SurveyMonkey's results are one row per respondent. Export the CSV, drop it here, and every question becomes a clickable distribution — with responses trending by start date and any answer usable as a filter across all the others.
Survey answers are categories begging to be counted. Each question column turns into a distribution; each answer becomes a filter against every other question; the start date drives the response curve.
In your survey: Analyze Results → Export All → All response data → CSV. You get one row per respondent with a column per question.
Each question column is detected as a category; the Start Date column drives the response trend; numeric recommend scores read as numbers for an NPS-style view.
See the answer mix per question, then click an answer — every other question recomputes for that segment, and the score average follows.
The thing you actually want from survey data: how one answer relates to another — without an upgrade prompt.
Every question's answer distribution, side by side, ranked by frequency — no filter rules to configure.
Click an answer and watch every other answer distribution recompute for that group, the way a cross-tab would.
Recommend scores average per segment for a quick NPS read, while responses by start date show each campaign's reach.
Respondent IDs and free-text answers stay in your browser — nothing about who answered is uploaded.