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The future of customer contact centers

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The future of customer contact centers

Companies with large customer bases usually set up contact centres to handle customer complaints and feedback. A contact center is a central place where all customers can contact a business via phone, email, or social media platforms. There, issues are received and managed to ensure good customer experience and after-sale service.

The success of any company’s marketing and sales campaign directly hinges on the experience and satisfaction customers derive from the company when they encounter challenges. Every interaction a customer has with a company’s contact center ends up in one of these: the customer either becomes a detractor, one who actively campaigns against the company [usually on social media and by word of mouth] due to a bad experience or the customer becomes a promoter, one who actively campaigns for the company. Well, some customers are also passive and may neither promote or detract your brand.

In staffing contact centers, organizations have to recruit, train and maintain agents who will essentially be the voice of the company. Speed, accuracy and one-time resolutions are vital to the efficiency of any contact center. In order to cut down on operational expenses without impacting customer experience, companies have to be very tactical about staffing. They normally rely on projections and trends to have a feel of what call volumes may be.

But the gag is, more often than not, it gets challenging managing contact center agents sometimes. Some may fall sick, get pregnant, take days off and even quit the job. Also, because they are humans and not robots, there’s that emotional element at play. An irate customer’s tantrums are likely to set the tone for a particular agent’s day and affect their service delivery.

This is where the bots come in.

This is where the bots come in. Advances in artificial intelligence has resulted in the creation and development of bots that can actually understand and participate in human conversations. Unlike traditional chat-bots that are wired to answer a finite set of hard-coded questions, the new AI-based chat-bots are trained with data-sets of human conversations so that they can learn on their own and identify the intent behind every request or conversation, a technique known as natural language processing.

Basically we [humans] can speak, read, write, reason, analyse and understand the world around us. This is essentially hinged on how much exposure we have and the things we might have picked from watching movies, talking to others, reading books and so on. How much we know is directly related to the information we have assimilated and how much we can remember. Natural language processing is just training a machine to analyse and understand speech just like the way the human brain does. Machines can analyse large data sets rapidly and have total recall, which is something most humans cannot do and do not have.

A working example is Facebook Messenger bots. A local company, CYST, has built some AI-based chat-bots for themselves and 3NewsGh. Using deep learning and a type of Recurrent Neural Network, known as Long Short-Term Memory, the bot is able to store the state and history of the conversation to enable it handle queries as intelligently as possible. Once the bot is able to determine the intent, the required result is produced. In the screenshot below, the bot responds to a query that is phrased in Ghana’s pidgin English. By typing “What dey go on?” [“What’s happening?” / “What’s up?”], the bot automatically understands that the user wants access to the latest information and it fetches the latest headlines from the data it has access to.

Late last year, Google launched its AI-powered assistant — Google Assistant, a bot that can engage in two-way conversations. The Assistant can book tables in restaurants, add items to your calendar, remind you about your itinerary and answer general questions you may have. As more and more users keep using the bot, its database grows exponentially and it

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