| BY RAIF SHAF| INTERACT CX
Humans are wired to want to find quick and efficient ways to do things. We’re all antecedents of this paradigm shift from linguistic and philosophical approaches to the mechanical utilization of Alan Turing’s automaton called “Bombe” (or Christopher) which was able to decode the German communication encryption device: “Enigma” in World War 2, under the same premise.
With this legacy in mind, from the first stone tool, the waterwheels, windmills, steam-powered machines to the sophisticated cloud and AI technology that we have today, all are reminders of progress towards the “Automated Today”.
It is the partial or total replacement of people with machines to undertake repetitive jobs in order to decrease or eliminate human effort and increase efficiency. With the economic and financial climates we are facing in today’s world and the pace this dynamic is changing, achieving SLAs and boosting KPIs through automation is at the cornerstone of success and delivery.
The modern-day Contact Center has a detailed history of its becoming. Call forwarding was initially enabled by Private Branch Exchange (PBX) and Private Automatic Branch Exchange (PABX) systems in the 1920s. Later enhanced with various forms of systems like Automatic Call Distributor (ACD) and Interactive Voice Response (IVR) etc. These types of automation drastically cut down on the amount of work that people had to do. They have become very efficient over time and are still being used today.
With the rise of the internet and the rapid emergence of other tech advances like social media platforms and artificial intelligence (AI), it became essential for Contact Centers to not only use these tools to improve efficiency but also to cater to customers on all channels that are being widely used. Advanced technologies such as Natural Language Processing (NLP) engines, Machine Learning, Real-time Speech and Predictive Analytics etc. make these goals possible. Incorporating these innovations also paves the way for Contact Centers to grow into a true Omni-channel.
Starting from the most fundamental instruments, we have the Interactive Voice Response (IVR) system.
IVRs widespread use in Call Centers started in the early 1990s. IVRs interact with the caller, either with voice or DTMF tones through the keypad, and collect relevant information and route them to the most appropriate agent to resolve their issues quickly. Early IVR systems were designed to recognize only single words or a series of words that were programmed into the system, and the routing took place based on that recognition of words. Newer IVR solutions are coupled with Automatic Speech Recognition (ASR) functionality which has the capability to interpret a broad set of words and the caller's intent to route them to the correct agent accurately.
ACDs are conditional call routing systems that are pre-programmed with basic if-then conditions and different rules relevant to the industry it's being used in. Conditional Call Routing examples include skill-based routing, most idle routing and circular routing.
IVRs and ACDs go hand in hand in constructing the basic Customer Journey.
Moving on to the more advanced components, we have Natural Language Processing (NLP).
NLP is a form of approach to Artificial Intelligence (AI) that originated from the idea of Machine Translation (MT) during WW2. The primary concept was to translate one language to another which later on developed into the notion of the humans communicating with machines. We can think of a language as a set of rules or patterns which can be defined for the processing engine.
The NLP engine allows for the system to understand text or speech by breaking it down and encoding it into an understandable format.
There are two sub-categories/counterparts to NLPs. Natural Language Understanding (NLU) and Natural Language Generation (NLG).
NLU further processes the speech or text input and figures out its intent, context and emotion by performing different analyses like Syntactic, Semantic and Pragmatic.
NLG then generates the appropriate response in text or speech.
Machine Learning (ML) is another important means of achieving an effective system. Arthur L. Samuel was a pioneer in the field of artificial intelligence. In 1959, he had an epiphany that instead of teaching the machine how to perform tasks and give it the necessary knowledge, perhaps enabling it to think and learn for itself could be attainable. His Checkers-playing algorithm was one of the first demonstrations of the core notion of artificial intelligence. With the vast ocean of data generated and collected every day, incorporating such said algorithm with a system and if utilized proficiently, could establish exceptional capabilities for an organization to stand out in today’s competitive market.
Now, imagine an NLP integrated IVR system with speech analysis to detect patterns and tones, and adding a forecasting mechanism to it will make one robust solution offering a spectrum of possibilities. Equipping a Contact Center with these automations will enable it to redefine CX and deliver seamless and fulfilling experiences for its customers.
With fast-evolving technology, there is a multitude of solutions that these advancements might be put to use. Discover them with us and dive right into it!