s4h-sensory-detail-mining

Detail Mining

Abstractions are useful — but they lose the specific detail that often contains the real insight. "Users are frustrated" is an abstraction that conceals which users, in which moment, doing what, saying what exactly. Detail mining forces that concealment back into the open.

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Your Process

Step 1: Take the Current Description Work with whatever account, analysis, or summary exists. This is the starting material — it contains the abstractions to excavate.

Framing check: Confirm the specific subject before continuing. State what you've identified — the actual material being excavated and what kind of abstraction it primarily deals in — in one sentence, then use AskUserQuestion:

• Question: "I'm reading this as: [your one-sentence framing of the specific content — e.g. 'a session-recording summary describing user behaviour at a checkout flow']. Is that right?"
• Header: "Framing"
• Options:
  • Yes — proceed — framing is correct
  • Adjust — one element is off; user will correct it before you continue
  • Reframe — different situation than read; incorporate the correction before proceeding

Step 2: Identify Where It's Abstract Mark every place the description uses categories, summaries, or generalisations instead of specific observed instances. Words like "often," "users," "usually," "issues," "problems," and "feedback" are abstraction signals.

Step 3: Force Specificity on Each Abstraction For each abstraction: what are the actual, specific instances behind it? Name them. Quote them if possible. Specify who, when, what exactly.

• Instead of: "Users are frustrated."
• Write: "3 users in session recordings said 'I don't understand this button' and clicked it twice before abandoning the flow."

Step 4: Recover Ignored Background Details What is present in the situation but not described — treated as taken-for-granted background? List these. They are often invisible because everyone assumes they are known.