# Reputation

Compare evidence-backed reputation dimensions and inspect how each score is supported.

Canonical: https://docs.equalai.io/analytics/reputation
Markdown: https://docs.equalai.io/analytics/reputation.md

Open **Reports → Reputation** to review your brand and tracked competitors against the dimensions configured for the project. Reputation reports use already collected responses; they do not replace running your prompts.

## Prepare and generate a report

1. Collect answers to questions relevant to the attributes you want to investigate.
2. Open **Configure dimensions** and review the dimensions before saving changes.
3. Select **Generate reputation report** when no report is open, or **Regenerate** to create a new report from available evidence.
4. Use **All reports** to return to the saved report library.

Generating or regenerating is a write action. Changing dimensions and generating reports should be deliberate, not a way to refresh a read-only view. A dimension needs relevant prompt or answer evidence; adding its name does not manufacture supporting observations.

## Read Overview

Set the date range and **All filters**, then inspect **Brand comparison**, **AI reputation score**, and **Dimension breakdown**.

- The overall reputation score averages dimensions that have evidence. Unscored dimensions are excluded, not treated as zero.
- Standing is relative to brands with evidence in the current tracked set.
- Mention share compares tracked brand mentions, not the entire market.
- Dimension coverage distinguishes relevant evidence for a specific attribute from a broad overall signal.
- Visibility and citation authority are indexed relative to the strongest tracked brand. Sentiment uses an absolute scale with 50 representing neutral.

A leader-relative score can change when competitor evidence changes, even without a corresponding change in your own responses. Read response counts, evidence tiers, and reasoning alongside the score.

## Inspect model and raw evidence

Open **Model Comparison** to compare dimension scores by model and focus on the brand or dimension offered by the controls.

Open **Raw Data** for rows by brand, model, and dimension. Use its dimension filter and search, and disable **Hide unscored** when you need to see gaps rather than only supported scores. Read the evidence tier and reasoning before interpreting a number as a robust conclusion.

Use **Export CSV** for the relevant report or raw-data view. Keep the selected scope with the export when sharing a comparison.

## Troubleshooting

- **Generate is unavailable:** collect tracked AI responses first.
- **Responses exist but there is nothing to score:** the selected answers may not mention your project or tracked competitors.
- **A dimension has no score:** inspect whether relevant questions and answers support it; unscored is not poor performance.
- **No rows match:** widen the date range or clear filters.
- **Scores differ from Overview:** these are dimension/evidence and competitor-indexed calculations, not the Overview visibility average.

## Related guides

[Prompts](https://docs.equalai.io/analytics/prompts) · [Sentiment](https://docs.equalai.io/analytics/sentiment) · [Competitors](https://docs.equalai.io/tracking/competitors)