4 min
Today, call centers have the unique ability to leverage all available data to drive interaction for each customer. This data includes various sources, such as marketing campaigns, the type of recently completed transaction, or the last search for a lead.
Of the many technologies that call centers may have implemented, Artificial Intelligence is one of them. AI has driven huge growth in contact centers due to widely available cloud services and machine learning tools.
AI in Customer Service Centers
There are two main types of Artificial Intelligence in BPO (Business Process Outsourcing) at the moment. The first can evaluate large volumes of data and provide information in real time so that agents have a greater resolution capacity in a call.
The second type of Artificial Intelligence in business outsourcing is conversational AI. Analyze the speech of both the agent and the caller to identify emotions and, ultimately, intention. Conversational AI is primarily used for sentiment analysis in a conversation based on vocal tics, emotional state, and general engagement level of both the caller and the agent.
Why Is AI Used in Call Centers?
Companies want to create a positive and personalized experience for customers. How? Taking into account the following factors:
1) Automation: AI automatically capture data, route calls to the right agent based on the analyzed data, and create a profile with future reference that can be used in the call center and other business areas.
2) Analytics: Contact center AI provides in-depth analysis of individual calls, making it easier for QA managers to make decisions.
3) Support: Artificial Intelligence is directly integrated with the agents’ work desktops so that they have immediate information on the captured data. The result is faster response times, a higher call resolution rate, and happier, more motivated agents who now have tools to help them improve their performance.
How Is the Call Center Scene Changing with AI?
Customer service centers strive to provide a simple and seamless experience for users as they constantly face the potential risk of losing a customer to a competitor. To prevent that from happening, contact centers have turned to Artificial Intelligence and machine learning solutions in order to help them take the next best actions, convert potential customers into customers, increase retention rates or purchase products, among others.
Business Process Outsourcing or BPO companies tend to work a lot around data. So what are the best practices for call centers using AI and Big Data to improve sales through a good customer experience?
1) Intelligent Call Routing
Call routing through Artificial Intelligence helps each customer reach the appropriate agent, taking into account the reason and complexity of the call.
2) Better Analysis of Caller Feedback
Artificial Intelligence improves call management by performing essential functions such as real-time monitoring, analysis, and support. Machine Learning performs a great part of this function. ML services help to analyze the mood and response of both the client and the agent. When used as feedback, the data allows agents to respond more effectively, increasing the satisfaction of both, compared to the previous experience.
3) Personality Profiles of Agents
While the primary goal of most call centers has been to constantly improve customer satisfaction, over time, BPOs have also realized that it is just as important to take care of agents. Each agent communicates differently and attracts a different segment of customers. Some can handle negative comments well and some cannot.
4) Taking Advantage of the Context
The context makes the process easier for the customer, since they do not need to repeat or spend a lot of time on the call explaining their problem or query. In addition, it is a key element for call routing.
AI can actively analyze a customer’s call data to predict when someone is likely to be upset and facilitate a change before that happens. This is done by capturing data points related to voice characteristics, past call history, and response from the customer service agent. Predictive analytics can help understand the problem a customer may have, thus reducing long calls, customer wait times, and more.
5) Chatbots
Thanks to the digital age, online reviews available on Google or on e-commerce sites of a product have a lot of influence on buying trends. Customers tend to use a chatbot before calling customer service. However, while chatbots and automated phone systems can guide customers in answering simple questions that may not need a human agent, chatbots are considered the first line in the customer service ecosystem.
Advances in machine learning have improved the way Natural Language Processing (NLP) is being implemented across all industries. To make chatbots take advantage of conversational text, assistants with Artificial Intelligence technology are now being introduced to better respond to customer prompts, in the same way that the voice assistant of Google, Alexa or Siri is used.
In conclusion, Artificial Intelligence (AI) and machine learning (ML) are transforming call centers, providing an excellent customer experience (CX). This wave of AI, affecting contact centers, is the best opportunity for the CXO (Director of Experience) to be the first to adopt cutting-edge technology and bring its call centers to the forefront of the revolution driven by Artificial intelligence.
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