Codetru, a leading software development and consulting company, was approached by a major eCommerce client to create a comprehensive customer complaints portal. This portal was required to incorporate a dedicated ticketing platform, provide an intuitive customer journey, offer real-time order status updates, and predict delivery timings for end users. Our goal was to improve the customer experience, streamline complaint resolution, and enhance operational efficiency.


Problem Statement

The client's existing system was disjointed and did not provide a seamless, integrated solution for managing customer complaints. The absence of a unified portal resulted in delayed complaint resolution, a lack of transparency in the order process, and an overall subpar customer experience. The client needed a portal that could not only address these issues but also predict delivery times, a feature that would significantly improve customer satisfaction.



Data Integration

The project required seamless integration of data from various sources, such as sales data, research data, and manufacturing data, to create a unified view of the client's operations.


The solution needed to accommodate the client's growing data volume and future expansion plans, ensuring it remained scalable and efficient.

Data Quality and Standardization

Ensuring data quality and standardization was crucial to derive accurate and meaningful insights. The challenge was to address inconsistencies and errors in the source data during the ETL process.

Analytics and Visualization

Developing advanced analytics models and intuitive visualizations to uncover hidden patterns and trends from the integrated data posed a significant challenge.


Key Results

Codetru successfully developed and implemented a customer complaints portal that addressed all of the client's needs. Here are the key results:

Seamless integration

The portal was fully integrated with the client's existing systems, ensuring smooth data flow and operations.

Enhanced security

Codetru implemented stringent data security measures to protect sensitive customer information.

User-friendly interface

The portal featured an intuitive user interface that improved the customer journey and experience.

Accurate delivery predictions

By leveraging machine learning algorithms and historical data, the portal was able to predict delivery times with high accuracy.



The implementation of the customer complaints portal significantly improved the client's operations and customer satisfaction levels. The streamlined complaint resolution process led to a 40% decrease in complaint resolution time. The transparency offered by real-time order tracking and the delivery prediction feature resulted in a 23% increase in customer satisfaction ratings.

Moreover, the client reported a 37% reduction in operational costs related to handling and resolving customer complaints due to the automation of various processes. The overall impact of the portal implementation was a more efficient, customer-centric approach to handling and resolving complaints.

Technology Stack

The customer complaints portal was built using a robust technology stack to ensure reliability, security, and scalability. The technologies used included:

Backend : Python and Django were used for backend development due to their versatility and the extensive library support they offer.

Frontend : React was chosen for frontend development because of its efficiency and user-friendly interface capabilities.

Database : PostgreSQL was used as the database solution for its reliability and robustness.

Machine Learning : Python's Scikit-Learn and TensorFlow libraries were utilized for the delivery prediction feature.

Security : Standard security practices were enforced, including data encryption, secure API integrations, and strict access controls.

Codetru's expertise in ETL, analytics, and visualization technologies enabled the successful execution of this project, providing the pharmaceutical client with a powerful solution to unlock the value hidden within their data and drive strategic business decisions.