When Apple introduced Siri, speech recognition by machines found humanization that became quickly and immensely popular. Speech recognition may be a modern perceived phenomenon of the 21st century, but its roots can be traced back to the early 1950s. In fact, Siri might not be the foremost personification of speech analytics technology. In 1952, Bell Laboratories built Audrey, a device capable of recognising strings of digits displaying 97%-99% accuracy if configured to the speaker’s voice. The only problem was it was too cumbersome and consumed excessive energy. Years later Siri was developed as a virtual assistant technology by another company. Apple eventually acquired the technology and implemented Siri in the iPhone 4S in 2011. Over time, Siri has accumulated a user knowledge database that has been augmented with AI and deep learning technology. Siri’s intelligence capability is enabling simplification of human life by deriving data from human speech itself. Siri is the most successful example of speech recognition technology that uses a natural language user interface to interpret the human voice to answer questions and offer recommendations in human voice form.

Speech analytics is a powerful business intelligence tool as well for many enterprise sectors. It is especially useful in delivering accurate insights in industries such as banking, insurance, finance and healthcare. Smartphone and mobile disruption has led to complex customer journeys which businesses want to comprehend fully and more, in order to retain existing customers and attract new ones. Contact centres that are adept in customer experience management believe in adopting technological sophistication that benefits their clients in understanding their target audience behaviour for smarter CX strategies. Cloud based infrastructure, mobility, self-service, customer journey analytics, gamification etc. are some of the areas that are attracting interest and investment as businesses strive to create the best customer-centric deliveries. Voice recognition and speech analytics are at the frontier of deciphering customer journeys in real-time as well as post interaction, thereby making it a prominent part of contact centre operations. In fact, speech analytics market is expected to be worth USD 1.60 billion by year 2020.

What is speech analytics?

Speech analytics is an interpretational process employed by customer contact centres to harness relevant intelligence from audio recordings of call interactions. Speech analytics software uses audio mining to scan customer call recordings for data extraction without any loss. In this two-fold process, the first phase is speech recognition that enables identification and comprehension of spoken words and phrases. The second phase is sentiment recognition and analysis. Sentiment analysis offers insight on the basis of speech patterns, timing, volume and keywords and phrases used. With AI integration, agents can now access real-time feedback on the caller’s tone and mood and judge the tenor of the conversation for pertinent responses.

How does speech analytics benefit customer experience?

Data Mining

Speech analytics has multiple advantages like call interaction management, keyword tracking and automatic transcription of customer conversations. These conversations can be mined for data around positive or negative sentiments, business intelligence, accurate insights on agent behaviour, customer preference and even tracking silence. Speech analytics helps point the strengths and weaknesses of a business or brand via feedback and aids a business or service to gain an objective perspective for better sales, customer service and subsequently higher ROI.

Reducing operational costs

While applying speech analytics insights for their clients to create better customer experience, contact centres gain more than customer loyalty.

This directly affects the company bottom line and aligned with best practices, speech analytics can empower contact centres within three to nine months of implementation. It can detect cost savings by highlighting where processes fail or work within the organization while also enhancing team performances and productivity.

Drives sales growth

With data from real-time speech analytics applications, sales focused agents can design personalized up-sell and cross-sell opportunities during a call while it is in progress, as they have instant access to the customer’s requirements (based on past data) and current conversation. Real-time analytics prepare senior management to support agents with better responsiveness, conversions and issue resolution.

Tracking the impact of marketing campaigns

Whether real-time data or post interaction data, insights derived from customers using speech analytics tools can be used to track customer demographic and the impact of marketing campaigns on the target audience. Based on these insights, better product line, improvised product features and effective marketing strategy can be evolved to suit customer preference. Understanding customer dissatisfaction and intervention for improvement in real-time is a possibility realised only with the prowess of speech analytics.

TeleApps along with its strategic partners brings high-quality speech analytics solutions to a diverse range of customers from financial services, banking and insurance industries, telecom and GSM operators and public institutions. Voice Biometrics, Speech Analytics, Call Steering, Speech Recognition and Text-to-Speech technologies are a range of partner services and contact centre solutions that TeleApps provides to its vast and global clientele. Read more about TeleApps here.

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