We have a straightforward opinion here: the spreadsheet tools most people rely on were not built for the kind of work this user is doing, and that is a real problem. This person is managing a dataset of over three thousand rows, tracking questionnaire responses across multiple sessions and participants, and trying to isolate which questions generate the most comments. They are not asking for a miracle. They want a count of each variable, a sorted list from most to least frequent, a way to filter out test participants, and the ability to trace any comment back to its original context. Those are reasonable, concrete needs. Yet the default toolset forces them to consider combing through every row by hand.
What stands out is the user's self-description as a "complete Excel beginner," paired with the admission that pivot tables did not make sense to them. That is not a failure of the user. It is a failure of the tool. Pivot tables are powerful, but they require a mental model of data that is not intuitive for someone whose primary concern is understanding their participants' responses, not restructuring columns and rows into abstract aggregation zones. The user should not have to learn a separate conceptual language just to get a simple count. The tool should adapt to the task, not the other way around.
This is exactly where an AI-native approach changes the equation. Imagine describing your goal in plain language: "Give me a count of how many times each variable appears, sorted from most to least, and remove any rows where the participant is marked as 'test.' Keep the participant ID and session info so I can look up the original context." That should be the instruction. The system interprets the intent, applies the logic, and returns the organized result. No pivot table wizardry. No manual filtering. No learning curve for a feature that exists only because spreadsheets were designed by engineers for engineers.
The user's example screenshots show exactly what they want: a clean, sorted summary that preserves the ability to trace any comment back to its source. That is not an unreasonable ask. It is a fundamental data management task that should be simple. The fact that it is not simple in traditional tools is not a sign that the user needs to learn more. It is a sign that the tools need to catch up. Our take is this: stop struggling to describe your spreadsheet problem in terms the spreadsheet understands. Start describing your problem in terms you understand, and let the technology handle the rest.