We have 52 KPIs on Customer Support in our database. KPIs for Customer Support are instrumental for Product Management as they provide quantifiable metrics that reflect the performance and quality of the customer service being provided. These indicators help in identifying patterns in customer inquiries and issues, which can signal areas where the product might require improvement or where additional features could enhance user satisfaction.
KPIs also enable Product Management to gauge the effectiveness of support strategies and initiatives, ensuring that resources are allocated efficiently to improve customer satisfaction and retention. By tracking metrics such as response times, resolution rates, and customer satisfaction scores, Product Managers can make data-driven decisions that align support efforts with overall product strategy and business objectives. Moreover, analyzing KPI trends over time assists in anticipating customer needs and proactively addressing potential product challenges before they escalate.
KPI | Definition | Business Insights [?] | Measurement Approach | Standard Formula |
---|---|---|---|---|
Agent Satisfaction Score | A measure of how satisfied support agents are with their work environment and tools, which can impact the quality of customer service. | Reveals agents' contentment with their work environment, tools, and management, which can impact turnover and customer service quality. | Includes job satisfaction surveys, eNPS scores, and feedback forms. | Average of agent satisfaction survey scores |
Agent Schedule Adherence | The degree to which customer support agents adhere to their scheduled work times and breaks, impacting staffing and service levels. | Helps manage workforce efficiency and predictability of service levels. | Measures the percentage of time agents adhere to their scheduled work times and breaks. | (Total Time Agents Adhere to Schedule / Total Scheduled Time) * 100 |
Agent Turnover Rate | The rate at which customer support agents leave the company, which can impact the continuity and quality of service. | Provides insights into job satisfaction, training effectiveness, and the overall work environment to improve retention strategies. | Calculates the rate at which agents leave the company over a specific period. | (Number of Agents Who Left During a Period / Average Number of Agents During the Period) * 100 |
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Agent Utilization Rate | The percentage of time that support agents are actively engaged in handling customer inquiries, as opposed to being idle or waiting for calls. | Highlights efficiency and potential staffing adjustments required to optimize resources. | Determines the percentage of time agents spend on handling customer interactions versus idle time. | (Total Handle Time + Total After-Call Work Time) / (Total Time Agents are Logged In) * 100 |
Average After-Call Work Time | The average time spent by agents on follow-up tasks after a customer call has been concluded. | Indicates the complexity of follow-up tasks and can highlight training or process improvement opportunities. | Measures the average time spent on work related to the call after the customer interaction is over. | Total After-Call Work Time / Total Number of Calls Handled |
Average Handle Time (AHT) | The average amount of time an agent spends handling a customer interaction, including talk time, hold time, and after-call work. | Provides insight into the efficiency of interactions and identifies opportunities for agent training or process improvements. | Includes talk time, hold time, and after-call work time. | (Total Talk Time + Total Hold Time + Total After-Call Work Time) / Total Number of Calls Handled |
We can categorize Customer Support KPIs into the following types:
Operational Efficiency KPIs measure the effectiveness and efficiency of customer support operations. These KPIs help identify bottlenecks and areas for process improvement. When selecting these KPIs, focus on metrics that directly impact customer satisfaction and operational costs. Examples include Average Handle Time (AHT) and First Call Resolution (FCR).
Customer Satisfaction KPIs gauge how satisfied customers are with the support they receive. These KPIs are crucial for understanding the customer experience and identifying areas for improvement. Prioritize KPIs that provide actionable insights into customer sentiment. Examples include Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS).
Agent Performance KPIs assess the effectiveness and productivity of individual support agents. These KPIs are essential for managing and optimizing team performance. Choose KPIs that align with your organization's goals and provide a clear picture of agent contributions. Examples include Tickets Resolved per Agent and Agent Utilization Rate.
Service Level KPIs measure the organization's ability to meet predefined service standards. These KPIs are vital for maintaining customer trust and ensuring consistent service quality. Focus on KPIs that reflect your service commitments and customer expectations. Examples include Service Level Agreement (SLA) Compliance and Response Time.
Cost Management KPIs track the financial efficiency of customer support operations. These KPIs help identify cost-saving opportunities and ensure budget adherence. Select KPIs that provide a comprehensive view of cost drivers and financial performance. Examples include Cost per Ticket and Support Cost as a Percentage of Revenue.
Channel Performance KPIs evaluate the effectiveness of different customer support channels. These KPIs are essential for optimizing multi-channel support strategies. Focus on KPIs that highlight channel-specific performance and customer preferences. Examples include Channel Utilization Rate and Channel Resolution Rate.
Organizations typically rely on a mix of internal and external sources to gather data for Customer Support KPIs. Internal sources include CRM systems, helpdesk software, and customer feedback surveys, which provide detailed insights into operational efficiency, customer satisfaction, and agent performance. External sources, such as industry benchmarks and market research reports, offer valuable context for comparing performance against peers.
Analyzing Customer Support KPIs involves several steps. First, data must be cleaned and standardized to ensure accuracy and consistency. Next, advanced analytics techniques, such as predictive modeling and sentiment analysis, can be applied to uncover trends and patterns. According to a McKinsey report, organizations that leverage advanced analytics in customer support can achieve up to a 20% increase in customer satisfaction and a 15% reduction in operational costs.
Visualization tools, such as dashboards and scorecards, are essential for presenting KPI data in an easily digestible format. These tools enable executives to monitor performance in real-time and make data-driven decisions. Gartner highlights that organizations using real-time dashboards for customer support KPIs experience a 25% improvement in decision-making speed.
Regularly reviewing and updating KPIs is crucial for maintaining their relevance and effectiveness. This involves setting clear performance targets, conducting periodic reviews, and making adjustments based on changing business needs and market conditions. A Deloitte study found that organizations that regularly review and update their KPIs are 30% more likely to achieve their customer support goals.
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The most important KPIs for measuring customer support effectiveness include Customer Satisfaction Score (CSAT), Net Promoter Score (NPS), First Call Resolution (FCR), and Average Handle Time (AHT). These KPIs provide a comprehensive view of customer satisfaction and operational efficiency.
Improving FCR involves training agents thoroughly, providing them with the right tools and resources, and implementing robust knowledge management systems. Regularly reviewing and analyzing FCR data can also help identify common issues and areas for improvement.
NPS measures customer loyalty and the likelihood of customers recommending your organization to others. A high NPS indicates strong customer satisfaction and can be a predictor of future growth and customer retention.
Measure cost-effectiveness by tracking KPIs such as Cost per Ticket and Support Cost as a Percentage of Revenue. These KPIs help identify areas where costs can be optimized without compromising service quality.
Dashboards provide a real-time, visual representation of KPI data, enabling executives to monitor performance and make informed decisions quickly. They are essential for tracking progress, identifying trends, and ensuring alignment with organizational goals.
Customer Support KPIs should be reviewed and updated regularly, at least quarterly, to ensure they remain relevant and aligned with organizational objectives. Regular reviews help identify areas for improvement and adapt to changing market conditions.
Best practices include setting SMART (Specific, Measurable, Achievable, Relevant, Time-bound) targets, involving key stakeholders in the target-setting process, and benchmarking against industry standards. Regularly reviewing and adjusting targets based on performance data is also crucial.
Advanced analytics can uncover hidden trends, predict customer behavior, and identify areas for improvement. Leveraging techniques like predictive modeling and sentiment analysis can lead to more proactive and personalized support, ultimately enhancing customer satisfaction and operational efficiency.
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These best practice documents below are available for individual purchase from Flevy , the largest knowledge base of business frameworks, templates, and financial models available online.
KPI Depot (formerly the Flevy KPI Library) is a comprehensive, fully searchable database of over 20,000+ Key Performance Indicators. Each KPI is documented with 12 practical attributes that take you from definition to real-world application (definition, business insights, measurement approach, formula, trend analysis, diagnostics, tips, visualization ideas, risk warnings, tools & tech, integration points, and change impact).
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Each KPI in our knowledge base includes 12 attributes.
The typical business insights we expect to gain through the tracking of this KPI
An outline of the approach or process followed to measure this KPI
The standard formula organizations use to calculate this KPI
Insights into how the KPI tends to evolve over time and what trends could indicate positive or negative performance shifts
Questions to ask to better understand your current position is for the KPI and how it can improve
Practical, actionable tips for improving the KPI, which might involve operational changes, strategic shifts, or tactical actions
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Potential risks or warnings signs that could indicate underlying issues that require immediate attention
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How the KPI can be integrated with other business systems and processes for holistic strategic performance management
Explanation of how changes in the KPI can impact other KPIs and what kind of changes can be expected
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