> ## Documentation Index
> Fetch the complete documentation index at: https://guides.robylon.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Guide: Using the Analytics Dashboard

> The Analytics tab provides detailed reports and real-time data on team performance and customer interactions. This guide explains how to configure your dashboard, set up automated reports, and track key support metrics.

## Configure Your Dashboard

Use the **configuration button** on the Analytics tab to enable or disable the analytics modules you want to view.\
You can personalize the dashboard for different roles (e.g., managers, team leads, agents).

***

## Create an Automated Report

<Steps>
  <Step title="Create a New Report">
    Click the **New Report** button on the Analytics tab.
  </Step>

  <Step title="Set Delivery Schedule">
    Choose how often the report is emailed:

    * **Daily** — Track day-to-day performance
    * **Monthly** — Monitor trends and strategy outcomes
    * **On-demand** — Generate custom reports anytime
  </Step>

  <Step title="Export Data (Optional)">
    Export reports to an **Excel file** with detailed ticket resolutions and automation data.
  </Step>
</Steps>

***

## View Key Metrics

<Accordion title="Team Activity">
  View a list of team members with:

  * Online / Offline status
  * Login and logout times
  * Total time available for chat
</Accordion>

<Accordion title="Chat Resolutions">
  Track:

  * Chats created
  * Chats closed by the bot
  * Chats closed by agents

  Filter by **Today, Yesterday, or Last 7 Days**, and compare with previous periods.
</Accordion>

<Accordion title="Customer Satisfaction (CSAT)">
  Monitor overall **CSAT scores** across all channels, as well as:

  * Bot CSAT
  * Agent CSAT

  View **trends over time** to identify performance peaks and dips.
</Accordion>

<Accordion title="Issue Types">
  Analyze the distribution of **common issues** across chats and tickets.\
  Helps identify recurring customer pain points and prioritize fixes.
</Accordion>

<Accordion title="Knowledge Base Gaps">
  Measure knowledge base effectiveness:

  * Total questions asked
  * Successfully answered by KB
  * Unanswered queries

  Use these insights to improve and expand your documentation.
</Accordion>

***

## Voice Analytics

Track how your **voice agent** performs across pickups, duration, and user engagement. Use the **date filters** (15 Days, 7 Days, Today) to switch time ranges and compare trends.

### Voice Resolution (KPIs)

At the top of the page, the Voice Resolution strip shows today’s headline metrics (with % deltas vs. previous period):

* **Voice Calls Triggered** — Total outbound/inbound voice tasks initiated.
* **Voice Calls Picked Up** — Calls answered by users.
* **Voice Calls Picked Up in First Try** — First-attempt connections (quality of list/routing).
* **Call Tries per Pickup** — Average attempts needed to get one pickup (lower is better).
* **Average Call Duration per Picked-Up Call** — Typical handle time for successful calls.
* **Average Number of User Turns per Picked-Up Call** — Conversation depth/engagement signal.

<Tip>
  If **Call Tries per Pickup** rises or **First-Try Pickups** drop, review dialer windows, number reputation, and list quality.
</Tip>

### Call Analytics (Timeline)

A time-series chart of call outcomes for the selected range:

* **Calls triggered** (red)
* **Calls picked up** (blue)
* **Picked up first try** (green)

Use this to spot **spikes** in calling or **pickup windows** (hours where users answer most).

### Retries per Pickup

Line chart of **average retries before a successful pickup** across the day.

* Sudden peaks suggest list quality issues or suboptimal call windows.
* Sustained high values warrant **cooldown** rules or **time-of-day** adjustments.

### Call Duration (Bucketed)

Histogram of **picked-up call durations** (e.g., `<10s`, `10–30s`, `30–120s`, `120–300s`, `300–600s`, `>600s`).

* More **30–120s** bars usually indicate efficient verification/short workflows.
* Many **less than 10s** calls may imply accidental pickups or poor intros.

### User Turns (Distribution)

Bar chart of **user turns per picked-up call** (e.g., `0`, `1–3`, `3–6`, …).

* **0 turns** after pickup → user hang-ups or IVR misfit.
* **1–3 turns** suggests short confirmations; **6+** may need script simplification.

***

### Recommended Actions

* **Improve pickup**: Test alternate **calling windows**, verify **CLID reputation**, and throttle retries to reduce **Call Tries per Pickup**.
* **Tighten intro**: If \*\* less than 10s durations\*\* spike, shorten the greeting and clearly state **purpose + opt-out**.
* **Guide to resolution**: If **User Turns = 0** or **1** dominate, add a quick **DTMF** or **yes/no** prompt to capture intent before hang-up.
* **Policy & cadence**: Cap total attempts per user/day and add **cooldowns** after consecutive failures.

<Note>
  All charts respect the **15 Days / 7 Days / Today** filters. Use the same range when comparing KPIs to timeline patterns.
</Note>

***

## Best Practices

<Note>
  Schedule **monthly automated reports** for leadership review, and **daily reports** for frontline managers.
</Note>

<Tip>
  Use **Knowledge Base Gap reports** to prioritize new help articles. A 10% reduction in unanswered queries can significantly boost CSAT.
</Tip>