The 2019 State of Speech Analytics

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With more powerful hardware and evolved software to provide better efficiencies and a larger array of insightful data, speech analytics has started to go beyond its traditional uses primarily in large enterprise contact centers to deployment in smaller enterprises and for uses beyond the contact center and into search, digital assistants, and even hearing devices.

The Year in Review

The expansion of the technology’s capabilities and uses meant that its adoption in 2018 started to accelerate from what had been a relatively slow pace in previous years, says Omer Minkara, Aberdeen Group’s vice president and principal analyst for contact centers and customer experience management. “More than half of the companies that use it today have more than $1 billion in annual revenue,” Minkara says. “It’s only started to take off recently due to the development of cloud-based solutions.”

Speech analytics is valuable for users because it enables enterprises to maximize customer satisfaction while reducing the cost of customer service—fewer live agent interactions are needed to handle customer communications. By enhancing customer satisfaction, speech analytics also helps boost upselling opportunities. Reduced cost of compliance is yet another benefit, according to Minkara.

The cloud-based solutions enable wider use of the technology than installed solutions. Speech analytics also grew in 2018 because companies increasingly incorporated self-service into their activities via IVRs and voice-enabled websites, chatbots, etc., according to Aberdeen.

Beyond advanced computing power, artificial intelligence was one of the driving forces behind the growing use of speech analytics among enterprises during the past year, according to Allan Andersen, director of enterprise solutions at IPsoft. “It was a big year for new developments in speech analytics and natural language understanding—specifically, the rapid progression of conversational AI and its ubiquity in the enterprise—impacting the way businesses operate, the way employees work, and the way customers engage with brands’ services and products,” Andersen says.

With conversational AI, businesses across industries are able to address internal pain points for employees and reduce the amount of time it takes to resolve time-consuming tasks, Andersen points out. “Using natural language, employees are able to communicate with a virtual agent (instead of calling the service desk) for help with IT, HR, or finance-related questions. This not only empowers employees to self-service more menial tasks (e.g., resetting passwords or submitting expense reports) but also improves operational efficiencies by automating simple, repetitive tasks and freeing up time for service desk agents to focus on more complex problems.”

Alexis Bernard, chief technology officer at Knowles, adds that the contextual understanding available in speech analytics has continually evolved, driven by AI and machine learning. As a result, speech analytics has become part of the the growing Internet of Things (IoT) market, with speakers in microwaves, smart thermostats, and other devices having much the same natural language understanding as the technology used in contact centers. These devices have also started to improve their ability to filter out extraneous sounds and have been optimized for low power operations.

Hearing devices also started to incorporate similar technology in 2018, according to Bernard. “There are a lot of new devices that are a lot smarter with much better audio processing and context awareness.”

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