Speech analytics is a software feature gaining momentum in the contact center industry. The technology has been on the market for some years but has not been fully adopted and utilized by call center managers. Industry analysts believe call centers did not embrace early iterations of speech analytics because of a number of factors, including unconvincing marketing hype, confusing technology platforms, and unmet expectations when the technology was first introduced.
According to a recent CRM Magazine article, DMG Consulting and ContactBabel have found that just fewer than 20 percent of call centers use speech analytics technology.
But the tide may be turning. Among the 80 percent that has not implemented this technology, 25 percent are planning to soon move forward with this feature. micro markets, an analyst firm, estimates a growth rate of 21.4 percent in speech analytics, from a market of $233.2 in 2014 to $614.1 million in 2019.
Experts believe this growth will be driven by an increasing number of contact centers and management’s need for real-time cloud analytics and risk management to improving the customer experience.
Speech analytics combines several technologies. It begins scanning for keywords and phrases; client interruptions; talking rate, pitch, tone; and emotions within the context of the phone conversation. An artificial intelligence engine will then analyze the data and provide feedback to the agent based on preset rules. Feedback includes steps and actions the agent should take to improve the outcome.
Leading analytics platforms use historical data and real-time information to identify patterns and trends, allowing the agent to tailor the call. Disgruntled customers can be identified by their language and tone of voice. In real-time, the system can generate offers for retention, helping reduce escalations and terminations of service.
Of course, transitioning to speech analytics requires resources. Firms will need to invest in processing power to harness the capabilities of real-time analytics. Cloud-based contact centers can tap into voice stream and IP communications infrastructure, making it easier for adoption. Training and cultural transformations are also required as this innovation changes the traditional customer service mindset.
Understanding the capabilities and impact of speech analytics is necessary for a seamless rollout. Companies need to mindfully approach implementation without overwhelming agents with multiple alerts where the authenticity is lost. Interactions between the agent and customer should be flawless, especially when the call is escalated to a supervisor. Information acquired from calls can be analyzed to identify opportunities to improve service.