The same pre-trained deep learning model architecture used for text classification and entity recognition is also used to create our powerful text summarization feature, tuned specifically for summarizing call or chat transcripts. Text summarization is the process of automatically generating a shorter version of a piece of text that retains the most important information from the original. In the case of call or chat transcripts, this involves identifying the key points and topics discussed in the conversation and generating a summary that captures the essence of the conversation. The pre-trained summarization model is able to identify the most important information in the text and use it to generate a concise summary. This feature is extremely useful for quickly and easily understanding the content of long or complex conversations.
There are numerous benefits that a customer service organization can derive from being able to summarize contact transcripts using natural language processing (NLP) techniques including:
- Improved efficiency: Summarizing contact transcripts can help customer service organizations process and analyze large volumes of text data more efficiently, as it allows them to quickly extract the key points and main themes from the transcripts.
- Enhanced customer understanding: Summarizing contact transcripts can help customer service organizations better understand the needs and concerns of their customers, as it allows them to identify patterns and trends in the feedback and inquiries they receive.
- Improved decision-making: By summarizing contact transcripts, customer service organizations can gain insights into the types of issues and problems that are most commonly reported by their customers, which can inform decision-making around resource allocation and product development.
- Enhanced customer experience: By providing customers with concise summaries of their interactions with customer service, organizations can improve the overall customer experience and demonstrate their commitment to meeting customer needs.
- Reduced cost: Summarizing contact transcripts can help customer service organizations reduce the time and resources required to process and analyze large volumes of text data, which can lead to cost savings. This could include reductions in AHT as advisors are no longer asked to spent time creating a contact summary as part of a “call wrap”