Artificial Intelligence provides 24/7 availability, quick response using Machine Learning, load scalable systems, etc in Customer Service.
Customer Service Systems provide assistance to the customer for planning, training, and troubleshooting of a product. Depending on the type of business, there are different channels of interaction like a web page, e-mail, on-site support, android application, telephone. Business giants like Netflix, Amazon, Zomato, Uber where customers need their issues to be solved quickly cannot entirely depend on the manual solution for every customer. An automated solution helps in clustering similar issues and forming a base level auto solver for common problems in the product. If any particular issue requires attention then a manual solution can be provided.
For any business, the Customer Lifetime Value(CLTV) is very important for Overall growth, Reputation, and Brand Marketing. Better Customer Experience forms a positive image of the brand. Artificial Intelligence provides 24/7 availability, quick response using Machine Learning, load scalable systems, etc in Customer Service.
The following are the areas where AI can help at the different levels of Customer Service Systems.
Techniques – Seq2Seq Models, Encoder-Decoder RNN.
Techniques – Sentence embedders like Doc2Vec, BERT, GloVe.
Techniques – Keyword Extraction – TF-Idf, RAKE, CountVectorizer.
Word embedders – Word2Vec, BERT.
Similarity – Euclidean distance, Cosine Similarity, Pattern matching.
Techniques – Many to One RNN models, Support Vector Machines, Decision Trees.
Chatbot Techniques – Application integration (like Messenger, WhatsApp), RASA, NLP for analysis models.
Techniques for reply generation – Context-based recommendation system created for conversation dataset.
Techniques – Support Vector Classifier, LSTM, Convolutional Neural Networks.
Once the conversation is closed an auto-generated unified report can be created. This helps the organization to understand the areas of improvement for the system as well as the agent. Report if converted to a metric value using the sentiments, average resolution time, average response time, etc as parameters reduce the task of the senior agent. If the report itself mentions the areas of improvement, forms a complete product for enhancing customer satisfaction.
The customer service system is the backbone of any business. Today, Customer Service as a Service has provided opportunities for businesses to add the AI element to their customer relationship with investing the development time.
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