I'm interpreting from this that you have more data than you have time to process, so you go after the signals in order of how close they are to the user's complaints (user convos, etc).
And this implies to me that your ideal scenario is one in which the amount of data coming in from user convos, surveys, complaints, tickets, etc is equal or greater than the amount of time you have as a team to process it, such that you can focus on that and keep yourself productively at capacity.
But what if the amount of such high-priority signals is much higher than what you can deal with? Is it worth clustering that to get a smaller list of actionable trends?
Furthermore, if this is the highest quality data, is there even any need to go in and 'process' ALL of the sessions and bin them regardless of their high-priority signal status? Am I reading you right?
And this implies to me that your ideal scenario is one in which the amount of data coming in from user convos, surveys, complaints, tickets, etc is equal or greater than the amount of time you have as a team to process it, such that you can focus on that and keep yourself productively at capacity.
But what if the amount of such high-priority signals is much higher than what you can deal with? Is it worth clustering that to get a smaller list of actionable trends?
Furthermore, if this is the highest quality data, is there even any need to go in and 'process' ALL of the sessions and bin them regardless of their high-priority signal status? Am I reading you right?