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How Natural Language Can Improve the IVR Experience

Interactive voice response systems have been around for decades. These pre-recorded systems provide options for customers so that they can resolve requests with a contact centre. In most instances, this element removes the need for a human agent to be involved in the completion of the enquiry, reserving this resource for more complicated tasks. 

Decisions are made via voice or through touchpad tones depending on the set-up of the IVR system. They are commonplace in most call centres; however, in this feature, we’ll specifically look at AI-powered IVR systems. What’s more, we’ll explain what natural language processing (NLP) is and how it is enhancing IVR systems for support centres. 

When Was IVR Invented?  

A lightbulb in a chalk thought bubble.

The technology was invented back in the 1930s when Bell Laboratories discovered how to synthesise speech. It wasn’t until the 60s and 70s, however, that this technology was put into good use, incorporated into the then infant call centres. 

Bell Laboratories continued to trial their IVR technology, exploring multi-frequency techniques for quicker processing with the idea of serving customers faster. By the 80s, computer systems could interpret and understand human responses, digitise speech and play it back, allowing for the smooth integration between computer and telephone data.  It was this step in IVR technology that propelled call centre businesses and shaped them into what they are today. 

IVR systems are not only considered a vital business optimisation tool for call centres, helping support teams deal with the level of demand. They are also regarded as a critical aspect of customer engagement. In a previous blog, we highlighted the problems with the traditional legacy IVRs of the past, and how these outdated systems can impact on customer experience. But with the help of the latest AI advances, IVR systems continue to develop, expanding beyond one-word inputs to understand customers in a way like never before. 

What is Natural Language Processing (NLP), and How Does it Work? 

A graphic of AI.

Natural language processing (NLP) is a type of artificial intelligence. It is why you will sometimes see IVR systems that utilise NLP as AI-powered IVRs. NLP is what helps a computer interpret and comprehend human language, with the ability to use this information to engage in conversation with people. NLP stems from computer science and computational linguistics, intending to help people communicate better with the computer systems they rely on.

Developments in computer science have seen NLP flourish and improve as experts work with it in their quest to enhance human-to-machine communication. Decades ago, only a select few could communicate with computers via punch cards. Now, our voice commands can activate devices and initiate actions on them through the computer’s use of NLP and other AI elements such as machine learning and deep learning. 

An IVR system that utilises NLP comprises of two elements which work together; these are a statistical language model (SLM) and a statistical semantic model (SSM). The language model works by recognising a sequence of words by the caller, while the semantic model determines the meaning of the words. 

These systems are programmed to understand a wealth of predictable pattern sequences from customers. For example, if the system asks a caller how they can help and the customer asks to pay their bill, the NLP system will take the input and convert it into code meaning such as: call_type =pay_bill. 

How is NLP Improving the IVR Experience for Customers? 

Two phones connected together.

1. Real, Two-Way Conversation

The first obvious benefit of an IVR system that utilises NLP is that it can communicate with your customers in a natural, human-like way. This adds value for the customer by creating a more enriched experience. 

NLP nowadays is so developed that it can interpret and decipher meanings despite any variations. This includes the language used, regional accents, abbreviations and slang or the inflexion. Not only can the system decipher the meaning of the words, but it can also measure the sentiment of the customer. This understanding helps businesses calculate emotions and perceptions toward the support experience and brand overall.

Real, two-way conversation is also achieved by giving the customer more control over the call flow. NLP allows the IVR to be dynamic, and this means the customer doesn’t have to wait to go through a menu of options irrelevant to their request. Not only does this reduce frustrations, but it also helps in replicating the format of natural conversations.  

Personalisation can also be achieved through dynamic, AI-powered IVR systems as they can utilise data on customers from other channels. This cements the feeling of being valued by the customer, helping to drive loyalty and retention. 

A man annoyed with phone conversation.

2. Reduces Customer Complaints

Sentiment analysis performed through the system can also pinpoint feedback trends. Insights go toward improving customer service, reducing the number of complaints around the same issue. One real-life application includes the Royal Bank of Scotland who use the NLP in IVR systems to identify areas for customer dissatisfaction and utilise this knowledge in improving customer support.

Did you know, for example, a dynamic, AI-powered IVR can perform regular data dips in customer satisfaction surveys? This process ensures only relevant questions are asked, optimising your surveys and reducing complaints.

3. Quicker Results

AI-powered IVR systems allow customers to get their enquiry dealt with faster, and with less effort coming from the customer themselves. Traditional IVR systems require one-word input conversations and long menus that take time to work through any irrelevant options. This helps not only to reduce the number of customer complaints (an improvement highlighted above), but customers have more control, and the call becomes more efficient. This helps to reduce call drop-offs, improving customer retention rates or in the case of debt collection, help ensure payments are received. AI-powered IVRs are worth considering for businesses who receive high volumes of calls and/or have a large number of services but don’t want to jeopardise the quality of customer interactions.

To summarise, IVR systems that utilise NLP are capable of handling complex queries. They learn from the experiences to drive customer satisfaction rates by providing an all-round better customer experience. Is your IVR technology in need of a serious update? If yes, why not get in touch with us today? We are specialists in the field, providing expert solutions to businesses just like yours for years. With a free consultation and easy integration, it couldn’t be simpler to modernise your IVR.  

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