In the world of artificial intelligence and machine learning, intent classification is the process of classifying customer intent by analysing the language they use. For example, a customer who types "How can I find the status of my order" in an enquiry is probably looking for, well, the status of the order. The machine understands this intention and directs the customer to a customer service representative who can handle the query.
Why is intent classification important for customer service?
Intent classification is important because correctly classifying the customer's intentions in advance leads to a much faster and more frictionless experience for the customer (and also for the agents involved). The agent's time is not wasted on poorly targeted customer questions, and more importantly, the customer's time is not wasted.
Efficient intent classification doesn't just find out what the customer needs. It can go as far as determining customer sentiment and dissecting when a customer is a VIP or otherwise deserves faster service.
In short, the ability to interpret what a customer is looking for, no matter how they formulate their request (including typos and bad grammar) is the key to solving customer problems quickly.
How Trendskout supports Intent Classification
Trend-skout intelligent intent classification, powered by a type of AI that machine learning is called freeing your team from manually classifying inbound queries with an AI-powered intent classification engine that allows you to customise and deploy AI models that automatically label inbound customer queries. The AI algorithm only needs to be trained once and outperforms standard keyword automation. It also continuously improves over time.
The state-of-the-art algorithms that power Trendskout are already helping companies that rely heavily on NLP ea. Best of all, Trendskout's intent classification platform does not require engineers or data scientists to operate. It is designed for non-technical users such as customer service managers.