When it comes to delivering exceptional app user experiences, fintech companies like our client can't afford to ignore customer feedback. With millions of users relying on their digital banking services across Europe, they required a reliable way to analyze and act upon the vast amounts of feedback pouring in from various channels – app reviews, support tickets, and in-app surveys. To rise to this challenge, we collaborated with the fintech startup to develop an AI-powered customer feedback analysis tool that would revolutionize their product development process.
To tackle this project, our team worked closely with the client to integrate artificial intelligence (AI) into their existing web platform. Our goal was to create a comprehensive solution that could analyze customer feedback from multiple sources, detect sentiment, and provide actionable insights for both product and support teams.
The client's web platform already had a solid foundation, but they needed our expertise in developing AI-powered sentiment analysis features to unlock the full potential of their user feedback. We assembled a project team consisting of a project manager, AI engineer, backend engineer, frontend engineer, and QA engineer to tackle this ambitious project.
Our first step was to define the key features we would focus on. These included developing AI-powered sentiment analysis features, integrating data from various sources, creating a unified data pipeline, building dashboards for real-time insights, and ensuring seamless testing and iteration.
Throughout the development process, we faced several challenges that required creative solutions. One of the most significant hurdles was dealing with unstructured data – customer feedback that was sometimes vague, inconsistent, and filled with typos, sarcasm, or irrelevant content. To overcome this issue, we employed natural language processing (NLP) preprocessing techniques to filter out low-value feedback using heuristics like minimum word count and presence of relevant keywords.
Another challenge we encountered was integrating our AI-powered features with the client's legacy systems. Our solution involved decoupling AI logic from the main app by introducing microservices and a REST proxy service, allowing for smoother integration.
The end result was impressive: our AI-powered customer feedback analysis tool accurately classified 80% of feedback with high precision, enabling the client to identify critical issues three times faster than before. Furthermore, we helped reduce ticket response time for product-related issues by 22%.
By leveraging AI in customer feedback analysis, fintech companies can unlock valuable insights that drive better app user experiences and improve overall product development.