For a long time, call center quality management was carried out with manual spot checks. With rapidly increasing call volumes and emergence of new contact methods, manual quality inspection is no longer sufficient to meet modern contact centers needs. Agent quality inspection must be done efficiently and accurately, which can only be achieved by relying on advanced technology.
At present, the sampling rate of the industry is approximately 1-2%, which means that a large number of recordings go ignored. Hidden pointers and risks are not effectively identified.
- Business value
Because coverage rate is relatively low, it is impossible to grasp customer needs and seize business opportunities accurately. The business value of quality inspectors is subsequently not well-established.
- Quality inspection delay
Manual quality inspection is generally conducted after service. This method cannot respond to incidents and risks in real-time and in a timely manner.
- Work efficiency
Manual quality inspection usually requires repeated playback. This results in inefficiency and limits the number of problems that can be found during working hours.
- Quality inspection standards
Manual quality inspections are limited by individual perceptions. Different people draw different conclusions from the same event; a person’s perception also changes over time. This caused difficulties in establishing a unified quality inspection standard.
- Quality inspection costs
Manual quality inspections are highly repetitive and heavy. As call volume increases, companies will need to invest more and more manpower and material to meet inspection needs and inspection proportions.
With the development of artificial intelligence technology (speech recognition, big data mining), mass recording data can now be converted (real time or offline) into unstructured data such as text. We can achieve 100% voice file coverage and greatly reduce the cost of quality inspection. Thanks to text analysis and data mining, it is now possible to achieve compliance inspection, risk warning, trend analysis, and business opportunity mining.
Record Storage and Management
Converts large-scale voice calls to text indexes. Long-term support for high-speed retrieval, playback, and analysis of voice data.
The system provides extensive and flexible search conditions. It highlights search terms and color codes caller and callee.
System visually displays call sound, call content, and timeline; caller and callee color coded. Click a word to accurately position playback.
Standard manual quality inspection workflows can be converted into system-recognizable rules via role settings, position settings, range settings, and expression combinations. Freely customize and recreate different workflows.
AI-assisted Quality Inspection
Establish quality inspection rules (keywords, sentiment indicators, mutes, etc.) and automatically process and score service capabilities and attitudes. Solves the problem of low manual coverage.
The system can filter out low-rated calls for further manual quality inspection; quality inspection subsequently follows the model “AI batch inspection + operator targeted inspection”. This model facilitates comprehension and enhances customer service and contact center service quality.
The report engine and customizable report designer provide flexible and adaptable reports. Improve correlation and achieve data mining from report display to content query.