Addressing the challenge of scattered customer feedback across platforms like LinkedIn, Twitter, Email, and more. The unstructured nature of Voice of Customer (VoC) data creates difficulties in processing and extracting meaningful insights. This project offers a solution by leveraging AI-powered snap-ins from DevRev to seamlessly aggregate VoC data. By incorporating unique sources, it aims to denoise, cluster, and generate actionable insights, providing organizations with a consolidated and organized view of customer feedback for informed decision-making.
We faced challenges in understanding the DevRev snap-ins architecture, gathering data from different places, and efficiently using snap-in CLI commands. To solve these issues, we used tools like the gplay scraper for app data and the Twitter API for social media data. We also learned how to use DevRev CLI commands effectively. Our goal was to create a service that takes in data from various sources and connects it with llm models to provide useful insights. This approach has helped us turn raw data into valuable information for better analysis.
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