How can AI enhance the process of customer service ?

In these times, where customer loyalty is a rare phenomenon, and the customers are ready to switch from one company to the other at the drop of a hat, the only thing that can help organizations retain their customers is enhancing the services offered. The outdated IVR systems can be very frustrating, especially if customers get through the call after navigating through various options and are put on hold for several minutes. The only solution to this challenge is the adoption of Artificial Intelligence (AI). As per Gartner’s Press Release dated 19th Jan 2022, “Customer Services and Support Leaders should use AI to offer Insights or Predictions, Improve User Experiences, and Optimize Business Process Automation.”

Most of the sectors like Telecom, Banking, Retail, Transportation, E-Commerce, Healthcare and BPO Services are actively employing AI techniques and are reaping the benefits. The AI is being deployed in the form of Chatbots, Conversational AI (CAI), Robotics Process Automation (RPA), Machine Learning (ML), Natural Language Processing (NLP), or Digital Assistants in the field of Customer Services.

Let us explore a few use cases of AI in Customer Services:

  1. Chatbots – This is the most prominent and successful use-case of AI in Customer Services. Bots can be easily integrated with various channels and help respond to routine customer queries easily. It eliminates the need to set up huge call centers to cater to the customers from different time zones and preferable timing to interact. As per Gartner, “By 2022, 70% of white-collar workers will interact with conversational platforms on a daily basis.”
  1. Personalization or Customization – AI-based systems ensures that the data related to the customer’s past interactions, behaviour patterns, and other details are stored appropriately. This information helps formulate apt responses and give the customers the most personalized experience. These customized experiences can help influence the future decisions and attitudes of the customers.
  1. Data Collection – Artificial Intelligence is capable enough to collect data by interacting with the customers directly. Unlike the early days, it is no more dependent on the existing database or the data entered by the agents. The data gathered can be analyzed to identify the behaviour patterns and respond to the customers. These interactions can support the customer during the purchase journey and can tilt the customer to decide in favour of the company’s products and services.
  1. Social Media Monitoring Solutions – Identifying the issues customers face is one of the best ways to create customer-centric solutions. By leveraging Natural Language Processing and Machine Learning, it becomes easier to identify the customer’s challenges, contact them and respond automatically. It is now a known fact that companies who engage with their customers on social media can reduce the cost per contact heavily, and their customers tend to spend more.
  1. Call Classification systems – Bots leverage the power of NLP to understand the customers’ expectations and connect them with the right agent. It takes away the load from the representatives, and they can offer quicker resolutions, thereby reducing the average call timings.
  1. Sentiment Analysis Solutions – Sentiment Analysis or Emotion AI solutions are utilized, to logically estimate a customer’s emotions by analyzing the textual, audio or video signals. It allows the system to support the customer service representatives and guide them by fetching responses to customer queries ensuring a positive outcome. The advanced systems even help transfer calls to the call centre representative’s superiors in an effort to improve the experience and increase customer satisfaction levels.
  1. Reduced Call Waiting time – The customer experience is highly compromised if the customers are left on call waiting for a long time. In such situations, Conversational AI can be integrated with the system to have human-like conversations with the customers and respond to their routine queries instantly. For more complex queries, the calls can be transferred to human agents after collecting the relevant details, ensuring the issue resolution in a minimal time. Most companies are experiencing a drop in the call waiting time by deploying such sophisticated solutions. It also helps ensure that human resources can focus on more complicated tasks or queries and do not need to waste their time on simple stuff.
  1. Predictive Analytics – The data collected using AI-powered solutions can help brands get deep insights into the customers’ actions, interests, and drive. Brands can easily leverage this information to design targeted campaigns to reach customers with their offering at the right time. The analytics derived from this data can become the guiding light to resolve customer issues and provide the right solutions. The AI can help remove the chances of humans missing the information due to boredom or bias and ensure the opportunities are not lost.

As per Gartner, 68% of Service Leaders believe AI bots and VCAs (Virtual Customer Assistants) will be of significant importance for them and their organizations in the next two years.

Apart from Gartner, many other research organizations are also predicting the growth in AI usage in the years ahead. Keeping that in mind, Business process services are integrating AI with customer services solutions to enhance the overall experience. They are even taking a step forward and providing these solutions as Business Process as a Service (BPaaS). To stay ahead of the curve, investing in emerging technologies is no longer a choice but the need of these times.

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