Analytics Continues Its Charge Beyond the Phone
Research firm MarketsandMarkets valued the worldwide speech analytics market at $2.3 billion in 2022 and expects it to reach $5.1 billion by 2027, growing at a compound annual rate of 17.3 percent.
The contact center has always held and will continue to hold the largest share of the market, particularly as companies seek to address the increasing need to improve the customer journey and overall experience, enhance and monitor agent performance, and adhere to regulatory and compliance standards.
With speech analytics, companies can substantially increase the number of calls examined without having to increase staff. Depending on their size and call volume, some companies can analyze 100 percent of calls; without speech analytics, the percentage of calls that most companies could analyze is in the low single digits.
Now, companies are gaining even more actionable business intelligence by deploying artificial intelligence and natural language processing engines to customer conversations in multiple digital channels. Chief among them is the chatbot, as our cover story, “Speech Analytics Start Steering Chatbot Interactions,” points out.
As companies look to do more with self-service automation, speech analytics can help identify which factors are driving escalation to agents and where in the conversation flows the escalations are happening. There could, for example, be certain words or phrases that the chatbot doesn’t understand, causing the interaction to default to a human agent. It can also identify process deficiencies and provide insight into which interaction types are ripe for chatbot automation.
But perhaps speech analytics’ greatest strength, going beyond the medium or channel context, is the ability to create an overview of customer interactions so companies can have a comprehensive understanding of customer behavior and preferences.
Speech analytics’ expansion hasn’t stopped at chatbots. Companies have started to take their speech analytics systems out of the customer service realm altogether, applying the technology to sales, marketing, and e-commerce interactions. It’s being used to help salespeople identify where conversations might have gone off the rails and identify common objections customers might have. It’s being used to help marketers better tailor customer outreach to each individual buyer. And it’s being used to ensure script adherence and that the necessary disclosures are given.
Across sales, marketing, and customer service, speech analytics is also being applied to a human relations function, helping determine where employees are missing the mark, which employees need extra training or coaching, and which learnings suit their needs. As our second feature, “How Speech Analytics Helps Improve Coaching/Training,” points out, technology vendors today are uniting customer interaction analytics systems and agent coaching/training systems to identify problems during interactions and then guide agents in real time to overcome them.
“There is undoubtedly growing momentum around bringing real-time analytics and agent coaching together to drive meaningful customer experiences,” Rachel Lane, former contact center solution principal at Medallia, says in the article.
This trend, she adds, has been driven by today’s critical challenge of attrition, causing huge pressure to get new hires onboarded and ramped up as quickly as possible.
“Real-time agent coaching triggered by conversational analytics running alongside an engagement can be of great benefit to help newbie agents,” Lane says.
“By augmenting your coaching and performance management with analytics, you can create better agents and even better CX outcomes,” agrees John Thompson, head of sales at Ibex, a digital customer experience outsourcing firm.
A common theme is the need for insight to be delivered in real time. Companies can’t wait hours or even days or weeks to correct deficiencies in their CRM processes.
AI is starting to make its mark in the analytics space, and it can’t happen soon enough. Systems will only get faster, more scalable, and more capable from here. And with AI, the possibility of human error is removed from the equation, which will only improve the analysis and recommendations that come from it.
Leonard Klie is the editor of Speech Technology magazine. He can be reached at email@example.com.