Speech analytics, also known as audio mining, is software that uses a variety of techniques to convert unstructured conversations into structured output, turning it into metadata and transcripts. The output files can then be analyzed, and the enterprise can use the findings to identify customer insights, needs and wants. See the figure below. What is Speech Analytics? Speech analytics applications use a variety of mathematical algorithms, analytic techniques, contextual and other call/customer-related metadata (including desktop and text analytics) to structure unstructured conversations. These techniques are applied to recorded audio files and live (real-time) conversations. The speech analytics process is multi-phased; it starts with a speech engine - either phonetic or large vocabulary continuous speech recognition (LVCSR, also known as speech-to-text) - to convert conversations into system-readable data for further analysis.
Next, each of the speech analytics solutions applies its own technology and methodology to create output (metadata), which is indexed prior to making it available to end users for search and analysis. The audio mining solution sends recorded or real-time conversations through a speech engine that breaks them into phonemes (representations of sounds), or words, phrases and concepts. To improve accuracy and provide context, each of the solutions applies a variety of techniques to further analyze and index the conversations, using proprietary algorithms to enhance the recognition capabilities. The underlying speech engine determines the output file; it may be a transcript of the conversation, an index of words, phrases and categories, or an index of phonemes. All output files must be searchable so that end users can create queries to parse the data into words, topics or categories for root cause, trend and correlation analysis.
Once the data is bucketed into categories, users can run reports or conduct ad hoc searches of databases or indices populated by the analysis/indexing layer of the application. Speech analytics output is delivered via dashboards, reports and alerts. Users can also run queries and see their findings online or in reports. Some speech analytics solutions also perform emotion detection, either by evaluating linguistic events, acoustics (volume, pitch and rate of speech) or a combination of the two approaches. When emotion detection is used together with root cause analysis, it is very helpful in identifying positive or negative trends. Real-time speech analytics, which emerged in 2011, will play a very important role in the future of this market. These solutions analyze calls as they are happening, and deliver some form of actionable recommendations to managers, supervisors or agents. Real-time speech analytics is being used to identify situations where agents are not in compliance with their script, guidelines or standard operating procedures. They can also help identify when customers are very unhappy or angry, so that a supervisor can intervene to rectify the situation in real time.
Real-time speech analytics makes remarkable contributions to customer service performance which directly influences customer experience and customer satisfaction in the long-run. When used as an agent guidance tool, real-time speech analytics can improve agent performance by increasing script adherence and identifying problematic situations when agents are not in compliance with standard operating procedures. By providing real-time agent feedback and online coaching, the technology unveils training needs of agents and helps organizations to adopt a continuous learning approach. In addition to its contributions in terms of agent performance, real-time speech analytics also helps organizations to boost customer satisfaction by improving interactions as they happen and by providing personalized responses to customers’ questions. Being able to improve customer satisfaction at the time of the call, shapes the future of customer-brand engagement.
In other words, real-time speech analytics helps organizations reach first base with customer loyalty and brand advocacy in the long run. Post-call speech analytics which already has a dominance in the market, already proved success in various industries through diversified projects. The technology has been an important component of voice of the customer platforms by giving an answer to the question ‘Why customers call? ’ Post-call analysis not only identifies useful insights about a company’s products, services, customers and competitors but also uncovers insights regarding overall call center performance. Post-call speech analytics contributes to enhanced customer experience by enabling continuous monitoring which includes categorizing calls into groups and reviewing them in order to determine customer-related issues accurately. Applying comprehensive analysis with historical data also helps organizations discover the root causes of customer issues and trending topics in customer communications.
Thus organizations can adopt a proactive approach in a way that prevents customer churn, repeating calls and negative customer perception. Taking into account their overall contributions; it is possible to see real-time speech analytics and post-call speech analytics as components of a holistic analytics system. While real-time speech analytics provides the ability to alter the outcome of a call positively by intervening interactions as they happen; post-call speech analytics lets organizations better see the longer term impacts of real-time actions they take. The technologies complement each other by improving different stages of customer interactions which result in overall enhancement in customer experience. Organizations which use real-time data in conjunction with post-call reporting tools can maximize the business value by improving agent performance, customer satisfaction and call center processes.
Real-Time Speech Analytics -- Real-time speech analytics for customer support and sales is a potential gold mine. The system can monitor agent calls to assess potential churn, identify stress, and aid the agent in engaging the customer in the best possible way. For example, real-time speech analytics systems can be used to monitor calls for keywords or stress points. It can quickly find reliable, contextual answers for agents about customer questions, evaluate corresponding sales opportunities, and check for any mistakes made by the agents, whether related to compliance or product information. This has the potential to save significant time and end user frustration.
Clearwater, FL, Oct. 25, 2018 (GLOBE NEWSWIRE) -- CallMiner, a leading platform provider of award-winning speech and customer engagement analytics, demonstrated its updated real-time speech analytics module, Eureka Alert, at the 10th annual LISTEN customer conference. Eureka Alert combines AI-driven automated transcription, redaction, and alerting to provide real-time direction to contact center agents and supervisors to drive specific outcomes within a call as it is occurring, or alerting management of critical risk or customer experience issues. "Real-time alerting is a crucial tool for improving or even saving customer interactions, preventing customer attrition, driving sales, or mitigating serious legal and security risk," said Bruce McMahon, Senior Director of Product Strategy at CallMiner.
Alert uses high quality, speaker-separated audio captured at the source produce real-time streaming transcriptions that substantially increase alerting speed. Customer calls to cancel a service which triggers an alert with recommendations on talk down language and standard promotions to offer. The customer mentions a promotion from a competitor, which then triggers another alert with specialized options available to the agent to compete with that specific competitor pricing. At the first mention of customer dissatisfaction, an alert would be triggered with reminders to the agent on how to address the customer’s frustration. As an API-based module, data and notifications from Alert can be integrated not only into agent and supervisor tools, but also into tools across the wider business such as BI and CRM systems. Access to these customer insights can inform a range of business programs such as sales, marketing, compliance, and customer experience with real-time understanding of the voice of the customer. This allows businesses to pivot or amplify their strategies based on quicker access to customer intel. CallMiner empowers organizations of any size to extract and take action on intelligence from customer interactions, for improving customer experience, sales, marketing, compliance, and agent and customer engagement centre performance.
MELVILLE, N.Y.--(BUSINESS WIRE)--Verint® Systems Inc. (Nasdaq: VRNT) today announced enhancements to its Real-Time Speech Analytics™ solution. The software, which leverages conversational indicators and analyzes customer calls as they unfold, enables organizations to take a proactive approach to identifying opportunities to guide interactions for the mutual benefit of both the end customer and the organization. With the ability to positively influence customer interactions as they take place, companies can increase first-contact resolution, enhance the customer experience, manage policy and regulatory compliance and heighten satisfaction and loyalty. The sophisticated rules engine in Verint Real-Time Speech Analytics can identify the presence or absence of words and phrases, as well as the sentiment expressed. Leveraging real-time insight as interactions unfold, customer service professionals can tap into the intelligence they need to support customer interactions and the drive toward successful outcomes.
Likewise, organizations can further drive sales opportunities and closing rates, and enhance adherence to compliance requirements, such as government regulations, industry mandates and internal organizational policies. Real-Time Speech Analytics is natively embedded in the Verint recorder to make it easier for customers to add it on at a lower cost of ownership, especially as service needs and demands change. The solution, which uses Verint’s new, purpose-built speech engine, combines phonetic recognition and full transcription of calls, and leverages advanced language understanding to deliver organizations the insights they need with even greater speed and accuracy. Organizations can further the value of Verint Real-Time Speech Analytics by using it as an extension of Verint Speech Analytics™ and Verint Desktop and Process Analytics™.
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