The customer service industry is witnessing a technological breakthrough with AI-powered digital solutions. Advanced automated systems are changing the way users buy a movie ticket, book a hotel room, reserve a restaurant table, or order a pizza. AI-enabled customer support assistance is set to replace any interaction with human agents. Overall, implementing AI will help customer service platforms to resolve customer queries accurately and timely.
NATURAL LANGUAGE PROCESSING - Categorization
Chat / Email / Topic Modeling
Each day customer service teams spend a huge amount of time reading and resolving chats and queries. AI techniques like NLP (Natural Language Processing) make this time-consuming and monotonous task much easier and convenient. This helps in attending to bulk of customer queries within a short time and achieving customer satisfaction.
NATURAL LANGUAGE PROCESSING - Content Moderation
Customer service platforms get a huge volume of chat messages from users. They face a tough task while dealing with toxic or offensive phrases from unhappy customers. The customer service industry uses NLP-based algorithms to analyze chat text in real-time and provide an immediate response to users. NLP is used to develop chat moderation solutions that detect normal messages and chats containing offensive language. These moderation solutions are more accurate and cost-effective than manual moderation systems.
NATURAL LANGUAGE PROCESSING - Named Entity Recognition
Improving customer support strategy and efficiency is a high priority for every company. Using NLP, companies can get a solution where they see the chat graphs, comparing the chat with the time trends on an hourly, daily, weekly or monthly basis. Analyzing the peak hours, waiting times, response time, and chat rating helps companies to retain their customer base by optimal utilization of resources.
NATURAL LANGUAGE PROCESSING - Sentiment Analysis
Chat Sentiment Analysis
Understanding customer emotions is essential for the success of every business. Sentiment analysis allows companies to identify customer feedback toward products, brands or services in an online conversation. Chat sentiment analysis gives a fair idea about a company’s performance. It also highlights the aspects that need improvement like personalization, tone, efficiency, etc from customer’s point of view.
Try out these ML models
Q&A Topic Tags
Tag user-provided topics from Q&A sessions
Contact Center Topic Modeling
Discover which topics your customers are contacting you about
Customer Reviews Moderation
AI for extracting product mentions and popular terms from customer reviews
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