Problem Discovery: From Feature Requests to the Real Problem
The first stage of the Double Diamond focuses on Discover. Instead of immediately focusing on the first problem or solution that comes to mind, this stage is about exploring the problem from different perspectives and developing a deeper understanding of the current situation.
During Discover, teams gather evidence through observation, user interviews, data and log analysis, and the exploration of different hypotheses. In the Define stage, these findings are reviewed, consolidated, and prioritized to determine which problem is truly worth solving.
The key idea is simple:
The first diamond does not ask what we should build; it asks which problem is actually worth solving.
A Feature Request Is Not Necessarily the Real Problem
In many software teams, a problem enters the team in the form of a requirement or feature request. However, a specific feature request does not necessarily represent the customer's underlying problem.
For example, a request might be:
“Add transfer history to the application.”
If we immediately start designing this feature, we may assume that the problem is the absence of transfer history. A product-thinking approach, however, first asks:
“Why does the user need transfer history?”
User behavior may reveal that users who want to transfer money again to previous recipients have to repeatedly find and copy the recipient's card number from messaging apps or other sources. This process takes time and increases the possibility of errors.
The underlying problem might therefore be:
“Sending money again to previous recipients is a time-consuming and effort-intensive process for users.”
In this example, transfer history is only one possible solution. It should not automatically be considered the best solution before the problem is properly understood.
Sources for Problem Discovery
A strong problem-discovery process should not rely on a single source of information. Three important sources can provide complementary perspectives:
Users and their behavior: User interviews, observation, support tickets, and customer feedback.
Data and logs: Customer Journey analysis, Funnel Analysis, and step-by-step analysis of how users interact with the product.
Business and market: Competitor analysis, similar product capabilities, and solutions already available in the market.
Combining these sources allows teams to examine the problem from multiple perspectives and reduces the risk of making decisions based on a single request or isolated signal.
From Technical KPIs to User Experience
One of the important responsibilities of a product manager is to connect technical metrics with user behavior and experience.
In many software projects and contracts, metrics such as Latency, Error Rate, Availability, Uptime, TPS, and API response time are closely monitored. However, their real importance becomes clearer when we understand how they affect the user's actual experience.
For example, if an API becomes slower, the impact is not limited to a technical issue. When a response takes too long, the user may think that the application has stopped responding or that their request was not processed. As a result, they may submit the same request again.
Repeated requests can increase system load and, if not handled properly, may even lead to duplicate transactions and reduced user trust.
This means that a technical KPI can directly influence user behavior and the quality of the user experience.
A product manager should understand the relationship between four key areas:
Technical KPIs, user experience, user behavior, and business outcomes
Alongside technical metrics such as response time, error rate, and stability, metrics such as perceived speed, task success rate, satisfaction, trust, and repeated actions are also important for evaluating the actual quality of a product.
Ultimately, the product manager should create an effective connection between the technical team, user experience team, and business team.
Real value is created when technical KPIs can be connected to user-experience KPIs, their impact on user behavior can be understood, and their relationship with business outcomes can be identified.