How To Convert Raw Customer Feedback Into Actionable Product Insights Using an AI-Driven Customer Insight Platform

What do customers want?

This question has continued to remain unanswered, giving brands sleepless nights.

The lack of data on what customers want has limited brands’ capabilities to innovate and grow.

While many brands have begun using social listening tools to gain a deeper understanding of customer sentiments and drive innovation, they have yet to unlock their full potential. 

They have the right data, but lack the insights needed to make data-driven decisions.

This is exactly what happened with one of our clients, a leading global consumer brand. 

Large Data Volume, Limited Insights

The brand, known for its customer-centric approach and innovation, received a vast amount of customer feedback through digital channels like online reviews, social media, and discussion forums. 

While this spelled good news for the brand, there were limitations. 

First, the brand manually tracked feedback across different channels. This was not only time-consuming but also led to subjective interpretations that were inconsistent and unreliable.

Second, the teams lacked real-time visibility into the feedback. This prevented them from identifying what was working and what was not.

Since the client lacked real-time or reliable insights, they were unable to make informed decisions, such as product upgrades and feature prioritization.

They needed a centralized, intelligent customer insight platform that would allow them to:

• Ingest and centralize customer feedback from multiple platforms 
• Analyze customer sentiments, detect trends, and identify areas for improvement
• Share reports in a visual and actionable format with product, marketing, and customer experience teams for decision-making
• Make faster, data-driven decisions to drive product improvements and meet customer expectations.

The client decided to partner with Gadgeon to build an AI-powered Customer Insight Platform that enables teams to convert raw, unstructured data into actionable insights and plan future product strategies. 

How An AI-Powered Customer Insight Platform Helped The Client Make Data-Driven Decisions

Armed with deep expertise in AI/LLM integration and building scalable enterprise solutions, our team at Gadgeon built a cloud-native customer insights platform that captured customer feedback and transformed raw data into structured insights. Additionally, the team helped with everything, ranging from building data architecture to processing user analytics.

Some of the core functionalities of the platform included:

• Product enrollment to help the client upload products manually or in bulk, and automatically detect relevant attributes based on the category
• Attribute customization to define and refine custom products and track customer sentiments on a granular level
• Multi-source integration that allowed the client to connect Amazon, YouTube, and other platforms seamlessly and centralize product reviews, comments, and discussions in one place
• AI-powered review analysis that used LLMs like ChatGPT, Mixtral, and Llama to cleanse, classify, and analyze sentiments from text-based feedback
• Dynamic visual reporting built using Apache Superset to monitor trends, benchmark performance, and gain insights easily at a glance

Here’s a glimpse of how the dashboard looks:

To build this interactive Customer Insight Platform, we used:

• AWS Cloud and Elastic Beanstalk for container deployment and Route 53 for DNS routing
• ReactJS with Tailwind CSS for developing a seamless, responsive frontend and UI
• Apache Superset for building interactive dashboards
• AI models like ChatGPT, Mixtral, and Llama to extract sentiments from texts and understand the context
• MySQL for structured data and NoSQL for storing and querying unstructured feedback

Here’s what the architecture of the platform looks like:

How The Brand Cemented Its Reputation As Being Customer-Centric With The New Platform

While the client already had a reputation for being customer-centric, they further solidified it with the new customer insights platform.

Through continuous monitoring, the AI-driven customer insights platform allowed the client to gain real-time insights about customers’ sentiments around a product launch. Furthermore, it enabled the brand to identify top-performing products and features, as well as detect product issues emerging from repeated complaints. 

The real-time insights from customers also allowed the product and marketing teams to prioritize features and enhancements that matter the most to customers. 

However, the icing on the cake was the client’s ability to move from a reactive to a proactive approach. They could respond to customer feedback more quickly and make product improvements even before the issue escalated further. 

This approach enabled the client to accelerate the product development cycle and enhance brand reputation and customer satisfaction. From scattered reviews to centralized insights, Gadgeon enabled the client to build more innovative products faster and unlock the key to customer satisfaction.

Interested in building a similar application for your enterprise? Contact us for more information.