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    1. Home
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    3. >The importance of voice in the moments that matter
    Business

    The Importance of Voice in the Moments That Matter

    Published by Gbaf News

    Posted on September 6, 2019

    6 min read

    Last updated: January 21, 2026

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    A customer service agent engages with a client via phone, emphasizing the significance of voice in enhancing customer experience in banking and finance. This image illustrates the article's focus on the need for personalized support in crucial moments.
    Customer service representative assisting a client over the phone - Global Banking & Finance Review
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    Written by Andy White, CEO Contexta 360

    As the digital revolution has provided consumers with more information, so their relationship with vendors that they purchase products from has fundamentally changed. Power is now firmly with the buyer; and this means customer experience is the new battleground on which businesses thrive or die.

    As consumer expectations continue to rise, businesses who fail to transform their customer experience functions risk losing ground to competitors who have succeeded in combining big data insight with products and services, enabling them to provide seamless support for their client base.

    Digital channels undoubtedly have a pivotal role to play in this transformation. Growing familiarity with chatbots and smart Interactive Voice Response systems means customers are choosing (or being forced) to self-serve in order to solve straightforward queries. However, for more complex problems, customers still reach for the phone – in fact, they can be very frustrated if a human option isn’t easily accessible. Even if they are available, if they do not know what the customer has said in another channel this raises frustration immediately. The challenge for contact centres is getting this balance right so the service is cost-effective for the business and high quality for the customer and that’s not always achieved successfully.

    Contact centres don’t meet customer expectations

    Businesses face twin pressures when it comes to contact centre management. First, they are now operating in an environment where customer expectations increase exponentially in proportion to the data they share or have access to indirectly.  When a customer calls in, they expect the contact agent to know about them and their history with the company.

    Without a complete 360-degree picture of customer interactions, businesses risk failing to meet expectations, which are only going to continue to rise as customers expect digitally enabled businesses to make their experience better.

    The second pressure is the imperative to reduce costs of customer service and increase efficiency in the contact centre. Many contact centres are motivated to digitise primarily to control costs – it’s much cheaper for customers to self-serve through chatbots or emails. However, reducing the direct costs of the contact centre through increasing automation can negatively affect a customer’s experience, causing an increase in less- easily-defined costs related to the company’s reputation for customer care.

    So, for complex customer problems it is not always in the best interest of the business to fully automate their channels. Intelligent escalation systems should detect when a chatbot interaction should be elevated to a human agent and then agent ‘augmented support and assistance’ can assist the live operator so they are fully briefed before the call and during the call. Many automated interaction technologies and  deployments don’t have effective live agent safety nets attached, let alone the augmented support. This means that the lack of effective escalation mechanisms introduces customer service risk.

    Many call agents are overloaded. They have to process all customer data and external data in a maximum of five seconds before they answer the call. This leaves the high possibility that the agent won’t be able to fully understand all of the information relating to the customer, resulting in failed first-time call resolution and frustrated customers. Furthermore, call centre managers are in an extremely difficult position, as much of the customer-agent interaction is invisible to them. They cannot possibly listen in to 100% of the calls. Now speech and chat analytics can detect topics, questions, compliance, bad phrases (as well as good), clearly identifying ‘problem’ calls or opportunity calls and conversations.

    How to solve customer experience challenges

    Voice is the prestige channel in customer interactions and by unlocking valuable insight in customer calls, using speech analytics and AI, businesses can improve their customers’ experience and gain critical insights to shape strategic decisions, whether that be in real-time or analysing historical conversations in any channel.

    The critical first step to unlocking the value of voice is overcoming the issue of inaccurate and limited data entry by contact centre agents. That means capturing the content and the context of the conversation and accurately converting speech into text. Highly accurate speech-to-text that can also detect your industry lexicons and your own brand terms is just the foundation that is needed to build an advanced AI and conversational analysis solution. Without this, the AI house you build on this foundation will be weak.

    The second step is to turn the core conversation (Voice / Video / Chat / email / form) into understanding. The customer may not have mentioned “trade-up” or “buy”, or “angry” and “complain” but the NLP and neural networking can detect these key findings without them being mentioned, along with other key data on sentiment, topic detection and so on. Blending this across multiple channels solves a key contact centre challenge: the ability to meet client expectations because agents do not have perfect knowledge of the customer situation, at the moment the call comes in, or the agent is not trained on a particular situation or product. Lack of complete information (customer and or product) leads to longer calls and greater customer frustration, which limits any chance the agent might have to turn the call into an upselling or cross-selling opportunity. Agents need to be able to detect the subtle differences between customers and respond to nurture them accordingly. That is where AI-derived ‘proposed next action’ and ‘sentiment and intent analysis’ combined with human empathy and intuition helps meet customer expectations.

    The third step is to implement real-time intelligence to boost agent performance. As the call progresses, real-time speech analytics listens in and guides the agent, detecting topics, questions or objections and suggesting appropriate actions. This ensures that agents don’t miss an opportunity to resolve the issue or add value.

    Now is the time for organisations to really start exploring the extensive insight and strategic value that speech analytics and conversational computing can offer. Speech analytics offers many benefits such as accessibility, meaning it can now be deployed by more organisations, at a lower cost and with a high degree of flexibility and scalability.

    Additionally, speech analytics and conversational computing are now easy to integrate, meaning that the risks of experimenting with new solutions are reduced. Conversational computing is coming of age as a powerful tool for brands to improve the customer experience that is so critical to continuing success. In the critical customer moments that matter, this is the edge that businesses need.

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