The Amazon International Seller Growth (ISG) team runs the CSBA (Customer Service by Amazon) program that supports over 200,000 third-party Merchant Fulfilled Network (MFN) sellers. Amazon call centers facilitate hundreds of thousands of phone calls, chats, and emails going between the consumers and Amazon MFN sellers. The large volume of contacts creates a challenge for CSBA to extract key information from the transcripts that helps sellers promptly address customer needs and improve customer experience. Therefore, it’s critical to automatically discover insights from these transcripts, perform theme detection to analyze multiple customer conversations, and automatically present a set of themes that indicate the top reasons for customer contact, so that the customer problems are addressed in the right way and as soon as possible.
This post presents a solution that uses a workflow and AWS AI and machine learning (ML) services to provide actionable insights based on those transcripts. We use

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