Analytics

Reports give an insight into your Virtual Assistant performance. With the data in hands, you can get a better understanding of what parts of your chatbot Stories work and what interactions require additional improvements. The Reports section provides in-depth knowledge about your Virtual Assistant. Here you can analyze the occurrence of interactions, compare Stories, browse data from various periods and much more.

API: Our analytics module has an API to obtain and consume all data. Request documentation and access to our team if you need to use this service…

General metrics

Real-Time

The Real-Time dashboard provides a live view of agent performance and chat activity across the customer service team. This feature is essential for supervisors and support leads to monitor operational efficiency and react instantly to shifts in workload or user demand.

Key Metrics Displayed

• Users Assigned to Agents: Total number of users currently being handled by available agents.
• Users in Queue: Number of users waiting for an agent response.
• Agent Workload: Average percentage of active workload based on agent capacity.
• Bot to Human Transfer Rate: Percentage of conversations escalated from bots to human agents.
• Average Wait Time: Total average wait time (in minutes) for users in the queue.

Agent Status Table

A real-time view of all support agents with the following information:

• Name: Agent’s full name.
• Status: Online or Offline indicator.
• Workload: Number of ongoing conversations compared to their capacity (e.g., 1/3 with a visual progress bar and %).
• Languages: List of supported languages per agent, helping route users to the most suitable person.

This live module enables customer service teams to make fast, data-driven decisions—like redistributing workload, prioritizing urgent chats, or bringing agents online—ensuring optimal customer experience at all times.

Main dashboard

The Main Dashboard offers a comprehensive view of your AI and human agent performance over time. Designed to provide strategic insights at a glance, this dashboard consolidates key data points to help you understand how conversations are evolving, how users interact across channels, and how efficiently your agents are responding.

It allows filtering by date, agents, language, and channels, making it easy to track performance trends, identify areas for improvement, and support decision-making with real data. Visual charts and summary metrics provide clarity on user behavior, session dynamics, and message distribution—empowering you to optimize operations across both AI and human support teams.

Whether you’re tracking adoption, efficiency, or engagement, the Main Dashboard is your command center for continuous improvement and service excellence.

Agent Analytics

The Agent Analytics dashboard gives you a detailed overview of how your support agents are performing—both collectively and individually. This section focuses on human agent involvement, helping you understand how, when, and why agents step into conversations.

It includes high-level metrics on chat assignments, manual escalations, agent participation, and timeout behavior. Through visual escalation analysis, you can also detect trends by language and channel, allowing you to identify where agent intervention is most needed.

This feature is designed to optimize team performance, monitor efficiency, and detect potential gaps in automation or staffing—empowering managers to make better resourcing and training decisions with data at hand.

Social Listening

Our Social Listening Dashboard allows you to track and understand what users are talking about when interacting with your AI agent. By detecting key topics in real time, it gives you powerful insights into customer concerns, recurring themes, and potential service opportunities. This feature is ideal for identifying trends, prioritizing issues, and aligning support efforts with what truly matters to users.

You can create and manage custom topics, automatically tag user mentions, and monitor how those topics evolve over time—turning raw conversation data into strategic knowledge.

Social listening analytics

The Analytics tab provides a visual summary of how different topics are being mentioned across conversations within a selected date range. It includes:

• Topic Distribution: A pie chart showing how mentions are spread across defined topics, helping you quickly identify dominant conversation areas.
• Top Topics by Mentions: A bar chart ranking topics by the number of mentions, giving you a clear view of the most discussed issues.

Mentions

The Mentions section of the Social Listening Dashboard displays all user interactions that have been automatically or manually tagged under a specific topic. This view allows teams to review real examples of user queries related to each topic, ensuring full transparency and context.

By clicking on a topic, you can explore every conversation snippet associated with it—making it easy to validate classifications, analyze user intent, and refine topic definitions as needed. This is especially useful for quality assurance, trend verification, and training both AI models and human agents.

Whether you’re monitoring critical issues like cancellations or tracking emerging concerns, the Mentions tab gives you direct access to the voice of your customers—topic by topic.

Topics

In the Topics tab, you can define and manage the key themes you want to track in conversations. Simply click “Add topic”, give it a name, and choose a color to visually identify it across the dashboard.

This is where you shape your listening strategy—by creating relevant topics, you ensure your AI agent and analytics focus on what matters most to your business. Topics can be edited, toggled for visibility, or deleted at any time, giving you full control and flexibility as user needs evolve.

Activity report

The Activity Report tab provides a detailed log of recent user interactions with your AI agent, allowing you to monitor activity at a granular level. It includes essential metadata such as user name, contact information, language, channel used, timestamp, and whether the conversation required human escalation.

You can filter activity by date and download the full report as a CSV file for deeper analysis or integration into external reporting tools. This view is ideal for compliance, auditing, customer support tracking, and identifying patterns in user behavior or escalation trends.

With the Activity Report, all your conversational data is at your fingertips—fully searchable, exportable, and actionable.