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With the information collected by various modules (interactions, tickets, tasks, etc.), Sagicc generates a dashboard with statistics on the work and performance of each campaign. Users with administrator and supervisor roles can access the dashboard for each campaign, analyze the presented information, and make decisions to help improve productivity and service quality. By default, when entering the Campaign Dashboard, the information for the campaign selected by the user in the Campaign Selector will be displayed.
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Only users with administrator and supervisor the "Administrator" and "Supervisor" roles can access the Campaign 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 working on the selected campaign. At the top of the dashboard, there are filters that allow you to 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 use advanced filters.
Advanced filters for the dashboard include the following:
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Start Date: Filters the dashboard information, showing only information for tickets created from this date onward.
End Date: Filters the dashboard information, showing only information for tickets created before this date.
Campaigns: Includes information from other selected campaigns in addition to the default campaign.
Users: Includes information for all users or shows only information for specific users.
The 
Below is the description of the information, tables, and graphs displayed charts available in the various different sections of the campaign dashboard are described belowthe 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 in the campaign within the specified date range specified in the filter, grouped by each available ticket status. This information allows supervisors to gain a clear view of the progress and distribution of the workload of the users.
Tickets by User
This section shows the total number of campaign tickets created in the campaign within the specified date range specified in the filter, grouped by each available ticket status and by the assigned user. The table information can be downloaded in Excel format by clicking “Download Data”.
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 the campaign tickets, within the specified date range specified in the filter. This information allows the supervisor to evaluate the productivity and efficiency of users in managing the campaign tickets. It includes the following specific itemsdata:
Tasks created Tasks (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 taskCampaign 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.
Tasks by User
This section shows the total number of tasks performed by agents on the campaign tickets, within the specified date range specified in the filter, grouped by the user assigned to the ticket. The table information can be downloaded in Excel format by clicking “Download Data”.
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 the campaign tickets, within the specified date range specified in the filter, grouped by the main type task field of the task form (configured in the campaign). The table information can be downloaded in Excel format by clicking “Download Data”.
This information allows the supervisor to analyze and segment the tasks in more detail, facilitating informed decision-making.
Tasks by Hour
This section shows the total number of tasks managements performed by agents on the campaign tickets, within the specified date range specified in the filter, grouped by the creation hour of creation. This information allows will allow you to identify the hours of highest and lowest agent productivity for the agents throughout during the workday, helping you to improve operational efficiency.
Recent Tasks
In this section, you can quickly access the latest tickets managed by users in the campaign. The list shows will show basic information for about each managed ticket, and by clicking on the ticket number, you will be redirected to its detailed viewthe management view of the ticket.
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Service Level, Productivity, and Average Handling Time (AHT)
This section shows the total number of interactions received (incoming) or generated (outgoing) by the campaign agents within the specified date range, grouped by channel. This information helps you determine the channels with the highest and lowest interaction volumes, aiding in optimizing your team's resources.
Tickets by Channel
This section shows the number of tickets assigned to the campaign agents and created within the specified date range, grouped by the channel type that generated the ticket. This information helps you determine which channels are most and least used by customers to initiate conversations with the company.
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 agents , within the specified date range specified in the filter, grouped by the hour of interaction creation. This information helps will allow you to identify the hours with the highest and lowest interaction volumes throughout /or lowest volume of interactions during the day, aiding in optimizing helping you optimize your team's resources.
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Interactions by Channel
This section shows the details of the service level, productivity, and average operational time for each of the campaign agents.
total number of interactions received (incoming) or generated (outgoing) by the agents in the campaign, within the date range specified in the filter, and grouped by channel. 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
This section shows the number of tickets assigned to the campaign agents and created within the date range specified in the filter, grouped by the type of channel that generated the ticket. This information will allow you to determine which channels are most and least used by customers to initiate conversations with the company, and focus your strategies on these channels.
SLA
This section shows and compares data related to SLA rules and the compliance or /non-compliance with 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, and another showing the total total number of tickets with violations, i.e., tickets that did not meet non-compliance, meaning tickets where the times for at least one SLA rule metric were not met.
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SLA by User
This section shows the number of tickets in the campaign that met any of the SLA Rule 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.
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SLA by
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Ticket
This section shows the total number of violated metrics (First Response Time or Customer Wait Time) for the campaign tickets, grouped by the user. For example, if two metrics were violated for ticket #123, these will be counted as two violations for the user.
SLA by Ticket
This section shows specific information about tickets, SLA rule compliance, and violations in a table (ticket number, assigned user, metric, compliance or violation of SLA, and event date).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 shows a representation of the distribution according to the number of SLA rule compliances and violations. It is important to note that the calculation is based on whether one or two of the SLA rule metrics are met or violated for a ticket.
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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