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With the information collected by different various modules , information on (interactions, tickets, and tasks, etc.), Sagicc generates a dashboard with statistics on the work and performance of each campaign. Users with the administrator and supervisor roles can access the dashboard for each campaign and , analyze the presented information, and make decisions to help improve productivity and the service quality of service. By default, when entering the Campaign Dashboard, the information for the campaign selected campaign will be displayed for by the user in the Campaign Selector will be displayed.
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Only users with the administrator or supervisor "Administrator" and "Supervisor" roles can access the Campaign Dashboard. |
Through the side menu, you
Dashboards. Users with the "Supervisor" role will only be able to view the dashboards for the campaigns assigned to them. |
You can access the Campaign Dashboard through the sidebar menu.
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When entering the Campaign Dashboard, you will see several sections with important information about the work and performance of the users who are working on the selected campaign. At the top of the dashboard, you will see a series of there are filters that will allow you to query view information within a specific date range. By default, Sagicc will show information for the current day, but it is also possible to view information for the current week, the current month, or select use advanced filters.
Within the advanced Advanced filters for the dashboard , you will find include the following:
Start Date From: Filters the dashboard information, showing only information for tickets created from this date onward.
End Date To: Filters the dashboard information, showing only information for tickets created before this date.
Campaigns: Includes information from other campaigns by selecting them along with selected campaigns in addition to the default campaign.
Users: Includes information for all users or displays shows only information for specific users.
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The 
Below is the description of the information, tables, and graphs shown in the user dashboard are organized as follows:
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charts available in the different sections of the Campaign Dashboard.
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To integrate the Campaign Dashboard tables and charts into your management reports, documents, or presentations, you can download the information in Excel format by clicking on "Download Data" or as an image by clicking on "Download Visualization". |
Tickets
This section shows and compares the total number of campaign tickets created
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within the date range specified in the filter, grouped by each available ticket status.
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This information allows supervisors to gain a clear view of the progress and distribution of the workload of the users.
Tickets by User
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This section shows the total number of campaign tickets created
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within the date range specified in the filter, grouped by each available ticket status and by the assigned user
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. This information allows supervisors to gain a clear view of the progress and workload distribution for each user.
Tasks
This section shows and compares the total number of tasks performed by agents on campaign tickets
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, within the date range specified in the filter
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. This information allows the supervisor to evaluate the productivity and efficiency of users in managing the campaign tickets. It includes the following specific
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data:
Tasks
createdTasks created on all tickets(only assigned tickets): Shows the total number of tasks performed by users on their assigned tickets.
Tasks (all tickets): Shows the total number of tasks performed by users on all tickets, regardless of assignment.
Tickets managed with at least one task
Campaign Completion: Indicates the total number of tickets that have been managed by users, i.e., those that have at least one task.
Campaign Completion: Measures and compares the proportion of tickets assigned to users that have been managed and closed, versus those that are still pending management.
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Tasks by User
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This section shows the total number of tasks performed by agents on campaign tickets
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, within the date range specified in the filter, grouped by the user assigned to the ticket.
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This information allows the supervisor to evaluate the productivity and efficiency of each user in managing the campaign tickets.
Tasks by Type
This section shows the total number of tasks performed by agents on campaign tickets
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, within the date range specified in the filter, grouped by the main
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task field of the
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task form (configured in the campaign).
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This information allows the supervisor to analyze and segment the tasks in more detail, facilitating informed decision-making.
Tasks by Hour
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This section shows the total number of
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managements performed by agents on campaign tickets
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, within the date range specified in the filter, grouped by the
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creation hour. This information will allow you to
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identify the hours of highest and lowest agent productivity
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during the workday, helping you to improve operational efficiency.
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Recent Tasks
In this section, you can quickly access the latest tickets managed by users in the campaign.
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The list will show basic information about each managed ticket, and by clicking on the ticket number, you will be redirected to the management view of the ticket.
Service Level, Productivity, and Average Handling Time (AHT)
This section shows the percentage of compliance with three key indicators for customer service campaigns: Service Level, Productivity, and Average Handling Time (AHT). It is important to note that the information is broken down by each user in the campaign and is based on the specific parameters configured for that campaign.
Below are the three indicators:
Service Level (SLA): This indicator measures the percentage of tickets that were responded to in the first contact within the time specified in the campaign configuration (Service Level Time). For example, if the service level is configured for 20 seconds and 100 tickets are received, of which 75 are attended to in 20 seconds or less, the service level compliance percentage will be 75%. This percentage reflects the team's efficiency in responding within the agreed time, which is crucial for maintaining high customer satisfaction levels.
Productivity: This indicator reflects the percentage of managements performed compared to the number of tasks expected to be performed according to the campaign configuration (Number of Managements per Agent). For example, if agents are configured for 50 daily managements and only perform 25, the productivity compliance percentage will be 50%. This indicator is essential for evaluating operational efficiency and the team's capacity to meet established expectations.
AHT (Average Handling Time): The AHT compliance percentage is calculated by comparing the actual handling time of the tickets (time from ticket creation to closure) with the average handling time configured in the campaign. If the campaign has an AHT configured for 600 seconds (10 minutes), and out of 50 tickets handled, 40 were resolved in less than 600 seconds, the AHT compliance percentage will be 80%. This indicator is key to measuring how quickly tickets are resolved, which directly impacts customer satisfaction and process efficiency.
Interactions by Hour
This section shows the total number of interactions received (incoming) or generated (outgoing) by the agents in the campaign, within the date range specified in the filter, grouped by the hour of interaction creation. This information will allow you to identify the hours with the highest and/or lowest volume of interactions during the day, helping you optimize your team's resources.
Interactions by Channel
This section shows the total number of interactions received (incoming) or generated (outgoing) by the agents
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in the campaign, within the date range specified in the filter, and grouped by channel.
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This information will allow you to determine the channels with the highest and/or lowest volume of interactions, helping you optimize your team's resources.
Tickets by Channel
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This section shows the number of tickets assigned to
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the campaign agents and created within the date range specified in the filter, grouped by the type of channel that generated the ticket.
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This information will allow you to determine which channels are most and least used by customers to
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initiate conversations with the company
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Service Level: Displays the details of service level, productivity, and average operational time for each of the campaign's agents.
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and focus your strategies on these channels.
SLA
This section shows and compares data related to SLA rules and the compliance/non-compliance with
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the times associated with these rules. You will find an indicator showing the total number of tickets in the campaign for which SLA rules were validated
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, and another showing the total number of tickets with non-compliance, meaning tickets where the times for at least one SLA
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metric were not met.
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SLA by User
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Non-compliance by User: Displays the total number of missed metrics for tickets assigned to the user. This means that if two metrics were missed for ticket #2325, they will be counted as 2 non-compliances for the user.
SLA by ticket: Displays specific information about tickets, compliance, and non-compliance with SLA rules in a table (ticket number, assigned user, metric, whether SLA was met or not, and event date).
SLA compliance effectiveness: Represents the distribution based on the number of compliance and non-compliance with SLA rules. It should be noted that the calculation is based on the fact that a ticket can meet or miss one or two of the SLA rule metrics.
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This section presents a comparison between tickets that met all SLA metrics (First Response Time or Customer Wait Time) and those that failed to meet at least one metric, grouped by the user assigned to the ticket.
SLA by Ticket
This section shows a detailed table of SLA metric compliance or non-compliance for the 20 most recent tickets in the campaign. The table includes the ticket number, the assigned agent, the evaluated metric, the compliance status, and the date corresponding to the compliance or non-compliance.
SLA Compliance Effectiveness
This section offers a detailed comparison between the percentage of tickets that achieved compliance with both SLA metrics and those that failed to meet one of them. The analysis helps to identify the proportion of tickets that reached the established service goals, contrasted with tickets that showed deviations in meeting critical metrics.
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