In this webinar, we will explore an implemented advanced analytics system, which leverages the power of machine learning to effectively track and categorise large amounts of textual data in near-real time, such as emails, chats, and messages.
NLP Customer Care with Advanced Analytics
May 31, 2023
4:00 PM - 4:30 PM
About this webinar
By attending this webinar on advanced analytics systems, professionals in customer service, marketing, and data analytics teams can gain valuable insights into using an advanced machine learning system to automatically analyse large volumes of text data. This can help organisations save time and resources. You will also learn how to identify significant trends in near-real-time using the power of AI, so you can stay ahead of emerging problems and capitalise on new opportunities.
This session is especially relevant for organisations in the banking, finance, retail, and telecommunications sectors that deal with large amounts of textual data. By understanding how to leverage this advanced technology, attendees can optimise their data analysis processes and stay ahead of emerging trends in their respective fields. Additionally, you will have the opportunity to learn from successful implementations while gaining practical knowledge and insight.
In this webinar, we will explore an implemented advanced analytics system, which leverages the power of machine learning to effectively track and categorise large amounts of textual data in near-real time, such as emails, chats, and messages. We will show you how the system is capable of detecting less significant textual inputs by considering their semantic score, ensuring that only relevant information is focused on. All the analytical results, including emerging categorisations and associated trends, are aggregated in an intuitive dashboard, providing an immediate view of incoming traffic without any manual intervention.
We will also explore how this advanced analytics system can specifically improve the customer care experience by providing timely and accurate insights into customer needs and concerns. By automatically categorising and analysing large volumes of textual data, customer care teams can quickly identify the most popular requests in near-real-time and prioritise their efforts to address customer issues promptly, leading to higher customer satisfaction and loyalty.
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