Call Center Operations
May 31, 2024
Contact center leaders are feeling the pressure more than ever. Customers expect swift resolutions, call volumes fluctuate, and skilled agents are hard to hire and retain. Call center management is the ability to address these complexities while ensuring efficiency, employee engagement, and customer satisfaction.
To tackle these challenges all at once, integrating technology into the operation is key. Generative AI plays an essential role in extracting powerful insights from calls and automating tasks. In this post, we share 13 call center management best practices to deliver exceptional customer support and employee experience with AI-powered tools.
Table of Contents
1.Leverage data-driven recruitment and onboarding
Hiring top talent is a costly process, but what if you could target candidates with the specific skills your team lacks? AI streamlines recruitment and onboarding by:
Mapping recurrent team difficulties (e.g., achieving FCR, increasing resolution)
Identifying skills your agents miss the most (e.g., communication, problem-solving)
Adding questions related to these skills in hiring interviews
Preparing new agents with an onboarding that covers common issues
With an AI-driven call center quality management system, you access data in real time to update recruiters with the skills you're looking for. You also inform new employees about challenges your team uses to deal with.
2.Enable automated quality assurance
According to Deloitte, the quality of service is the most popular indicator to measure the performance of teams and individual employees. With AI tools, you don't need checklists or sampling to evaluate customer interactions. AI automatically:
Collects data from calls (e.g., duration, resolution, CSAT score)
Analyzes the content, including topics mentioned and customer sentiment
Scores calls based on pre-defined criteria such as script adherence and active listening
This process offers insights into agent performance and frees up managers' time to focus on daily priorities
3.Track performance development goals
If your call center team needs to reduce average handle time (AHT), watch this metric to understand which employees struggle with this goal. This is what AI performance tracking does. generative conversation intelligence platforms like Echo AI offer dashboards to monitor call center performance, allowing leaders to investigate the reasons behind the lowest scores.
4.Analyze performance data to identify priorities
AI analyzes vast amounts of customer data in seconds, providing a comprehensive view of your contact center's performance. These insights help you identify areas with the most significant impact on customer satisfaction and operational efficiency.
With call center analytics software, you:
Detect emerging trends like high call volumes and long waiting times
Uncover and fix CX blind spots that lead to lower customer satisfaction
Empower call center agents with real-time information on their performance
Explore how call center analytics and reporting makes for a data-driven team.
5.Encourage clear communication
Clear communication from leadership fosters trust within the team and inspires agents to improve their own abilities when interacting with customers. According to a PwC report, only 38% of U.S. consumers believe the employees they interact with understand their needs.
With AI, managers detect unclear conversations to tailor coaching sessions. It supports the development of a positive approach when dealing with customer complaints.
6.Ensure regular performance evaluation
Regular 1-1 meetings foster open communication and allow supervisors to coach based on each employee's needs. With AI, you fuel your conversations with information on agents' posture and results. Leveraging QA scorecards, leaders can direct these questions to the team:
How do you feel about dealing with these long and complex calls?
What specific techniques are you using to achieve such a high success rate?
How can I help you improve your time-management skills?
A data-driven approach to one-on-ones improves agent behavior and motivation to achieve career development goals.
7.Integrate VoC data into performance evaluations
Voice of the Customer (VoC) is the feedback customers provide about your company, products, and services. It's a valuable source of data to assess agent performance, so take advantage of AI-powered VoC tools to analyze interactions across different touchpoints (e.g., emails, CRM systems, chat, and others).
With this comprehensive view, multichannel or omnichannel contact centers create strategies to reduce call volumes while improving the effectiveness of other touchpoints. Inbound and outbound call centers also benefit from VoC to enable AI churn prediction, addressing concerns before customers stop using your product or service.
8.Foster a culture of continuous feedback
Feedback is a challenging task in contact center management, as it requires an eye for detail in a fast-paced environment. AI streamlines this process by providing constructive reviews based on resolution, sentiment, and QA scores.
After every interaction, you receive AI-generated feedback on your agents. These evaluations help leaders recognize efforts and correct attitudes as they happen.
9.Understand the need for training
To reduce costs with call center training initiatives, use AI-powered analytics to understand what kind of knowledge and skills your agents need to excel. By evaluating data from interactions, you extract insights like:
Frequent call topics: Look at the reasons why customers call you. For example, if your product return inquiries contribute to lower customer satisfaction scores, you should examine how your team is handling return policies.
Missed opportunities: AI identifies areas for improvement in sales performance by detecting upselling or cross-selling openings. It supports training on sales techniques.
Keywords and sentiment: Analyze frequent keywords and the sentiment agents and customers express. For example, if "warranty" is often related to negative sentiment, additional training may be crucial to improve information about product replacement.
10.Monitor inappropriate agent behavior
11.Offer ongoing support and motivation
Gartner reports that only one in three service representatives feels engaged. By implementing coaching initiatives, you can better motivate and support your team.
With AI, you can:
Detect signs of impatience or stress during calls to provide appropriate coaching
Discover who are the best talents within your team so you can recognize their efforts
12.Use gamification to engage team members
Contact center gamification involves incorporating game mechanics to engage your agents, encouraging productivity and healthy competition. A study by IBM shows that organizations with exceptional employee experiences achieve 31% higher revenue growth compared to organizations with a lack of top initiatives.
Here are three call center management best practices focused on gamification:
Share award points for completing calls and exceeding customer satisfaction targets
Create a friendly competition between top performers based on key metrics like first-call resolution rate (FCR) or AHT
Design challenges that encourage agents to focus on specific goals, like resolving a customer query within a timeframe
Leverage AI to personalize these experiences and motivate agents with gamification elements. This will boost motivation and performance development among your team.
Analyzing Return Patterns with Intent Data
Operational bottlenecks, such as long hold times and frequent call transfers, affect performance in your contact center. Use AI-powered analytics to identify what is causing slowdowns.
For example, ongoing call monitoring may reveal that 70% of order cancellations are due to failures in package delivery. This insight gives you the confidence to renegotiate contracts with your distribution partner, reducing operating costs related to cancellations.
