According to IBM, an American multinational technology company,
“Machine learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so.”
Machine Learning leverages trained algorithms to find patterns in massive volume of data and helps in the process of predictions and decision making. Machine Learning is widely used in various sectors across the globe. One of the business areas that is benefiting from ML is customer service. ML plays a significant role in providing efficient customer service and improving the customer experience.
Here, let us briefly discuss how machine learning is benefiting customer service.
Quicker, Efficient and 24/7 Assistance
One of the worst experience that businesses can offer to a customer is to make them wait. Customers hate to wait when they need help regarding any issue or query. When customers contact support service they expect a quick response and faster resolution. However, businesses that leverage the traditional way of customer service fail to deliver a favorable response to the customer. Customers are either routed to wrong agents or they are made to wait in long call lines which is a time-consuming and stressful process for both customer and the business. This way customers will lose faith in the brand.
In this regard, Artificial Intelligence, with Machine Learning (ML) and Natural Language Processing (NLP), has proved to be the best solution. Machine learning capabilities with NLP tools assist the system to understand and interpret human language. It can also examine the emotions involved in the text or voice of the customer with Sentiment Analysis. This will help enterprises to provide quick and efficient customer service to all their valuable customers.
Offer a Hyper-Personalized Experience
What do we do when we receive an irrelevant notification, messages or mail? We just ignore it, right? Meanwhile, when we receive a personalized message that proves to be relevant to our current situation we feel engaged.
Hyper-Personalized is the path that leads to better customer engagement. It is not about just inserting the customer’s name in some random messages and deliver to them. Understanding your customer is the first step towards personalization.
With machine learning technology, the process of customer personalization has become much easier. ML assess customer data including purchase history, past interactions with the brand, and other metrics and utilize this valuable information to provide a personalized experience to the customer. Hyper-personalization improves customer engagement and increases the chances of positive responses from customers.
Identify the Behavioral Pattern of the Customer
Understanding the need of the customer will assist an organization to improve the customer satisfaction level. To understand your customer, you must have an in-depth knowledge of their consumer behavior. Machine learning analyzes customer data and learns from their previous actions, preferences, search history and past purchase history. Then it identifies the pattern in customer behavior which will allow the system to understand the need and interest of the customer and provide real-time recommendations and assistance, allowing organizations to deliver efficient customer service.
Spot the Fraudulent Activities
Security is one of the most important pillars that hold any organization. In today’s digital era, it is very important to safeguard your customer data and protect it from cyber-attacks. Fraud is a big concern for every business across the globe. Businesses worldwide are finding every possibility that offers an extra layer of protection to guard against fraud. Fraud during online payment is a major concern that customers and businesses, both are worried about. Payment fraud will lead to customers losing faith in companies.
However, fraud detection has become easier with machine learning technology. Integration of online payment system powered by Artificial Intelligence and machine learning algorithm analyzes from past transactions and historical fraud patterns. It learns from the previous data and recognizes inconsistency in any future transactions and block it before the payment happens. This way, it detects any fraudulent activity and eliminates the risk of a breach in customer data.
Predict the Customer Intent
The best way to provide efficient customer service is to detect in advance why the customer is contacting customer support. If a support agent gets an idea about customer intent, the agent can make the whole process faster and easier. But how to predict the customer intent? The answer is Artificial Intelligence with Machine learning.
Imagine a scenario where a customer contacts the customer support service from a specific location regarding a particular issue. AI can store this inquiry in the form of data. When another customer contacts from the same location regarding the same product, ML recognizes and learns from the previously stored data which allows the system to have an idea about the customer intent. This way, the agents can provide an improved and efficient customer service.
From predicting customer behavioral patterns to detecting fraudulent activities, Machine learning has become an important factor in providing efficient customer service. Its ability to deliver a hyper-personalized experience is improving customer engagements. With the assistance of NLP and sentimental analysis, ML has enabled enterprises to understand customer emotions in text and voice-based data. ML is easing the load on human agents by handling tedious and time-consuming repetitive tasks. Overall, Machine learning is improving the efficacy of business and enhancing the number of loyal customers.