How A Global Consumer Products Company Improved Customer Satisfaction By 30% Using Customer Insight Application

By Author: Anil Janardhanan 
Total Articles: 22
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As more companies become customer-centric, the need for real-time customer feedback has become crucial. Real-time customer feedback lets companies analyze customer sentiments immediately, improve their products and user experience, and meet customer expectations. It helps companies keep their ear to the ground and make proactive changes that make customers happy.

Although companies understand the importance of customer feedback, they struggle to gain holistic insights. This happens when feedback is scattered across multiple platforms, including email, social media, and support tickets. They lack the insights to analyze and understand customer sentiments.

So, what can they do to address these challenges? Well, let’s learn from a recent example of a global consumer product company.

How Fragmented Customer Feedback Prevented the Company from Improving Its New Product?
The company wanted to know its customers' views on a recently launched product, identify strengths and weaknesses, and make improvements to meet customer expectations. However, those efforts were marred by the following shortcomings:

The ...
... company was slow to make product changes based on customer feedback, primarily due to delays in the feedback cycle.
Since the company received data from various sources, such as social media, surveys, and support tickets, the data was unstructured. This meant it had to spend considerable time standardizing the data to gain actionable insights.
The company had limited access to predictive analytics. This prevented it from forecasting customer trends and missed the opportunity to make product enhancements and stay ahead of the curve.
It used manual analytics processes to analyze customer sentiments. This was not only time-consuming but also prone to errors. The inaccuracies in the analysis prevented it from making the right decisions.
After many discussions, the company decided to build a customer insights application to understand what customers wanted.

How A Customer Insight Application Solved the Problem
A customer insight application is a tool that gathers and consolidates customer feedback from various sources, providing a holistic view to analyze and make data-driven decisions.

The company partnered with Gadgeon to build an application with the following features:

Configurable product category definition and selection: One of the application's core features was its ability to define product categories and attributes. It was customizable. So, the company could easily define new attributes for a product and add them to the application. The application could automatically identify the relevant attributes based on the selected product category. This saved the company time and effort in categorizing products and ensured easy product discoverability.
Data collection, cleansing, and categorization: The application eliminated the manual intervention involved in collecting, cleaning, and analyzing data. Its built-in review analysis engine gathered data from all diverse platforms, processed it by passing it through different levels, and cleansed and categorized it using advanced AI models. This enabled the company to maintain the accuracy and reliability of the data.
Multi-channel data aggregation: The company gathered and unified feedback from various sources, such as e-commerce platforms, public forums, social media, review sites, customer support logs, and surveys. This provided a comprehensive view, giving the company a complete perspective on what customers think and expect from its products.
AI-powered sentiment analytics: The application used Natural Language Processing (NLP) to determine positive, negative, and neutral customer sentiments from customer feedback. This allowed the company to understand the sentiments revolving around the product and make changes accordingly.
Predictive analytics: With easy access to standardized and accurate data, the company could now build a predictive model to forecast customer trends and identify potential product issues. This prepared the company to provide a positive customer experience proactively.
Dashboards and reports: Built on Superset, the application provided decision-makers with dynamic charts and reports. They could view the most popular products, the least liked attributes, product performance scores, and standout features, which enabled them to make informed decisions.
How A Customer Insight Application

Automated alerts and workflow integration: Gadgeon set up automated alerts that notified relevant departments whenever a critical issue occurred. This helped the teams take timely action and prevent any escalations or disruptions.
The application was deployed in three phases:

Phase 1 involved integrating data and developing the sentiment analysis module.
Phase 2 involved implementing dashboards and analytics features for customer analysis.
Phase 3 included rolling out predictive analytics and automated alert systems.
We used the following tech stack to build the application:

Frontend: React JS, Tailwind CSS, Superset for an intuitive and interactive user experience
Backend: Python (Django) and Node.js for data processing and API integrations.
Database: MySQL for structured data and NoSQL DB for unstructured customer feedback.
AI & Analytics: LLM models - ChatGPT, Mixtral, and Llama. TensorFlow for sentiment and predictive analysis.
Cloud Infrastructure: AWS Cloud, Amazon Route 53
Here’s a glimpse of how it works:

stack to build the application

Faster Response = Better Products, Happy Customers
After deploying the customer insight application, the company was able to filter and access feedback that helped them make strategic decisions. It helped the company:

Improve the response time by 45% by automating feedback categorization.
Increase customer satisfaction by 30% by resolving real-time issues and improving customer experience.
Enhance the product development process by incorporating customer suggestions for features.
Achieve ROI within six months, as it could strengthen customer loyalty by listening to customers and implementing their feedback.
The application has undoubtedly transformed the way the company gathers, analyzes, and responds to customer feedback. It has given the company the power to deliver superior products that align with customer expectations.

In fact, the company is so happy with the application's capabilities that it has already planned to expand them.

To begin with, the company plans to expand the application’s AI capabilities to capture and process both video and audio reviews.
Next, it wants to segment the market on a more granular level, such as by demographics, location, and customer behavior, for better customer analysis.
Finally, it plans to integrate the application with its CRM and marketing tools, allowing for seamless data exchange and improved analysis.
What We Learned While Developing The Application and Why It Should Matter To You?
While building the application, we learned a few crucial lessons:

A mix of structured and unstructured data can provide a more unfiltered and holistic view of customer sentiments. Hence, maintain data diversity.
Use AI to automate analysis. This will eliminate the bias that seeps in inadvertently during analysis and make data analysis more accurate. Automation will also help you make faster decisions.
Keep iterating and making product enhancements. That’s the only way to keep pace with the ever-evolving customer expectations.
If you want to enhance your customer experience and products and build a customer insights application, contact us.

We'll be happy to help you take your product and business to the next level.

Gadgeon is an end-to-end Technology solutions provider company which is reputed for its deep expertise in offshore IT outsourcing services with specialization in product engineering, IoT, and digital transformation. As a professional technology solutions provider, we have successfully enabled the digital journey of customers with critical digital services.