Artificial Intelligence
Quality management (QM) is crucial to the success of contact centers. It ensures that every customer interaction meets the highest standards, leading to improved customer satisfaction and significantly enhanced operational efficiency. At a time where customer expectations are constantly rising and competition is fierce, effective quality management is essential.
Manual methods of quality assurance often reach their limits. AI in contact centers streamlines these processes, enhances efficiency, and reduces the workload for companies. But what exactly is quality management in a contact center, and why is it so essential?
The Importance of Quality Management in Contact Centers
In a contact center, companies face various challenges. Customers expect fast, precise and friendly support. Even small mistakes can lead to negative reviews or the loss of a customer. Well-structured quality management helps to keep service quality at a consistently high level. It not only improves customer satisfaction, but also reduces operating costs. By identifying inefficient processes and providing targeted employee training, QM helps to minimize errors and repeat contacts.
“Quality management is crucial for identifying and proactively resolving the causes of repeat calls, escalations or complaints,” explains Britta Chiaia, Product Manager at ASC.
Additionally, QM is legally required in many countries and industries. Companies must adhere to certain standards to avoid fines and damage to their reputation.
While manual QM was once the standard, automated systems are now offering new opportunities. But what benefits does AI in contact centers offer compared to the manual approach?
Challenges of Manual Quality Management
Manual quality management presents several significant challenges. A major issue is the subjectivity of assessments.
“Manual quality assessments by humans are subjective, as different assessors may have different interpretations of quality criteria,” Chiaia emphasizes. “Different assessors can rate the same call differently, which can lead to inaccurate results and a distorted assessment of service quality.”
Another major drawback is the substantial resource investment required. Training the assessors, monitoring calls and analyzing data demand considerable manpower and time. Moreover, it’s nearly impossible to review all calls, meaning many potential issues may go undetected. Measuring the return on investment (ROI) can be challenging, as the benefits of improved QM are often hard to quantify.
“It can be difficult to quantify the direct impact of QM measures on key metrics and financial results, making it difficult to assess the value of these measures,” Chiaia continues.
Automated Quality Management Through AI
The introduction of AI in quality management offers a solution to many of the challenges mentioned. AI-based systems can automatically analyze based on predefined criteria, providing consistent and objective evaluations. This significantly reduces resource requirements, as AI processes large volumes of data quickly, eliminating the need for human reviewers.
The cost-benefit ratio also improves with AI in contact centers. By saving time and reducing the need for personnel, companies can use their resources more efficiently and enhance service quality simultaneously. Additionally, AI removes human subjectivity, ensuring more neutral and accurate assessments.
ASC's Approach: Automated Quality Management with Recording Insights
Many companies already have established processes and standardized documents for manual quality management. Recording Insights offers a solution that integrates these existing procedures with the benefits of automated assessments. This tool allows companies to use their current assessment questionnaires and perform both automated and manual evaluations, ensuring flexibility to meet specific needs.
This means that companies retain the flexibility to meet their specific requirements while ensuring increased efficiency and accuracy in their quality management processes. Recording Insights saves time, increases assessment precision, and adapts to individual requirements.
Another advantage is the uncomplicated integration.
“As contact centers often already use standardized evaluation questionnaires in Excel format, these can be easily imported into the Recording Insights interface,” explains Chiaia.
This ease of use facilitates a smooth transition to automated quality management without extensive adjustments.
AI has the potential to significantly transform the contact center industry in the long term. By automating and enhancing quality management processes, companies can boost service quality and reduce costs. Chiaia highlights this:
“Whether as automated self-assessment for agents or traditional QM for supervisors and department heads, AI-supported QM not only saves time, but also ensures professional customer communication and reduces stress for employees.”
