Over the years many organizations have tried to build a solution in order to anticipate the necessities of their customers and provide solutions to their queries related to products/services. Call centers tend to customer’s inquiries through telephones which can be inbound (e.g. Attending to customer’s queries) and outbound (e.g. Telemarketing).
Everyone would have faced the worst queuing up, possibly pressing your keypad a whopping number of times and listening to softly played music until you talk to an actual live agent.
At the end of all the fuss we end up repeating all the information again.
Hmm! Frustrating, ain’t it?
These can be discussed in terms of:
- Customer Experience
- Huge Business Expenditure
- Deep and Complex IVR (Interactive Voice Response) Tree.
- Customers Repeating Information more than once
- Agents searching for information thereby increasing the wait time.
Huge Business Expenditure:
Number of requests to call-center have increased massively in the past decade. The preference of the people has always been voice rather than other services such as chats or emails. Most of them are just routine calls, such as troubleshooting network issues (Internet Service Providers) and Debit card blocking/unblocking complaints when it comes to Banking Sectors. Live agent resources could be cut down if these routine calls are avoided to an extent.
“Focus on the Solution, Not the Problem”. With the advent in Natural Language Processing(NLP) chat-bots can easily decipher our intent, emotions and sentiments based on the way we interact.
There is ample evidence that Artificial Intelligence simplifies many routine things and daily tasks, changing our lives for the better. AI has been the buzzword around the business circle making it an unavoidable technology to account for. Creating computers that can understand natural language has always been the technology that surrounded homo sapiens’ speculation. The growth in Natural Language Understanding has quenched the thirst of longing.
Natural Language Understanding(NLU) and Natural Language Generation(NLG) are very promising areas of Artificial Intelligence. According to GlobalNewsWire forecast, the global NLP market accounted to hit a market value of $28.6 billion in 2026. Chat-bots exploit NLU, i.e., in simple words it develops the ability to understand what the user actually says.
Call centers are the best market to implement NLU algorithms, where chatbots could perform routine works and also works as an advisor to the live agents.
Lets checkout different places where an AI agent becomes handy.
Virtual Agent: Automates most common transactions and passes on complex transactions to live agents. It propagates all the context gathered during calls to the live agent. More interactive, informative and quicker than IVR.
Agent Assist: Pulls out contextually similar contents from the Knowledge Base and presents it to the Agent, thereby reducing the waiting time.
Conversational Topic Modelling: Discover the topics for which customers reach out to you and how they articulate. This is essential to update the Knowledge Base and produce more improved results in future. Thereby the system gets better and better.
AI can be better agents and the one way it does it is through AI-powered Knowledge bases. In customer service jobs, agents have to quickly search through relevant documents to find a solution to a customer’s problem and this has to be pretty quick. An AI-powered Knowledge base can quickly traverse through documentation by using key-phrases and deliver this straight to the agent thereby reducing the time. This surely inspires the confidence in the brand/product.
So, how to build a powerful Knowledge Base?
The main factor here is to understand what the customer wants, it includes discovery of the topic on which customer has to be serviced. Each time a customer calls, call logs are collected in order to generate training data for different topics. Any ML algorithm can be used to predict the needs of every user.
Once the topic is chosen, important keywords and top sentences used by the callers to articulate those topics are collected. ML algorithms along with human-supervised validation makes the system more robust.
Whenever an AI agent fails, the stored recording serves as the Knowledge Base thus making the chatbots better over time and much more adaptive to specific business cases.
The world now is adapting more towards AI-driven solutions. It is pretty clear that AI cannot take the position of human beings but sure it can assist them thereby increasing their productivity and is a boon for any business.
For all the promotions around AI Chatbots, few companies have embraced it in call center operations. But the rate of acquisition is going to rise up in the following years primarily because of the cost reduction and personalized experience it offers. And sooner chatbots being drafted to other businesses is not too far away.