For training, KPIs like course completion rates, post-training assessments, and real-world application of skills guide improvements in educational programs and materials. These indicators help ensure that users receive timely, competent assistance, and that training is effective and aligned with the actual needs of the users. Consequently, KPIs enable continuous improvement by identifying areas for investment and highlighting successful strategies, directly impacting user productivity and overall IT service quality.
KPI |
Definition
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Business Insights [?]
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Measurement Approach
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Standard Formula
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Average After-Call Work Time More Details |
The average time spent by support agents on follow-up tasks after a call has ended.
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Helps in assessing the efficiency of agents and understanding ancillary tasks related to customer calls.
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Time spent by agents on tasks related to the call after the call has ended, such as updating records or sending emails.
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(Total Time Spent on After-Call Work / Total Number of Calls)
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- An increasing after-call work time may indicate more complex issues being handled by support agents.
- A decreasing after-call work time can signal improved efficiency in handling follow-up tasks or better training for support agents.
- What are the common types of follow-up tasks that contribute to the after-call work time?
- Are there specific areas or skills where support agents may need additional training to reduce after-call work time?
- Implement automated systems for documentation and follow-up tasks to reduce manual work for support agents.
- Provide ongoing training and resources for support agents to improve their efficiency in handling follow-up tasks.
- Analyze call data to identify patterns and trends that could help in streamlining follow-up processes.
Visualization Suggestions [?]
- Line charts showing the average after-call work time over different time periods to identify trends.
- Stacked bar charts comparing after-call work time by support agent or team to identify variations and areas for improvement.
- High after-call work time can lead to longer resolution times and customer dissatisfaction.
- Chronic high after-call work time may indicate the need for process improvements or additional resources.
- Customer relationship management (CRM) systems with integrated after-call work time tracking and task management features.
- Workflow automation tools to streamline follow-up processes and reduce manual effort.
- Integrate after-call work time data with customer satisfaction surveys to understand the impact of follow-up tasks on customer experience.
- Link after-call work time tracking with performance management systems to identify training and development needs for support agents.
- Reducing after-call work time can lead to faster resolution of customer issues and improved customer satisfaction.
- However, overly aggressive reduction targets may impact the quality of follow-up tasks and overall customer experience.
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Average Handling Time (AHT) More Details |
The average time it takes to resolve a support ticket or call, from initial contact to resolution.
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Indicates overall efficiency of agents in resolving customer issues and managing their time.
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The sum of talk time, hold time, and after-call work time divided by the number of calls handled.
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(Total Talk Time + Total Hold Time + Total After-Call Work Time) / Total Number of Calls Handled
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- A decreasing AHT may indicate improved efficiency in resolving support issues or better-trained support staff.
- An increasing AHT could signal growing complexity of support tickets or a need for additional training or resources.
- Are there common reasons for prolonged resolution times, such as technical complexity or lack of expertise?
- How does our AHT compare with industry benchmarks or best practices?
- Invest in additional training for support staff to improve their technical skills and problem-solving abilities.
- Implement knowledge management systems to provide quick access to solutions for common issues.
- Regularly review and update support processes to streamline ticket resolution and reduce unnecessary delays.
Visualization Suggestions [?]
- Line charts showing AHT over time to identify long-term trends and seasonal variations.
- Stacked bar charts to compare AHT across different support teams or types of issues.
- High AHT can lead to customer frustration and dissatisfaction, impacting overall customer experience.
- Consistently increasing AHT may indicate systemic issues that could affect the overall efficiency of the support function.
- Customer relationship management (CRM) systems with built-in support ticket management and tracking capabilities.
- Performance analytics tools to identify patterns and bottlenecks in the support process.
- Integrate AHT tracking with customer feedback systems to understand the impact of support performance on customer satisfaction.
- Link AHT data with employee performance evaluations to identify training needs and recognize top performers.
- Reducing AHT can lead to improved customer satisfaction and loyalty, positively impacting long-term business performance.
- However, overly aggressive targets for AHT reduction may lead to rushed or incomplete resolutions, compromising support quality.
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Average Time to Answer (ATA) More Details |
The average time it takes for a support agent to answer a user's call.
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Measures the accessibility of support and can highlight staffing or routing inefficiencies.
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The average amount of time it takes for a call to be answered after it has been routed to an agent.
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(Total Time Taken to Answer Calls / Total Number of Calls Answered)
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- An increasing average time to answer may indicate a growing backlog of user calls or a decrease in support agent efficiency.
- A decreasing average time to answer could signal improved support processes, increased staffing, or better training for support agents.
- Are there specific times of the day or week when the average time to answer is consistently higher?
- How does our average time to answer compare with industry benchmarks or customer expectations?
- Implement call routing and queuing systems to distribute calls more evenly among support agents.
- Provide additional training or resources to support agents to improve their efficiency and effectiveness in handling user calls.
- Regularly review and optimize support processes to identify and eliminate bottlenecks.
Visualization Suggestions [?]
- Line charts showing the average time to answer over different time periods (e.g., daily, weekly, monthly).
- Bar graphs comparing the average time to answer across different support teams or individual support agents.
- A consistently high average time to answer can lead to user frustration and dissatisfaction.
- Long wait times may result in users seeking alternative support channels or solutions, impacting user retention and loyalty.
- Call center software with real-time monitoring and reporting capabilities to track and analyze average time to answer.
- Customer relationship management (CRM) systems to capture and analyze user interactions and support history.
- Integrate average time to answer data with workforce management systems to optimize staffing levels based on call volume and patterns.
- Link support metrics with customer feedback and satisfaction data to understand the impact of average time to answer on user experience.
- Reducing the average time to answer can improve user satisfaction and loyalty, leading to higher customer lifetime value.
- However, increasing staffing or resources to decrease the average time to answer may impact operational costs and profitability.
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CORE BENEFITS
- 45 KPIs under User Support and Training
- 15,468 total KPIs (and growing)
- 328 total KPI groups
- 75 industry-specific KPI groups
- 12 attributes per KPI
- Full access (no viewing limits or restrictions)
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Call Abandonment Rate More Details |
The percentage of inbound support calls that are abandoned by the caller before reaching a support agent.
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Reveals customer frustration or possible insufficiencies in call queue management.
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The percentage of calls that are abandoned by the customer before speaking to an agent.
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(Total Number of Abandoned Calls / Total Number of Calls Offered) * 100
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- An increasing call abandonment rate may indicate longer wait times or inadequate support staffing.
- A decreasing rate could signal improved call handling processes or better customer service satisfaction.
- Are there specific times of the day or week when call abandonment rates tend to be higher?
- What are the common reasons cited by callers for abandoning their support calls?
- Implement call routing and queuing systems to distribute calls more evenly among support agents.
- Provide self-service options for common support issues to reduce the volume of inbound calls.
- Regularly review and optimize staffing levels based on call volume patterns.
Visualization Suggestions [?]
- Line charts showing call abandonment rates over different time periods (e.g., daily, weekly, monthly).
- Comparison bar charts to visualize call abandonment rates across different support channels or teams.
- High call abandonment rates can lead to customer frustration and dissatisfaction.
- Chronic call abandonment may indicate underlying issues in support processes or resource allocation.
- Call center management software with real-time monitoring and reporting capabilities.
- Customer relationship management (CRM) systems to track customer interactions and support history.
- Integrate call abandonment rate data with customer satisfaction surveys to understand the impact on overall customer experience.
- Link support call data with workforce management systems to optimize staffing and scheduling.
- Reducing call abandonment rates can improve customer retention and loyalty.
- However, increasing support resources to lower abandonment rates may impact operational costs.
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Call Transfer Rate More Details |
The frequency with which calls are transferred from one agent to another or to a different support level.
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Highlights potential training gaps or mismatches in call routing.
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The percentage of calls that are transferred from the initial agent to another agent or department.
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(Total Number of Transferred Calls / Total Number of Calls Handled) * 100
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- An increasing call transfer rate may indicate a lack of training or knowledge among support agents.
- A decreasing rate could signal improved agent efficiency or better routing of calls to the appropriate support level.
- Are there specific types of calls that are frequently being transferred?
- How does our call transfer rate compare with industry benchmarks or best practices?
- Provide additional training and resources for support agents to handle a wider range of issues without transferring calls.
- Implement call routing and escalation protocols to ensure calls are directed to the most qualified agent or support level from the start.
- Regularly review and update knowledge bases and support documentation to address common issues that lead to call transfers.
Visualization Suggestions [?]
- Line charts showing the trend of call transfer rates over time.
- Pie charts to visualize the distribution of transferred calls by issue type or support level.
- High call transfer rates can lead to customer frustration and dissatisfaction.
- Frequent call transfers may indicate a need for process improvements or additional resources in specific areas of support.
- Call center software with reporting and analytics capabilities to track call transfer rates and patterns.
- Customer relationship management (CRM) systems to capture and analyze customer interactions that result in call transfers.
- Integrate call transfer rate data with customer satisfaction surveys to understand the impact of transfers on customer experience.
- Link call transfer metrics with workforce management systems to optimize staffing and training based on transfer patterns.
- Reducing call transfer rates can improve customer satisfaction and retention, leading to long-term business growth.
- However, changes in call transfer protocols may require adjustments in agent workflows and training, impacting short-term productivity.
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Change Request Fulfillment Time More Details |
The time taken to implement a change requested by a user in the IT system or services.
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Assesses the responsiveness and effectiveness of change management processes.
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The time taken to complete a change request from the time it was submitted.
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(Total Time to Complete Change Requests / Total Number of Change Requests Completed)
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- Increasing change request fulfillment time may indicate resource constraints or inefficient change management processes.
- Decreasing time can signal improved agility in responding to user needs or better automation of change implementation.
- Are there recurring types of changes that consistently take longer to fulfill?
- How does our change request fulfillment time compare with industry benchmarks or best practices?
- Implement automated change management tools to streamline and expedite the fulfillment process.
- Regularly review and optimize change management workflows to identify and eliminate bottlenecks.
- Invest in training and upskilling for IT staff to improve their ability to implement changes efficiently.
Visualization Suggestions [?]
- Line charts showing change request fulfillment time over different time periods to identify trends.
- Stacked bar charts comparing fulfillment time for different types of changes to pinpoint areas for improvement.
- Extended fulfillment time can lead to user frustration and decreased confidence in IT services.
- Consistently long fulfillment times may indicate underlying issues in IT infrastructure or resource allocation.
- Change management software like ServiceNow or Jira to track and manage change requests more effectively.
- Performance monitoring tools to identify and address bottlenecks in the change fulfillment process.
- Integrate change request fulfillment time with incident management systems to understand the impact of changes on system stability.
- Link with project management tools to align change implementation with broader IT initiatives and priorities.
- Reducing change request fulfillment time can enhance user satisfaction and productivity, leading to improved overall IT service quality.
- However, overly aggressive reduction efforts may compromise the thoroughness and quality of change implementation, potentially leading to system instability or errors.
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In selecting the most appropriate User Support and Training KPIs from our KPI Library for your organizational situation, keep in mind the following guiding principles:
It is also important to remember that the only constant is change—strategies evolve, markets experience disruptions, and organizational environments also change over time. Thus, in an ever-evolving business landscape, what was relevant yesterday may not be today, and this principle applies directly to KPIs. We should follow these guiding principles to ensure our KPIs are maintained properly:
By systematically reviewing and adjusting our User Support and Training KPIs, we can ensure that your organization's decision-making is always supported by the most relevant and actionable data, keeping the organization agile and aligned with its evolving strategic objectives.