Performance Indicators (KPIs) are essential tools for measuring the efficiency and effectiveness of a contact center, especially in a digital environment where multiple channels are used to interact with customers. KPIs such as FTEs per customer, Average Handling Time (AHT), percentage of calls handled by bots, and transactions per agent provide a detailed view of the contact center’s performance, both in terms of operational efficiency and customer service quality. Below is an in-depth analysis of each of these indicators:
1. FTEs per Customer (Full-Time Equivalents per Customer)
This KPI measures how many full-time equivalents (FTEs) are required to handle customer interactions in the contact center. The ratio between FTEs and customer volume provides insight into the efficiency of the service team and the workload distribution within the contact center.
Formula:
FTEs per Customer = Total Full-Time Equivalents (FTEs) / Total Number of Customers
Analysis:
A low FTEs per customer value indicates that the contact center is well-scaled, handling a high volume of interactions with a reduced number of agents. A high ratio, on the other hand, may suggest overstaffing or inefficiencies in service processes.
Factors Influencing FTEs per Customer:
- Customer volume: A larger number of customers typically requires more agents unless automation (such as bots) is widely used.
- Complexity of issues: More complex problems demand more time from agents, increasing the number of FTEs per customer.
- Automation: The use of self-service tools and chatbots can reduce the number of agents needed for routine interactions, lowering FTEs per customer.
2. Average Handling Time (AHT)
AHT measures the average time an agent takes to complete a customer interaction from start to finish. This indicator includes conversation time (or chat), waiting time, and after-call work (ACW).
Formula:
AHT =
Total Talk Time + Total Hold Time + Total After-Call Work (ACW) Time / Total Number of Calls Handled
Analysis:
- Low AHT may indicate efficiency but could also suggest rushed or incomplete service, potentially impacting customer satisfaction.
- High AHT may suggest that agents are spending too much time on individual issues, possibly due to the complexity of problems or inefficiencies in processes, technology, or training.
Strategies to Improve AHT:
- Training and skill development: Well-trained agents tend to resolve issues faster.
- Automation: Automating routine inquiries through chatbots or self-service portals can reduce the AHT for agents handling more complex issues.
- Knowledge management: Providing agents with quick access to FAQs, manuals, and resolution guides can help resolve issues more efficiently.
3. Percentage of Calls Handled by Bots
This KPI measures the percentage of customer interactions that are automated and managed by bots (e.g., chatbots or virtual assistants) without human intervention.
Formula:
Percentage of Calls Handled by Bots =
Total Calls Handled by Bots / Total Calls Received × 100
Analysis:
- High percentage of calls handled by bots suggests that the contact center has successfully implemented automation, freeing human agents to handle more complex tasks.
- Low percentage of calls handled by bots may indicate a lack of automation or an ineffective bot system, forcing most interactions to be handled by human agents.
Challenges of Bot Automation:
- Bot limitations: Not all inquiries can be efficiently resolved by bots, especially those involving complex issues requiring empathy, judgment, or human flexibility.
- Escalation procedures: It is crucial that when a bot fails to resolve a problem, the interaction is smoothly transferred to a human agent.
4. Transactions per Agent (Transactions per Hour)
This KPI measures the number of interactions or transactions an agent can handle per hour or per day. It is a key productivity indicator in a digital contact center.
Formula:
Transactions per Agent =
Total Transactions / Total Agent Hours Worked
Analysis:
- High transactions per agent suggest that agents are handling a large volume of inquiries, which may indicate high efficiency, especially for low-complexity inquiries.
- Low transactions per agent may indicate underutilization of agents, lack of training, or a need for better workflow optimization. It can also occur when agents handle more complex issues that require more time for resolution.
Improvements for Transactions per Agent:
- Automation: By automating more routine tasks, agents will have more capacity to handle complex issues, increasing transaction volume.
- Training and tools: Providing agents with quick and easy access to updated information and the right tools can speed up interaction resolution.
- Workforce management: Proper scheduling and workload balancing ensure that agents handle an optimal number of transactions, preventing burnout.
5. First Contact Resolution (FCR)
Although not initially mentioned, First Contact Resolution (FCR) is a crucial KPI, especially when aiming for customer service efficiency. FCR measures the percentage of customer issues resolved on the first contact without the need for follow-ups.
Formula:
FCR =
Total Issues Resolved on First Contact / Total Issues Reported × 100
Analysis:
- High FCR indicates that the contact center is effectively resolving customer issues on the first contact, reducing operational costs and increasing customer satisfaction.
- Low FCR may indicate that the contact center’s processes or knowledge base are insufficient, leading to multiple contacts and higher operational costs.
6. Cost per Interaction (CPI)
The Cost per Interaction (CPI) KPI measures the operational cost associated with handling each customer interaction.
Formula:
CPI =
Total Operational Costs / Total Number of Interactions
Analysis:
- Low CPI indicates efficiency and good resource optimization.
- High CPI may suggest inefficiencies in staffing, technology, or processes. In the context of a digital contact center, automation can reduce CPI by handling more interactions with fewer agents.
Conclusion: Balancing Efficiency and Quality
While efficiency KPIs are essential for measuring the performance of a digital contact center, it is crucial to balance them with quality metrics such as Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS). I will discuss this further in the next article. A quick or highly productive contact does not always yield the best outcome if it compromises service quality. Therefore, monitoring a combination of efficiency and quality indicators ensures that the contact center’s operational goals are met without sacrificing the customer experience.