Artificial intelligence and machine learning-based voice analysis models have become highly sophisticated to address contact centres’ ‘voice problem’.
Over the years, contact centres have evolved as epicentres of brand-customer interactions. These contact centers deploy a team of human agents aided by various technology solutions to respond to customer queries and complaints over calls, interactive voice response, emails, and text messengers. Automation solutions have helped contact centres reduce the query turnaround time and enhance the customer experience by providing accurate answers. However, customer experience analysts often question the ability of contact centers to understand the true intent of a customer’s call and offer a personalized solution. In other words, the general opinion is that it is tough for contact centre agents or automated solutions to understand what exactly a customer may have gone through. Let us test whether or not this notion is true:-
Years of research on human behavior and anecdotal evidence suggest that verbal communication is the best form for accurately narrating messages and emotions. People can better communicate their feelings and internal states through their voice than emails or texts. Thus, voice communication allows the listeners to focus their attention on understanding the emotions of the speaker. However, a human agent or an automated voice response system at a contact centre receives hundreds, if not thousands, of calls every day. It is impossible to infer anything from this data manually. Moreover, voice is a form of unstructured data. Every voice-based customer conversation has several qualitative parameters such as engagement, interest to purchase, satisfaction, irritation, anxiety, etc. Thus, it isn’t easy to accurately measure a customer’s intent through her voice.
Thankfully, artificial intelligence and machine learning-based voice analysis models have become highly sophisticated to address contact centres’ ‘voice problem’. Here’s how contact centres are using these solutions to decode a customer’s voice and offer personalized solutions to their customers-
1. Customized voice analysis process- Brands can collaborate with a technology provider who helps them construct and configure voice processes based on their incoming and outgoing calls. The system is based on a robust design, development, and feedback loop. First, it collects historical data from customer interactions, such as transcripts and recordings, to feed the AI-Powered Contact Center engines. Then, the engine uses a sophisticated algorithm to recognize the intent, vocabulary, nuances, and conversation variations to offer tailored responses in real-time. After the creation, the customized solution can be integrated across multiple channels to automate the entire voice-based customer journey.
2. Real-time voice analysis: Often, contact center executives, as well as automated systems, face a challenge with analyzing voice calls as it is subject to background noise,
variety of accents, inconsistent quality, and dual-channel separation. A sophisticated speech recognition system can help process audio data by converting the speech to text in real-time. The system leverages Natural Language Understanding (NLU), Natural Language Processing (NLP), and Robotic Process Automation (RPA), etc., to achieve this conversion. These high-quality transcripts, content summaries, and knowledge-based retrieval further fuel the system for accurate sentiment classification, empathy analysis, and improved customer response.
3. Omnichannel deployment and integration: Although the system is primarily designed for voice calls, it is flexible enough to be deployed across channels such as emails and messengers. Moreover, it can be easily integrated with any CRM, drives automation, and provides human workforce training without many changes in the current systems.
Voice-based technologies for consumer engagement are gaining prominence due to their speed, convenience, and multi-tasking abilities. Therefore, it is important for brands to offer high-quality, personalized, voice-based customer support. Brands that solve the ‘voice problem’ will have an unparalleled edge in terms of customer experience.
Source: Business World
