Conversations

Conversation Overview

This section provides an overview of conversations over a specific period. The chart helps visualize the number of new, closed, and reopened conversations, facilitating the analysis of customer support activity and efficiency.

• New Conversations: Represented in blue, these are the conversations initiated by users during the period.

• Closed Conversations: Represented in green, these are the conversations that were closed during the period.

• Reopened Conversations: Represented in red, these are the conversations that were reopened after being closed.

Usefulness of the Chart

• Support Efficiency: By comparing the numbers of new, closed, and reopened conversations, it is possible to evaluate the support team's efficiency and identify areas needing improvement.

• Activity Peaks Identification: The chart shows the days with the highest and lowest activity, allowing for resource allocation adjustments to improve support during peak times.

Below is a visual example of the chart:

Open

Opened vs. Closed Conversations

This section presents a comparison between the number of open and closed conversations over a specific period. The chart helps visualize customer support efficiency and identify potential bottlenecks or periods of high demand.

• Opened Conversations: Represented in blue, these are the conversations initiated by users during the period.

• Closed Conversations: Represented in green, these are the conversations that were closed during the period.

Usefulness of the Chart

• Support Efficiency: By comparing the numbers of open and closed conversations, it is possible to evaluate the support team's efficiency. Ideally, the number of closed conversations should be close to the number of open conversations.

• Activity Peaks Identification: The chart shows the days with the highest and lowest activity, allowing for resource allocation adjustments to improve support during peak times.

Below is a visual example of the chart:

Open

Heatmap of Opened and Closed Conversations

In this section, we present heatmaps showing open and closed conversations throughout the week, segmented by hour of the day. These charts help identify activity patterns, allowing for optimized resource allocation and support planning.

Heatmap of Opened Conversations

• The chart on the left shows open conversations by day of the week and hour of the day. Darker colors indicate periods of higher activity.

• This heatmap is useful for identifying when users are most likely to initiate conversations, allowing for adjustments in the support team to cover peak times.

Heatmap of Closed Conversations

• The chart on the right shows closed conversations by day of the week and hour of the day. Similar to the heatmap of open conversations, darker colors indicate higher activity.

• This chart helps understand customer support efficiency and whether there are periods when conversations are closed more quickly.

Below is a visual example of these charts:

Opened Conversations by Type

In this section, we present an analysis of open conversations categorized by type. This metric is essential for understanding the dynamics of interactions, distinguishing between new users and returning users.

Opened Conversations by New and Returning Users

• The bar chart shows the number of open conversations by new users and returning users over the days. This helps us monitor how different types of users are interacting with the system.

• The donut chart on the right presents the overall proportion of open conversations by new and returning users, offering a clear view of the distribution of interactions.

Below is a visual example of these charts:

Closed Conversations by Type

In this section, we present an analysis of closed conversations categorized by type. This metric is important for understanding customer behavior and support efficiency.

New and Returning Closed Conversations

• The bar chart shows the number of new and returning conversations that were closed over the days. This helps us monitor how customers are interacting with support over time.

• The donut chart on the right presents the overall proportion of new versus returning closed conversations, offering a clear view of the distribution of closed interactions.

Below is a visual example of these charts:

Open Conversations by Source

In this section, we present an analysis of open conversations categorized by source. This metric is essential for understanding the origin of interactions and evaluating the effectiveness of different support channels.

Open Conversations by Bot Users, Agents, and Bot

• Bot user means bot user/contacts initiated, Agent means live chat agent, Bot means bot automation.

• The bar chart shows the number of open conversations by bot users, agents, and the bot itself over the days. This helps us monitor how different channels are being utilized over time.

• The donut chart on the right presents the overall proportion of open conversations by each source, offering a clear view of the distribution of initiated interactions.

Below is a visual example of these charts:

Conversations and Conversation Closures

In this section, we provide an overview of the number of conversations and how they were closed, either by an agent or a bot. Analyzing these metrics can help us better understand customer interaction with our support system.

New and Returning Conversations

• The bar chart at the top shows the number of new and returning conversations over the days. It is important to track this metric to understand the flow of interactions and customer loyalty to the support system.

• The donut chart on the right presents the overall proportion of new versus returning conversations, offering a clear view of the distribution.

Closed Conversations by Source

• The second bar chart illustrates the number of conversations closed by agents and bots over time. Monitoring this information helps identify the efficiency of each source in closing cases.

• The donut chart on the right presents the overall proportion of conversations closed by agents and bots, providing an overview of each one's performance.

Below is a visual example of these charts: