What Is Intent Classification?
Intent classification is an artificial intelligence (AI) and machine learning (ML) process used to automatically identify and classify user intent. When intent classification software receives a query, it analyzes the customer’s message for keywords or phrases, such as “I need to locate my package,” and categorizes their query based on the text.
Companies can typically create their own categories to sort customer messages, using tags such as:
- Demo request
After categorizing the customer message, the software either directs the user to a live customer service agent or a chatbot programmed to answer shopper’s questions.
Intent classification does more than categorize user messages, though. The AI algorithm creates a fast, convenient, and smooth experience for your customers and customer service agents.
Rather than wasting their time on low-priority messages, customer service representatives can devote themselves to meaningful conversations and personalized care. At the same time, intent classification algorithms can connect website users with a chatbot for immediate assistance with minor issues, such as shipping, order status, or returns.
Why Is Intent Classification Important for Customer Service?
Intent classification works to enhance, streamline, and systemize the customer service process. Without intent classification software, customer service agents have to sort through customer messages, answer phone calls manually, and monitor website- or social media-based instant messaging platforms to understand the intent behind each query.
With intent classification software, the trained algorithm analyzes, tags, and assigns messages based on intent. The software will escalate messages to customer service agents or assign tasks to chatbots when possible. As a result, both customer service representatives and customers can enjoy benefits, such as:
1. Improved Customer Experience
Intent classification software allows your brand to automatically understand customer intent, resulting in faster, more appropriate care. With modern consumers expecting a response in less than six hours, intent classification tools are a crucial addition to any customer relationship management (CRM) software.
2. Consistent Care
Even the best human customer service representatives misread or misunderstand messages. On the other hand, machines consistently use the same processes, criteria, and parameters to analyze and categorize data. As such, customers will always receive the support they need, when they need it.
3. Increased Conversions
Finally, intent classification software enables your company to determine which customers are most likely to purchase. After identifying consumers, your team can make immediate contact, resulting in a boost in conversions by as much as 391%.
How Does Intent Classification Work?
Intent classification tools use machine learning and natural language processing (NLP) to analyze and associate phrases with specific customer intentions. However, you’ll need to train the software with text and data models – known as training data – before launching the program.
During the training and data analysis process, intent classification software examines emails, text messages, and chat responses, then relates the text to a tag, such as “Need Help.” You can even pair your company’s intent classification software with text extraction tools to identify relevant data during conversations, such as names, dates, and locations.
For example, if a customer initiates a website chat and says, “I need to book a hotel in NYC from November 11-14,” the intent classification software would categorize the message as “Make a reservation,” while the text extractor would extract NYC and November 11-14.
Using Intent Classification for Better Customer Experiences
Intent classification software helps your staff create a more efficient, positive customer service department. Both agents and customers can reap the benefits, ranging from a consistent care experience to increased conversions and happier customers. While the software requires training, the results are well worth the effort needed to develop a fully functioning intent classification tool.