Upload a CSV, pick your rating questions, and get top-box and top-2-box shares, full response distributions, median categories, and a diverging bar chart that ranks every item. Numeric codes or text labels — the scale is detected from your data. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size — sign up to analyze your full dataset.
Detecting your response scale and computing top-box shares...
Sent to — response distributions per item, top-box and top-2-box shares, median categories, a diverging stacked bar ranking every item, an optional rank-based group comparison, R code, and AI insights.
Analyze another fileThe response scale is detected from the data itself: numeric codes are read in ascending order, and text labels are ordered by matching them to a known survey wording family (agreement, satisfaction, frequency, quality, likelihood, importance) rather than alphabetically. Every item is then summarised on that shared scale — the full distribution, the top-box share (the highest option), the top-2-box share, the bottom-box share, the modal category, and the median category, defined as the lowest option whose cumulative share of answers reaches 50 percent so that it stays well defined under ties and even sample sizes. Items are ranked by top-2-box and drawn as a diverging stacked bar with shares at or below the midpoint to the left of zero. When a grouping column is mapped, each item's ranked answers are compared with Mann-Whitney (two groups) or Kruskal-Wallis (three or more), with Holm correction across items and a rank-biserial or epsilon-squared effect size. The mean of the codes is reported alongside, always with the equal-spacing assumption stated.
Use it for any set of survey questions answered on a rating scale — employee engagement, customer satisfaction, product feedback, course evaluations, agreement batteries — especially when you want to rank items or report them to an audience that will read an average as a measurement.
Not for a single continuous measurement (use the group comparison or regression tools), not for unordered categories such as "which channel did you use" (use the categorical association tool), and not for judging whether several items form one reliable scale (use the reliability tool for Cronbach's alpha).
Built for: Anyone reporting survey results — HR and people analytics, customer insight, product research, course and program evaluation
Typical data source: A survey export where each row is a respondent and each rating question is a column, answered either with numbers or with words
One row per respondent, one column per rating question, optionally a grouping column. Answers may be numeric codes or text labels:
Minimum 10 rows · Best with 100-20,000 respondents and 3-20 scale items
Standard-library analysis: your Likert-scale survey items analysed as the ordinal data they are, not as if they were numbers. Map the columns holding your scale answers and get, for every item, the full response distribution, the top-box and top-2-box shares, the bottom-box share, the median response category and the modal category, plus a diverging stacked bar across all items so you can rank them at a glance. The scale itself is detected and stated from the data — numeric codes (1-5, 1-7) or text labels ("Strongly disagree" through "Strongly agree") ordered by their wording rather than alphabetically. An optional grouping column compares the groups with a rank-based test (Mann-Whitney or Kruskal-Wallis), Holm-corrected across items, never a t-test on the raw codes.
The response scale as read off your data — how many points, in what order, and which options people actually used.
Every item's top-box, top-2-box, bottom-box, median and modal category in one ranked table.
Every item's full distribution on one axis, negative left of zero — where polarised items give themselves away.
The unambiguous ranking: the share choosing one of the two highest options, item by item.
Which items your groups answer differently, on a rank-based test corrected for testing many items at once.
Every definition and every assumption, including the one behind the mean.
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Which survey question is our weak point?
Map every scale question. Each item gets its full distribution, its top-box and top-2-box share, and its median answer, and the diverging bars rank them all on one axis — so the weakest item is visible rather than buried inside an overall average.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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