis?
Solutions exist at one level in a hierarchy of product questions:
- Design question: What is the best way to build this solution?
- Feature question: Is this the right solution to the problem?
- Value question: Are we solving the right problem?
When a solution hits a roadblock—whether it's a feasibility constraint or it's the wrong fit for the customer—teams should move up a level to explore alternatives or question whether they're solving the right problem.
Why does specificity matter when testing solutions?
When testing solutions, specificity matters. "Fixing a hard-to-use comment form" is not specific enough. How will you fix it?
Each different approach is a distinct solution worth testing:
- A redesign using dropdown menus (one solution)
- A redesign using inline editing (a different solution)
- A simplified form with fewer fields (yet another solution)
Some solutions might work. Others might not. Each is worth evaluating on its own merits because they're fundamentally different approaches to the same problem.
How do you turn feature requests into problems?
When customers request features (solutions), those requests are clues to problems you haven't uncovered yet.
Ask questions like:
- "How would you use that?"
- "Tell me about when and why you would use that"
Dig for the problem. It will be worth it—because understanding the problem helps you explore better solutions than the one initially requested.
Learn more:
- Hypothesis Testing Mistake #1: Not Knowing What You Want To Learn
Related terms:
- Assessing Opportunities
- Assumption Testing
- Prototyping
Last Updated: October 25, 2025