Here's how you can utilize feedback to identify and resolve technical issues in an application.

Effectively gathering data is crucial for resolving technical issues in your application. Start by establishing a robust feedback system through in-app forms, support emails, and external platforms. Collect detailed context, including user environment, steps to reproduce, and screenshots or logs, to understand the problem fully. Analyze the feedback to identify patterns and prioritize issues. Engage with users for clarification and inform them when issues are resolved. Implement fixes and monitor the app to ensure problems are addressed. Continuously improve your feedback collection methods to maintain a smooth and user-friendly application. More data means better problem-solving and user satisfaction.

Structured data is far more useful than unstructured. If you use forms make sure there are defined choices and not just blank fields for the user to use. Also you must pay attention to any data that may be sensitive e.g. PII. You still need to treat any data in the event of a problem with the same level of care you would if storing it. Try to avoid use of email, etc. as it is far better to ask the user at the point of the problem as you will be able to tie back their input with the diagnostics from the system.

Try to structure your data as much as possible so you don't have to try to reinvent data that would have been available to you at the point of the error. Using correlation identifiers across systems will help in tying together information from different parts of the overall system.

To resolve technical issues, you must first be able to reproduce them. This process is vital for understanding the root cause and ensuring that any fixes implemented will solve the problem for users. - Gather detailed feedback, including error messages, time of occurrence, and user actions leading up to the issue. - Replicate the user’s browser configurations and operating systems in our testing environment to observe the same issues. - By setting up a controlled environment mirroring the transaction data and patterns reported by users, devs can able to reproduce and analyze the false positives.

If you have good instrumentation and logging the need to reproduce a problem may not be required. If you are working on a website with 8 million people all of which have data that has been created over the duration of 40 years you 1) may not be able to recreate the same data e.g. it could be PII and 2) may not be reproduce the error. A disciplined approach of getting meaningful diagnostic data including stack trace, business data (masked if appropriate), expected flow, exceptional flow, etc. will help immensely and will avoid the trap of not being able to identify the cause of the error because you can't recreate the exact circumstances.