Customers have conversations with more than one department in your organization during the customer lifecycle journey. Once they move out of sales, they can interact with individuals in service, support, and even your billing departments. According to Ventana Research, the majority of these interactions take place via voice conversations, but other communication channels are gaining popularity at a rapid pace.
It should come as no secret that many organizations rely on speech analytics to analyze and interpret customer conversations. In fact, according to Ventana’s new research Putting Customer Conversations to Work:
- 1 in 5 organizations use speech analytics technology
- An additional 36% plan to use it in the next two years
- The top 3 reasons for using new analytics has to do with customers
Speech analytics analyzes conversations across various touch points and uncovers trends that organizations might not be able to detect otherwise due to time and resource constraints.
Artificial Intelligence and Machine Learning Trends
As artificial intelligence (AI) and machine learning (ML) continue to see growth in technology advances, speech analytics grows in value along with it. By combining speech analytics with AI/ML, companies can:
- Improve first-call resolution rates
- Automate cross-sells and upsells to customers
- Predict customer sentiment
- Uncover customers that need additional attention
- Automate the analytical process and review
AI already hasan impact on customer experience and will continue to drive more meaningful change as the technology matures. Today about 20% of call centers in the US use speech analytics to analyze their customer interactions, surfacing intelligence such as customer preferences and agent performance, and predicting outcomes such as a customer’s likelihood to cancel service or make a purchase. Speech analytics is fueled by speech recognition which has greatly improved in accuracy in recent years due to AI and the use of deep neural networks (systems that can continually improve the language models that convert speech to text). By using such solutions, organizations are improving the performance of their agents, handling calls more efficiently, maintaining compliance, and driving more revenue.
A core capability of speech analytics solutions is automatically categorizing calls as containing specific behaviors or events. This automated tagging creates maps or blueprints for customer interactions, which will continue to become more detailed over time, identifying the optimal path to a desired outcome for any given type of interaction.
Voice conversations may soon meet their match, but the voice of the customer will always be present and require attention. Organizations that want to create a better experience for customers need to start by listening to customer conversations today.
The report Putting Customer Conversations to Work highlights the importance of analyzing customer interactions and why organizations can’t afford to wait. Read the full report from Ventana Report to fully understand the significance of speech analytics and the rise of artificial intelligence and machine learning.