# Dashboard The **Dashboard - Team** section provides valuable insights into your conversations, including key metrics about the performance of your agents and bots. You will be able to track a wide range of metrics that help optimize customer engagement and service efficiency.
### Summary 1. **Open Conversations:** The number of currently active, ongoing conversations. 2. **Resolved Conversations:** The count of conversations that have been successfully resolved. 3. **Web Conversations:** The number of conversations originating from the web. 4. **WhatsApp Conversations:** The total number of WhatsApp conversations in the selected time range. 5. **WhatsApp Template Messages:** The number of WhatsApp template messages sent. 6. **WhatsApp Session Messages:** The total number of WhatsApp session messages exchanged. 7. **Conversations:** A summary of both open and resolved conversations. 8. **New Contacts:** The number of new contacts added within the selected time range. 9. **Active Conversations:** The count of ongoing, active conversations. 10. **WhatsApp Business Initiated:** The number of WhatsApp conversations initiated by your business. 11. **WhatsApp User Initiated:** The number of WhatsApp conversations initiated by users. 12. **WhatsApp Free Entry Points:** Conversations started by users via the Click-to-WhatsApp or Call-to-Action buttons. ### Conversation Analytics The **Conversation Analytics** section provides key insights into how your team is performing in terms of handling customer conversations. It offers you a clear picture of important metrics like **First Response Time (FRT)** and **Turnaround Time (TAT)**, helping you assess how efficiently your team is responding to and resolving customer inquiries. #### **Total Conversations** This metric displays the total number of conversations within the chosen time frame, including both **open** and **resolved** conversations. It gives you an overall count of customer interactions. #### **TAT (Turnaround Time)** 1. **What is it?** TAT measures the total time it takes to resolve a conversation from start to finish. 2. **How is it calculated?** TAT starts from the moment a customer initiates a conversation and ends when the issue is fully resolved, whether by an agent or automated bot. 3. **What do we show?** The TAT metric is displayed in hours, giving you a clearer idea of the total time spent from the customer’s first message to resolution. #### **FRT (First Response Time)** 1. **What is it?** FRT measures the time it takes for an agent to respond to a customer's first query. 2. **How is it calculated?** FRT is calculated by measuring the time between the customer’s first message and the first reply from an agent. 3. **What do we show?** Just like TAT, **FRT** is also shown in hours, helping you track and improve your team’s response time over different periods. #### **Active Conversations by Status** This pie chart breaks down the conversations into **assigned** and **unassigned** categories, giving you an overview of how conversations are being managed. It’s useful for understanding the workload distribution across agents and identifying if there are any pending unassigned conversations. #### **Active Conversations by Agents** This bar graph shows the distribution of active conversations across your agents. It provides a breakdown of how many conversations each agent is handling, including both assigned and unassigned conversations. This helps you keep track of your team’s engagement and ensures no one is overloaded.
### **How to Use These Insights** By keeping track of **FRT** and **TAT**, you can identify bottlenecks in your process and optimize your team's performance. For example: * If you notice a high **FRT**, you might want to look at your team’s responsiveness and find ways to speed up their first reply. * A high **TAT** could mean that conversations are taking too long to resolve, signaling a need for process improvements or better resource allocation. Overall, these metrics allow you to continuously improve customer engagement by ensuring your team responds quickly and resolves issues efficiently. With the **Conversation Analytics** dashboard, you can actively monitor and refine your team's performance, ensuring better customer satisfaction. ### Bot Analytics The **Bot Analytics** section gives you a detailed view of how your chatbot is performing and interacting with users. It provides key metrics like session completion rates, session durations, and areas where the bot may need improvement. By analyzing these metrics, you can optimize your bot’s performance and improve the overall user experience. #### **Bot Session** This metric shows the total number of sessions conducted by the bot. A "session" refers to a single interaction between the user and the bot. Tracking the number of sessions helps you understand how many users are engaging with your bot over a given period. This provides a general overview of bot usage. #### **Completed Session** This metric displays the number of sessions where the bot successfully resolved the user’s query and the session was completed. A **Completed Session** indicates that the bot was able to address the user's concern and bring the conversation to a resolution. High completion rates typically signal that the bot is performing well in terms of meeting user needs. #### **Dropped Session** This metric shows how many sessions were abandoned or terminated before the bot could fully resolve the user's query. **Dropped Sessions** indicate potential issues with the bot, such as it failing to answer user questions or users abandoning the session due to frustration. Monitoring this metric allows you to identify where the bot might be struggling and need improvements. #### **Flow Session** This section provides insights into which specific flow or node in the bot the user interacted with. By tracking **Flow Sessions**, you can see where users are engaging with the bot and which parts of the conversation flow are most popular. This helps you understand user behavior and identify areas to improve the bot's conversational flow. #### **Average Bot Session Length** This metric calculates the average duration of a bot session. Monitoring the **Average Session Length** helps you see how long users are interacting with the bot. If the sessions are unusually long, it might indicate that users are struggling to find answers or that the bot is engaging them too much. If sessions are too short, it could mean users are quickly abandoning the bot without getting their needs met. #### **Top Drop Cards** This section highlights specific elements or cards in the bot that cause users to drop off or abandon the session. Identifying **Top Drop Cards** gives you insights into which parts of the bot’s flow or conversation are leading to user abandonment. By optimizing or adjusting these areas, you can reduce drop-offs and improve the bot's effectiveness.
### **How to Use These Insights** By analyzing the data in **Bot Analytics**, you can optimize the chatbot to improve user satisfaction. For example: 1. If you notice a high number of **Dropped Sessions**, it’s worth reviewing the sections where the bot is losing users. Are there unclear responses or frustrating interactions? 2. A long **Average Bot Session Length** might suggest users are not getting quick, clear answers, leading to longer interactions than necessary. With the insights from **Bot Analytics**, you can continuously enhance your chatbot’s performance, ensuring it resolves user queries efficiently and effectively. By reducing **Dropped Sessions** and improving session completion rates, you’ll provide a better, more engaging experience for your users. --- # Agent Instructions: 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: ``` GET https://docs.gallabox.com/reports-and-analytics/dashboard.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.