Dashboard overview

Open the Analytics Dashboard by clicking Analytics in the sidebar. The dashboard is divided into several panels — each focused on a specific aspect of your project's story management. A date range picker at the top lets you filter all panels to a specific window. Choose from preset ranges (7 days, 30 days, 90 days) or set a custom start and end date. The dashboard respects your project's timezone, which is configured in Project Settings.

Velocity chart

The velocity chart plots committed vs completed story points for each sprint in the selected date range. A rolling average line shows your team's mean velocity over the last three sprints. Green upward and red downward trend indicators appear next to each sprint when the completion rate changes significantly compared to the previous sprint. Hover over any data point to see the exact story point values and the list of stories that contributed to that sprint.

Cycle time analysis

Cycle time measures the average time a story takes from creation to approval. The Cycle Time Analysis panel breaks this down by feature, so you can see which features move quickly through the pipeline and which get stuck. For each feature the panel shows:

• p50 — the median cycle time (50 % of stories are faster than this).
• p75 — 75 % of stories complete within this duration.
• p95 — 95 % of stories complete within this duration (useful for identifying outliers).

Features with unusually high p95 values are flagged with a warning icon. Use this data to spot features that may need to be sliced into smaller pieces.

Rejection rate

This panel tracks the percentage of stories that are rejected during the review workflow. A trend chart shows how the rejection rate has changed over time — a decreasing trend indicates that your team is getting better at creating well-defined stories. Below the chart, a ranked list shows the top reasons for rejection extracted from review comments, making it easy to identify recurring issues such as unclear acceptance criteria, missing edge cases, or ambiguous wording.

Persona breakdown

The Persona Breakdown panel shows the distribution of stories by user persona. A bar chart or pie chart (toggleable) visualises which personas are covered by your stories and which are underrepresented. This helps ensure that all user perspectives are addressed when slicing features. Personas that have zero stories assigned are highlighted so you can decide whether to create additional stories for them.

Bottleneck detection

Storymate's AI analyses the workflow state history of every story to identify bottlenecks. The Bottleneck Detection panel highlights stages where stories spend an unusually long time. For example, if several stories remain in PENDING status for days without being reviewed, the panel flags this and suggests possible causes. Each bottleneck includes:

• The affected workflow stage and the average time spent there.
• The number of stories currently stuck or delayed at that stage.
• An AI-generated recommendation for resolving the bottleneck (e.g. "Consider reducing the number of stories per sprint" or "Add more reviewer capacity").

Estimation accuracy dashboard

This panel compares the AI-generated story point estimates against the actual effort recorded after stories are completed (via connector data). Metrics include:

• Calibration accuracy — the percentage of estimates that fall within ±1 story point (or equivalent) of the actual value, tracked over time.
• Over-estimation pattern — which ranges tend to be overestimated (e.g. large stories are often overestimated by 30 %).
• Under-estimation pattern — which ranges tend to be underestimated.

The chart updates as more stories are completed, and the underlying calibration engine automatically adjusts future AI estimates to improve accuracy. No manual tuning required.

Exporting

Click the Export button in the top-right corner of the Analytics Dashboard to download reports. Two formats are available:

• PDF — includes all visible charts as rendered images plus summary tables. Ideal for sharing with stakeholders or attaching to meeting notes.
• Excel — contains the raw data behind every panel for further analysis in your spreadsheet tool of choice. Each panel's data is placed in a separate worksheet.

The exported report respects the currently selected date range. You can also export individual panels using the export icon in each panel's header bar.