Automated quality assurance for contact centers



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Assuring Superior Customer Experience Automated quality assurance for contact centers

Automated quality assurance for contact centers QA5 is a software solution for emotion detection, utilizing Nemesysco s advanced voice analysis technology to detect and measure in real-time anger, stress and other relevant emotions that may arise in contact center conversations. It is designed as a software development kit (SDK) that can be integrated into an existing contact center solution to monitor agent-customer interactions and identify calls that may require special attention or intervention, both in real time and offline. Business Benefits Save clients: monitor conversations in real-time, and automatically detect when intervention is required. Save time: scan through masses of recorded calls and automatically flag calls 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 over time to ensure quality, prevent burn-out, and reward good performance. In its real-time implementation, QA5 can analyze all ongoing calls and alert supervisors/managers when problematic call events occur. In offline mode, QA5 identifies patterns of interaction within calls and evaluates specific aspects of customer service quality, as well as provide insights about customers preferences, likes and dislikes. In addition, QA5 SDK contains Nemesysco s LioNet technology, 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.). 2 QA5 generates 2 summary values: Call Priority to assess the urgency and extreme emotional states of a customer, and Agent Priority, assessing Agent s performance during each call. Additional indicators of specific emotional activity can be used to enrich your system and business logic.

Protect your most valuable assets A company s most vital asset is its customers. Meeting customer needs and focusing on customer satisfaction helps to ensure customers loyalty to your business, as well as their recommendations to others. Even when monitoring the textual content of calls, customers rarely explicitly state their true preferences or feelings about their interactions with your company s contact center agents. Superior tools are needed to determine your customers true emotions and reactions, quickly and efficiently. Integrating the QA5 emotion detection components into your contact 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 mental states including stress, anger, embarrassment, satisfaction, excitement, rationality and more. Each contact center site may customize its data display according to criteria that is most relevant for its business or evaluation needs. By incorporating QA5 into your contact center, supervision capabilities will be dramatically enhanced with unbiased and accurate 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. Case study MTS Russia s biggest cellular operator A year-long study of QA5 and its ability to improve customer service and contact center management: 81,000 calls analyzed, 3,000 calls reviewed by supervisors. 95% similarity in QA5 & supervisors marking Good / Normal calls 77% similarity in QA5 & supervisors on all calls ( Good / Problematic / Bad ) Using QA5 improved supervisors efficiency between 400%-900%. Problematic calls detection ratio 90% 80% 70% 60% 50% 40% 30% 20% 10% 5% Without QA5 77% With QA5 Identified benefits: Managers have much better control over operators performance Operators can receive feedback from the system for selfimprovement QA5 s ability to produce a stable analysis over a long period of time is higher than of human operators. 3

Designing a QA5 based system Online / Real-time implementation Use QA5 to detect extreme emotional changes in all the calls taking place in the contact center and establish the emotional development trend for each call. The QA5 sample code contains an example for a Call Priority and Agent Priority scores. Real time monitoring can also collect data about the general emotional state of the agent, his current stress, fatigue and boredom level, and his customers reaction to his responses. A flexible set of rules can be added to your system, defining which indications will be provided to the manager by the system, attracting his attention to a specific call. Offline / Post processing analysis In offline analysis implementation, more comprehensive emotional data can be explored to provide better understanding about the customers, their likes and dislikes. Advanced markers and tags can be added to the call database by the QA5 learning system (LioNet) using feedback provided by each supervisor to tune the system to his specific needs. Using LioNet can be as simple as clicking a button: Normal (requires no further attention), Interesting or even Urgent attention. 4 The QA5 SDK can be used in many ways in your contact center application: Online/real-time analysis quality/priority monitoring Offline/post processing analysis Telemarketing Automated report generation and quantified goals Contact center s staff performance optimization Training and feedback Telemarketing aids The customer s emotional profile is an important indication to the agent handling the call, better directing his support and sales approach. The emotional profile of the client is determined by the QA5 core following the analysis of the first 10-15 seconds of the customer s voice, and contains 6 emotional elements. These emotional elements can be used by the contact center s professional team to design special scripts and instructions to handle different types of personalities. In addition, different real time indications can be used to further direct the sales approach as the conversation develops. Report generation The rich data QA5 can feed into your system, from the specific agent level to the overall group or site performance, can be used to automatically generate productivity and objective quality reports. These can dramatically enhance your product offering, simplifying managers work and save critical time. Use emotional values from different groups handling specific topics to reveal problems as they develop in different business areas.

Common implementations of QA5 Graphical display of emotions in a conversation Easily understandable and user friendly display is paramount to your system acceptance and can expedite large scale deployments. Using the analysis data, your system s conversation player can present a graphical display of significant emotions and their development over time in the course of the conversation. Managers can easily mark and playback any portions of the call where unexpected emotional reaction is detected to get to the bottom line and reach decisions faster. Work related stress analysis Monitor work-related stress level of the agents to automatically warn managers about burn-out and even prevent in advance serious stressrelated symptoms. Data Flow and Licensing System Using additional analytics tools in conjunction with QA5 When coupled with additional analysis technologies, such as word spotting or user identification, your system s capabilities can be further enhanced by providing, for example, emotional analysis of specific key-words/phrases, such as product names or extended emotional profile of different customers. Start Create instance of QA5 and initialize in License Server Mode License Server started OK? Wait for a call Create a new call handler containing QA5 analysis instance/s Acquire QA5 License from the license server Ongoing phone calls Handle UI, reports and alerts system Call ends: Generate reports & release call handler process Contact Center Host System Call Handler #1 Call Level Business Logic Call Handler #n 2 channels separated voice streaming data Operator & Customer Emotion analysis Overall Emotion analysis data QA5 License server Analysis OP Interface #1 Analysis CS Interface #2 Analysis OP Interface #m Analysis CS Interface #n Call categorization QA5 Core Internal LioNet Engine LioNet Engine 5

Focus of Analysis QA5 can analyze both ends 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 can alert the supervisor in real-time, allowing him 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 contact Center quality, prevent agent burn-out, reward good performance and maximize the efficiency and effectiveness of your customer service operations. Audio Formats The technology can process a number of uncompressed audio formats typically used in contact center conversation recordings, both from a file or streaming directly from the telephone system. These include 6/8/11 KHz sampling rates in 8/16 bit depth. Optimal results are obtained when analyzing a stream/file of only one party s voice in the conversation, separated from the other voices. Integration QA5 SDK is based on a Windows COM object (NMSQA5COM.dll) that contains all the functionality and objects required for development. Use the demonstration applications and sample source code to review different areas of functionality and capabilities supported by the QA5 SDK. Product Highlights Scans all customer-agent interactions in real-time to detect problematic scenarios as they develop, and enables automatic alerts to contact center supervisors/managers. Performs efficient offline emotional data mining on archived calls, based on criteria defined by any contact center manager, seamlessly, during normal work procedures. Measures different emotional parameters (such as averages of energy, stress and anger) over any time period to assess overall contact center 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. No special tuning required, QA5 is language independent! General System Architecture QA5 DLL can process any number of calls in real-time, however, exact performance is dependent on the type of hardware used in the existing system architecture. PBX CRM Solution Manager 6 Logger Manager

The QA5 Technology QA5 SDK utilizes Nemesysco s LVA and Emotion Detection Platform to detect and measure a wide range of emotions and cognitive states. Together with the LioNet learning engine, it further allows you to define, train and detect additional emotional states to meet specific customer needs. This unique combination of automatic detection of a variety of emotions, together with the ability to train the system to detect other emotions of interest, in real-time or from pre-recorded material, is what makes QA5 the most sophisticated, flexible, cutting edge voice analysis technology available today. Nemesysco Emotion Detection Platform technology produces a set of 12 normalized emotions and additional 4 indications of the tested party s emotional activity: Energy Stress Anger Content Upset Embarrassment Intensive Thinking Hesitation Uncertainty Excitement Concentration Level Arousal Extreme mental States Overall Cognitive Effort Rationality Imagination Activity LVA TM - Layered Voice Analysis SENSATION Positive / Conflict / Negative Stress / Excitement / Hesitation / Confusion / Mental / Effort Concentration / Embarrassment / Energy / Profound Emotions - Butterflies, Heaviness... Anger / Sadness / Happiness... Clinical states * For illustration purposes only The LioNet learning engine Principle The LioNet engine was designed in response to a need for research assistance. It uses Basic Clusters (the information bins created each time the system learns something new), and Prime Clusters (any possible output response). Between the 2, the Hidden Clusters layer is created and modified automatically based on the accumulative knowledge and common criteria between similar Basic Clusters. LioNetV6 further compute a layer of Smart Clusters that are different mathematical formulas automatically created by LioNet, further assisting classification of different types of uses. While analyzing an input, LioNet uses 13 different decision engines that can reach different decisions, and LioNet keeps track of the decision engine that was most useful and accurate, and will use it for its final analysis. 7

Assuring Superior Customer Experience About Nemesysco Nemesysco Ltd. is the leading provider of voice analysis and emotion detection technologies, for defense and civilian markets. Nemesysco s LVA (Layered Voice Analysis) technology detects the emotional content of a conversation, in real-time or from recorded materials, enabling analysis of different types of stress, cognitive processes and various emotional reactions. Nemesysco s products are implemented in a wide variety of applications for law enforcement, homeland security, insurance and banks fraud prevention, employee screening, call center quality monitoring, healthcare and entertainment. Nemesysco is a privately held company, founded in 2000 and is headquartered in Netanya, Israel. Nemesysco Ltd. Tel: +972-9-885-3864 Fax: +972-9-885-3782 bizdev@nemesysco.com www.nemesysco.com 6 Hagavish St. POB 8747 Sapir Industrial Park Netanya, Israel 42504 Copyright 2011 Nemesysco Ltd. All rights reserved.