Voice Analysis for quality assurance and customer relationship management
QA5 is a Software-Development-Kit (SDK) for Emotion Detection that utilizes Nemesysco’s advanced voice analysis technology to detect and measure anger, stress and other relevant emotions that may arise in call center conversations. It is designed as a set of components that can be integrated into an existing call center solution to monitor agent-customer interactions and identify calls that may require special attention or intervention.
QA5 can analyze all ongoing calls in real-time and alert managers when problematic call events occur. Additionally, QA5 can be used on archived calls (offline, Post-Processing-Server) to identify patterns of interaction within calls and evaluate specific aspects of customer service quality, as well as provide insights about customers’ preferences, likes and dislikes.
QA5 SDK includes Nemesysco's LioNet™ engine, an advanced learning system component which provides the ability to automatically tag archived conversations according to criteria defined by the contact center's managers and policies (i.e., “Problematic,” “Successful,” etc.).
A company’s most vital asset is its customers. Meeting customer needs and focusing on customer satisfaction helps ensure that your customers will continue to want to do business with you, as well as recommend your company to others. Even when monitoring the textual content of customer support calls, customers do not always explicitly state their preferences or feelings about their interactions with your company’s CSR agents. Superior tools are needed to determine your customers’ true emotions and reactions, quickly and efficiently.
Integrating the QA5 emotion detection components into your call center solution gives you a significant competitive edge in today’s market, where unsatisfied customers can and will easily take their business elsewhere. Using Nemesysco’s Emotion Detection Platform, the QA5 SDK is able to detect and measure a wide variety of emotions and cognitive states including stress, anger, embarrassment, satisfaction, excitement, rationality and more - and do so on 100% of the on-going calls, in real-time. Each call center or vendor may customize its data display according to criteria that is most relevant for its business or evaluation needs.
By incorporating QA5 into your call center, supervision capabilities will be dramatically enhanced with real-time indicators, smart and efficient analysis of recordings databases, performance logs and reports of your agents’ progress, and advanced tools to learn about customers’ likes and dislikes.
Save clients - monitor conversations in real-time, and automatically detect when intervention is required.
Save time - scan mass call logs/recordings and automatically flag calls that are classified as “interesting” or “urgent,” according to pre-defined criteria.
Gather "intelligence" – zoom-in on any call to obtain feedback on your clients’ preferences and reactions.
Improve CRM methods – measure the effectiveness of your customer service operations and agent training.
Maximize agent productivity – monitor agent performance to assure quality, prevent burn-out, and reward good performance.
Focus of Analysis
QA5 can analyze both sides of a customer service call. For example, the technology can be used to focus on the customer’s side of the conversation, identifying specific emotion-related events that may take place during the call. When such events occur, your system may alert the managers in real-time, allowing them to monitor the call and determine whether an intervention is needed. Additionally, QA5 can be used to focus on the technique and effectiveness of the agent handling the call. Monitoring agent performance helps assure CS quality, prevent agent burn-out and churn, reward good performance, and maximize the efficiency and effectiveness of your customer service operations.
Scans all customer-agent interactions in real-time to detect problematic scenarios as they develop, and enables automatic alerts to CS managers.
Performs efficient offline emotional data mining of archived calls, based on criteria defined by any CS manager, seamlessly, during normal work procedures.
Measures different emotional parameters (such as averages of stress and anger) over any time period to assess overall CS site performance and generate automated report.
Monitors any agent’s performance and emotional development over any period of time.
Identifies agents that are having a bad day instantly, allowing taking positive action.
Applies an automated scoring system to reward agents' performance.
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