The Heat Map displays every trait score across all rater categories in a colour-coded grid, giving you a rapid visual overview of the entire assessment.

Colour key: Deep red (1–1.5) = significant concern, orange (1.5–2.5) = below expectations, yellow (2.5–3.5) = meeting expectations, light green (3.5–4.5) = above expectations, dark green (4.5–5) = exceptional strength.

How to interpret: Scan for clusters of red or green to identify broad themes. Look across rows to see how a specific trait is rated by different groups — consistent colours indicate agreement, while mixed colours suggest different experiences. Compare columns to see whether a particular rater group tends to rate higher or lower overall.

Gap Analysis compares the individual's self-assessment against the combined average scores from all other rater groups. This highlights discrepancies between self-perception and how others experience the individual.

Positive gap (red) = the individual rates themselves higher than others do. This may indicate a "blind spot" — an area where the individual overestimates their effectiveness and may benefit from targeted feedback or coaching.

Negative gap (green) = others rate the individual higher than they rate themselves. This may indicate a "hidden strength" — an area where the individual is more effective than they realise and could leverage more confidently.

How to interpret: Gaps of ±0.5 or less typically indicate healthy alignment. Gaps greater than ±1.0 deserve attention in coaching conversations. Focus particularly on blind spots in critical competencies, and help the individual recognise and build on hidden strengths.

The Dimensions tab breaks down the assessment into its core dimensions, each containing multiple competencies and traits. Each dimension is displayed as a separate grouped bar chart showing scores by rater category.

This view lets you dive into specific areas of the assessment framework to understand which competencies within a dimension are driving overall scores up or down.

How to interpret: Compare the height of bars within each chart to see which traits are rated highest and lowest. Look for patterns within a dimension — if most traits cluster around the same score, the individual is fairly consistent in that area. Large variations between traits within the same dimension may suggest specific behaviours that need attention. Comparing rater categories within each trait shows whether the individual's performance is perceived consistently.

The Reliability tab assesses the statistical quality and trustworthiness of each trait score.

Mean is the average score. Standard Deviation measures how spread out the ratings are — lower values (below 1.0) indicate raters largely agree, while higher values suggest mixed opinions. Agreement summarises consensus as high, moderate, or low.

How to interpret: Traits marked as "Reliable" have sufficient responses and rater agreement to be considered statistically meaningful — you can act on these with confidence. Traits with low agreement or few responses should be interpreted more cautiously. Where agreement is low, it may be worth exploring why different raters have such different views, rather than relying solely on the average score.

The Comments tab collects all qualitative feedback provided by raters, divided into two sections.

Additional Comments are general observations submitted at the end of the survey — these often capture overall impressions and themes that don't fit into scored questions.

Question-Level Comments are specific notes attached to individual question responses, providing context about why a particular score was given.

How to interpret: Qualitative feedback often provides the richest and most actionable insights. Look for recurring themes across multiple raters. Pay attention to specific examples or behaviours mentioned — these make excellent starting points for coaching conversations. Comments should be read alongside the quantitative scores to build a complete picture.

The Question Drilldown provides the most granular view of the assessment data, showing every question grouped by Dimension → Competency → Trait.

For each question you can see the average score, number of responses, colour-coded score dots (1 = red, 3 = yellow, 5 = green), and any associated comments. If rater names are visible, hovering over score dots will show who gave each rating.

How to interpret: This view is ideal for identifying the specific behaviours and questions that drive overall trait scores. If a trait score is low, drill into its individual questions to pinpoint exactly which behaviours are rated poorly. Examine the spread of dots — a mix of 1s and 5s tells a very different story from consistent 3s, even if the average is the same. Use this detail to create targeted, behaviour-specific development actions.

The Deep Analysis Report uses deep knowledge and machine learning to synthesise all 360° feedback data — scores, gaps, patterns and qualitative comments — into a comprehensive narrative report.

The report identifies key themes, strengths, blind spots, and development areas across all dimensions and rater categories. It provides contextual interpretation that goes beyond raw numbers and offers actionable coaching recommendations.

How to interpret: The Deep Analysis Report is a starting point for deeper conversation, not a final verdict. Use it alongside the quantitative data on the other tabs to validate its conclusions. The AI excels at identifying patterns across large data sets that may not be immediately obvious. Pay special attention to areas where the Deep Analysis Report's analysis aligns with the quantitative gaps and comment themes.

The HR Report is a free-form rich-text document where HR professionals or coaches can write their own analysis, recommendations, and action plans based on the 360° feedback data.

This report is saved against the assessment and can be edited at any time. Use it to document key findings, coaching plans, development goals, and agreed follow-up actions.

How to use: Summarise the most important themes from the quantitative and qualitative data. Identify 2–3 key strengths and 2–3 development priorities. Link development actions to specific feedback evidence. Set clear, measurable goals and timelines for follow-up.

The User Feedback report is a short, positive one-page document designed to be shared directly with the feedback subject.

It summarises their key strengths as perceived by colleagues and provides practical, positive actions they can take. This is not the full analysis — it is an encouraging summary suitable for the individual.