By tracking relevant KPIs, such as first response time, ticket resolution time, and customer satisfaction scores, support managers can make data-driven decisions to enhance service quality and efficiency. These metrics also allow for benchmarking against industry standards, fostering a culture of continuous improvement. Moreover, KPIs can motivate technical support staff by setting clear targets and recognizing achievements, which in turn can lead to improved team performance and higher levels of customer service.
KPI |
Definition
|
Business Insights [?]
|
Measurement Approach
|
Standard Formula
|
Abandonment Rate More Details |
The percentage of customers who hang up or leave the queue before reaching a support representative.
|
Indicates customer frustration or dissatisfaction with wait times, potentially signaling a need for process improvement or additional resources.
|
Percentage of calls or contacts that are ended by the customer before reaching an agent.
|
(Total Number of Abandoned Calls / Total Number of Incoming Calls) * 100
|
- An increasing abandonment rate may indicate longer wait times or inadequate staffing levels.
- A decreasing rate could signal improvements in call handling processes or customer service satisfaction.
- What are the average wait times before customers abandon the queue?
- Are there specific times of the day or week when abandonment rates tend to spike?
- Implement call routing and queuing systems to distribute calls more evenly among support representatives.
- Provide customers with estimated wait times or offer call-back options to reduce abandonment rates.
Visualization Suggestions [?]
- Line charts showing abandonment rates over different time periods (daily, weekly, monthly).
- Comparison bar charts to visualize abandonment rates across different support channels or teams.
- High abandonment rates can lead to customer frustration and dissatisfaction.
- Consistently high rates may indicate systemic issues in the support process that need to be addressed.
- Call center software with real-time monitoring and reporting capabilities to track abandonment rates.
- Customer relationship management (CRM) systems to analyze customer interactions and identify patterns leading to abandonment.
- Integrate abandonment rate data with customer feedback systems to understand the impact on overall satisfaction.
- Link with workforce management tools to optimize staffing levels based on call volume and peak abandonment periods.
- Reducing abandonment rates can lead to improved customer retention and loyalty.
- However, overstaffing to minimize abandonment rates may increase operational costs.
|
Agent Turnover Rate More Details |
The rate at which support staff leave and are replaced within the technical support team.
|
Provides an insight into the overall work environment and satisfaction of support agents, which can affect service quality.
|
Measures the percentage of agents leaving the company within a certain timeframe.
|
(Total Number of Agents Who Left / Average Number of Agents Employed) * 100
|
- A rising agent turnover rate may indicate issues with employee satisfaction, training, or management.
- A decreasing rate could signal improved retention strategies, better hiring practices, or a positive work environment.
- Are there common reasons why support staff are leaving the team?
- How does our turnover rate compare with industry benchmarks or similar organizations?
- Invest in employee development and training programs to improve job satisfaction and retention.
- Conduct regular employee feedback surveys to identify and address any underlying issues causing turnover.
- Implement mentorship programs or career advancement opportunities to increase employee engagement and loyalty.
Visualization Suggestions [?]
- Line charts showing the trend of turnover rate over time.
- Pie charts to visualize the reasons for turnover (e.g., voluntary resignations, terminations, retirements).
- High turnover rates can lead to decreased productivity, lower morale, and increased recruitment costs.
- Consistently high turnover may indicate systemic issues within the organization that need to be addressed.
- Employee engagement and feedback platforms like Officevibe or TINYpulse to gather insights and improve workplace satisfaction.
- Human resource management systems (HRMS) to track turnover rates and analyze employee data for patterns and trends.
- Integrate turnover rate data with performance management systems to identify correlations between employee performance and retention.
- Link turnover rate with recruitment and onboarding processes to improve the quality of new hires and reduce turnover.
- Reducing turnover can lead to a more stable and experienced support team, improving overall customer satisfaction and service quality.
- However, investing in retention strategies may initially increase costs but can lead to long-term benefits in employee loyalty and performance.
|
Average Handle Time (AHT) More Details |
The average duration of a complete customer interaction, including call time, hold time, and post-call tasks.
|
Helps in assessing the efficiency of agents and identifying opportunities for training to improve speed and effectiveness of customer issue resolution.
|
The average duration of a single transaction, including hold time, talk time, and after-call work.
|
(Total Talk Time + Total Hold Time + Total After-Call Work) / Total Number of Calls Handled
|
- A decreasing AHT may indicate improved call handling processes or better-trained support staff.
- An increasing AHT could signal issues with system performance, increased call complexity, or inadequate staffing levels.
- Are there specific types of calls that consistently take longer to resolve?
- How does our AHT compare with industry standards or benchmarks for similar organizations?
- Provide additional training for support staff to improve call resolution efficiency.
- Implement call routing and queuing systems to ensure calls are directed to the most appropriate agents.
- Regularly review and update call scripts and knowledge base articles to address common customer issues more efficiently.
Visualization Suggestions [?]
- Line charts showing AHT over time to identify trends and seasonal variations.
- Stacked bar charts comparing AHT by support team or individual agent to identify performance variations.
- High AHT can lead to customer frustration and dissatisfaction, impacting customer retention and loyalty.
- Consistently low AHT may indicate rushed or incomplete customer interactions, leading to poor service quality.
- Call center software with built-in AHT tracking and reporting capabilities.
- Customer relationship management (CRM) systems to capture and analyze customer interaction data.
- Integrate AHT tracking with quality management systems to ensure that shorter call times do not compromise service quality.
- Link AHT data with customer satisfaction surveys to understand the impact of call duration on customer experience.
- Reducing AHT can lead to improved customer satisfaction and loyalty, but may require additional resources or process changes.
- Conversely, excessively low AHT may result in rushed interactions and reduced service quality, impacting long-term customer relationships.
|
CORE BENEFITS
- 47 KPIs under Technical Support
- 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)
FlevyPro and Stream subscribers also receive access to the KPI Library. You can login to Flevy here.
|
IMPORTANT: 13 days left until the annual price is increased from $99 to $149.
$99/year
Average Resolution Time More Details |
The average amount of time taken to resolve customer support tickets.
|
Shows the effectiveness of the support team and can help identify the complexity of problems faced by customers.
|
Average amount of time taken to resolve customer issues.
|
Total Time Taken to Resolve Issues / Total Number of Resolved Issues
|
- Increasing average resolution time may indicate growing complexity of support issues or inadequate training for support staff.
- Decreasing average resolution time can signal improved efficiency in handling customer inquiries or better access to necessary resources.
- Are there common reasons why support tickets take longer to resolve?
- How does our average resolution time compare with industry standards or benchmarks?
- Invest in additional training for support staff to improve their skills and knowledge.
- Implement a knowledge base or self-service options to empower customers to find solutions on their own.
- Regularly review and update support processes to identify and eliminate bottlenecks.
Visualization Suggestions [?]
- Line charts showing the average resolution time over time to identify trends and patterns.
- Stacked bar charts comparing resolution times across different support channels or product categories.
- High average resolution times can lead to customer frustration and dissatisfaction.
- Prolonged resolution times may indicate underlying issues in support operations that need to be addressed.
- Customer relationship management (CRM) software to track and manage support tickets efficiently.
- Help desk and ticketing systems to streamline the resolution process and prioritize tasks.
- Integrate average resolution time tracking with customer feedback systems to understand the impact of support experiences on satisfaction.
- Link support ticket data with product development and quality assurance processes to address recurring issues.
- Reducing average resolution time can lead to higher customer satisfaction and retention.
- However, overly aggressive targets for resolution time may compromise the quality of support provided.
|
Average Wait Time More Details |
The average time customers spend waiting in the queue before they are connected to a support representative.
|
Reflects how well staffed and efficient the support center is, directly impacting customer satisfaction.
|
Average amount of time customers spend waiting before reaching an agent.
|
Total Wait Time / Total Number of Calls Answered
|
- Increasing average wait time may indicate understaffing or inefficient support processes.
- Decreasing wait time can signal improved resource allocation or enhanced support efficiency.
- Are there specific times of the day or week when wait times tend to be longer?
- How does our average wait time compare with industry standards or customer expectations?
- Implement call routing and queuing systems to distribute incoming support requests more evenly.
- Invest in additional training for support representatives to handle inquiries more efficiently.
- Consider offering self-service options to reduce the volume of incoming support calls.
Visualization Suggestions [?]
- Line charts showing average wait time over different time periods (e.g., daily, weekly, monthly).
- Bar graphs comparing wait times across different support channels (e.g., phone, chat, email).
- Long wait times can lead to customer frustration and dissatisfaction, potentially resulting in customer churn.
- Consistently high wait times may indicate systemic issues that could impact overall customer service quality.
- Customer relationship management (CRM) systems with built-in support ticketing and queuing features.
- Call center management software to monitor and optimize support representative performance.
- Integrate average wait time tracking with customer satisfaction surveys to understand the impact of wait times on overall customer experience.
- Link support queuing data with workforce management systems to optimize staffing levels based on demand.
- Reducing average wait time can lead to higher customer satisfaction and retention, positively impacting overall customer lifetime value.
- However, overly aggressive reduction efforts may strain support resources and lead to decreased service quality.
|
Call Handling Time More Details |
The average time support staff take to handle a customer call, including talk time and after-call work.
|
Provides a complete picture of the time investment needed per call, useful for workforce optimization.
|
Time spent by an agent on a call, including hold time and after-call work.
|
Total Call Duration (Talk Time + Hold Time + After-Call Work) / Total Number of Calls
|
- Call handling time may increase over time due to more complex customer issues or inadequate training.
- A decreasing trend could indicate improved efficiency in issue resolution or better call management processes.
- Are there specific types of calls that consistently take longer to handle?
- How does our call handling time compare to industry benchmarks or best practices?
- Provide additional training or resources for support staff to handle common issues more efficiently.
- Implement call routing and prioritization systems to ensure more urgent or complex calls are handled by the appropriate staff.
- Regularly review and update call scripts and knowledge bases to streamline issue resolution.
Visualization Suggestions [?]
- Line charts showing the average call handling time over different time periods (e.g., daily, weekly, monthly).
- Stacked bar charts comparing call handling time by support staff or by type of call.
- Long call handling times can lead to customer frustration and dissatisfaction.
- Inefficient call handling may result in increased operational costs and reduced capacity to handle more calls.
- Call center software with reporting and analytics capabilities to track and analyze call handling times.
- Customer relationship management (CRM) systems to provide support staff with relevant customer information and history during calls.
- Integrate call handling time data with customer satisfaction surveys to understand the impact of call duration on customer experience.
- Link call handling time with workforce management systems to optimize staffing levels based on call volume and duration.
- Reducing call handling time can improve customer satisfaction but may require investment in training and technology.
- Conversely, excessively short call handling times may sacrifice quality of service and lead to unresolved customer issues.
|
In selecting the most appropriate Technical Support 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 Technical Support 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.