> For the complete documentation index, see [llms.txt](https://docs.helvia.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.helvia.ai/observatory/analytics.md). # Analytics Analytics gives you a workspace-wide view of how your agents perform. Open **Observatory > Analytics** to track engagement, session volume, response times, user feedback, and more across all agents and deployments. The default Helvia Dashboard organizes metrics into eight tabs, each covering a different aspect of agent performance. Custom dashboards tailored to your needs are also available by [contacting support](/resources/support.md).

### The Helvia Dashboard The default Helvia Dashboard organizes metrics into eight tabs. Each tab isolates a different dimension of agent performance so you can jump straight to what you need. For example, there are different tabs that map directly to the four workflow types in Designer: Generic, LiveChat, Surveys, and User feedback. The remaining tabs cover cross-cutting metrics like session summaries and, missed questions. Select any tab in the table below to navigate to its detailed section. | Analytics Tab | What It Tracks | | ----------------------------------------------------------------------------------------- | -------------------------------------------------------------------- | | [**Summary**](#summary) | Engagement rate, session volume, message counts, and user growth | | [**Automated Answers**](#automated-answers) | Trigger frequency for each pre-built response | | [**LiveChat**](#livechat) | Containment rate, missed chats, response times, and session duration | | [**Generic Flows**](#generic-flows) | Interaction distribution across generic workflows | | [**Surveys**](#surveys) | Survey completion, abandonment, and reach | | [**User Feedback**](#user-feedback) | Agent and LiveChat satisfaction scores | | [**Missed Questions**](#missed-questions) | Unanswered question volume, top misses, and daily trends | | [**CSAT**](#csat) | Customer satisfaction scores, per-section breakdowns, and usage | The Analytics dashboard scopes every chart to the typical Observatory filters at the top of the page. Check them first if a chart looks empty or the numbers look off. ***

		Cover image
Date Range	Set a start and end date to define the time window. Click Apply to update the results	/files/YGZDrhzwxahrZUDgDeub
Agents	Filter by agent or a specific deployment. Selected agents pin to the top of the dropdown	/files/x72II7mqcgDJkQE3RbP7
Tags	Include or exclude sessions by tag	/files/wEH8OZwrYajS6huOVqaX

{% hint style="info" %} Filters live in the URL, so sharing or bookmarking the page reproduces the same view. Your selection also persists as you navigate across the Observatory. {% endhint %} *** #### Reading the Charts Analytics are exposed through charts, plots and tables. The dashboard uses a consistent set of chart types across all tabs, so familiarizing yourself with these once makes navigating any tab faster.

Title	Description	Cover image
Donut Charts	Show ratios and proportions, like engagement rate or missed question percentage. The center displays the key metric	/files/NymitVccxg7TwhcxedPJ
Time Series	Track trends over your selected date range. Use the toggle icons in the top-right corner to switch between line and bar views	/files/6McQgMH9LpijQUXJDiuJ
Gauge Charts	Display scores on a scale, like overall CSAT satisfaction. The color gradient indicates performance ranges	/files/V8gv8ZKyIGeCQT4YQFAd
Data Tables	Rank items by count or score with sortable columns. All tables include a download button for CSV export	/files/4tXRSlCcnxIeoDjPUGhN

Every chart card includes a fullscreen button to view it in detail, and most charts display a summary table below with key numbers like totals, averages, and min/max values. ### Sharing and Exporting Analytics don't have to stay inside the platform. The **Share** and **Export** buttons let you get data in front of anyone who needs it, whether they have a platform account or not. To automate recurring deliveries of the dashboard to stakeholders, schedule them from [Reports](/observatory/reports.md).

{% columns %} {% column %} #### Sharing Generate a public URL that gives view-only access to the dashboard. Recipients do not need a platform account to open it. You can select which specific sections to include in the shared dashboard. {% endcolumn %} {% column %} #### Exporting Download the full analytics report as a PDF covering all tabs and charts in a single document. The export respects your current filter selection. {% endcolumn %} {% endcolumns %} {% hint style="warning" %} Shared links are publicly accessible to anyone with the URL. Avoid sharing dashboards that contain sensitive data. {% endhint %} *** The rest of the sections below walk through each analytics tab in detail, covering what they track and how to read the data they present. ### Summary This is your starting point for a quick health check across all agents and conversations. The tab answers four questions at a glance: how engaged are your users, how many conversations are happening, how much are users messaging, and is your audience growing.

Title	Description
Engagement	The ratio of interactive to non-interactive sessions. A high rate means users are going beyond the initial greeting
Sessions	Session volume over time. Spot traffic patterns, usage spikes, or drops that correlate with deployments or external events
User Interactions	Total message volume with averages per session and per user. Higher averages may indicate complex conversations
Users	Active, new, and returning user counts. Track audience growth and how often users come back

### Automated Answers {% hint style="warning" %} Automated Answers are only supported for older agent templates. Agents built with modern templates do not use them, so this tab will only contain the "DEFAULT-FALLBACK" entry. {% endhint %} The Automated Answers tab tracks how often each automated answer in your workflows was triggered. Use this to identify which pre-built responses appear most frequently and whether they align with actual user needs. ### LiveChat The LiveChat tab tracks how your support team handles conversations that escalate beyond the AI agent. Some metrics in this tab, such as missed chats and response times, are only available when using the Helvia LiveChat plugin. The key metric here is the containment rate: the percentage of conversations the agent resolved without human help. A rising containment rate means your workflows are improving. The remaining metrics measure how well your LiveChat team handles incoming requests, from how quickly they respond to how many chats go unanswered. | Metric | What It Tells You | | ----------------------- | --------------------------------------------------------------------------------------------------------------------------------- | | **Containment Rate** | Percentage of sessions resolved by the AI agent without escalating to a team member | | **Missed Chats** | Ratio of missed to received LiveChat requests. A high miss rate may indicate staffing gaps or business hours that need adjustment | | **Avg. First Response** | Time from when a user enters the queue to the first reply from a team member | | **Avg. Response** | Average time between consecutive replies during the conversation | | **Session Duration** | Average, shortest, and longest LiveChat session length | ### Generic Flows The Generic Flows tab shows interaction distribution across your *generic* workflows. Use it to understand which entry points and workflows users reach most, helping you prioritize where to invest in improvements. ### Surveys *Survey* workflows collect structured input from users during a conversation. Here you can see how many sessions included a survey, how many users completed it, and how many abandoned it before finishing. Use this to evaluate whether your survey placement and length are working. ### User Feedback Ratings collected through *User Feedback* workflows are aggregated here, split into two categories: one for the overall agent experience and one specifically for LiveChat sessions. This separation helps you understand whether satisfaction issues come from the automated workflows or the human support layer. ### Missed Questions Missed Questions provides a higher-level view of unanswered questions across all your agents. For investigating individual missed questions in context, see [Missed Questions](/observatory/sessions.md#missed-questions) in Sessions. The tab shows the proportion of missed to answered questions so you can gauge overall knowledge coverage at a glance. A ranked table lists the top 100 most frequently missed questions, and a trend chart tracks how missed question volume changes day by day. Spikes in the trend may indicate new user needs or workflow changes that introduced gaps. ### CSAT Customer Satisfaction Score (CSAT) measures user satisfaction through opinion scale surveys triggered by the CSAT node in your workflows. The overall score is displayed as a gauge with the aggregate percentage and average rating. If your survey has multiple sections, the tab breaks down scores per section so you can identify which aspects of the experience score well and which need attention. Use the dropdown filters to view a specific section or switch between score percentage and raw ratings over time. The usage chart compares how often the CSAT survey appeared versus how often users actually responded, helping you evaluate whether the survey triggers at the right moment in the conversation. ### Best Practices * **Check your filters first:** The date range and agent filter apply across all tabs. If metrics seem off, verify these are set correctly * **Start with Summary:** Use the Summary tab for a quick health check before diving into specific areas * **Monitor containment rate:** Track how well your agent resolves conversations without escalating to LiveChat. A rising containment rate means your workflows are improving * **Share with stakeholders:** Use the PDF export to share analytics with team members who do not have platform access {% hint style="success" %} You can now track agent performance across all eight analytics tabs, share dashboards with your team, and export them as PDFs. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.helvia.ai/observatory/analytics.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.

:calendar:

Date Range

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Agents

:tags:

Tags

:chart-pie:

Donut Charts

:chart-line:

Time Series

:gauge-high:

Gauge Charts

:table:

Data Tables

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Engagement

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Sessions

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User Interactions

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Users