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Case study

Logistics

Optimizing Performance & Real-Time Tracking for a Scalable Logistics Platform

Client type
Logistics & Supply Chain Management Company
Duration
1 Years
Team size
1 QA Lead + 3 QA Engineers + 1 Automation Engineer

Overview

Optimize your logistics systems, streamlined and timely deliveries.

Client overview

About client

The client is a logistics and supply chain company providing shipment tracking, fleet management, and delivery optimization services. Their platform is used by businesses to manage real-time deliveries and logistics operations efficiently.

Platform

Web Application (Angular + Node.js), Mobile Responsive Web

Users

10,000+ daily shipments tracked

Problem statement

The client faced challenges in real-time tracking accuracy, delayed updates, and system performance issues during high shipment volumes. These issues impacted operational efficiency and customer satisfaction.

Challenges

  • Inaccurate real-time shipment tracking
  • Performance issues during peak delivery hours
  • Complex route and fleet management workflows
  • Frequent data synchronization delays
  • Lack of automation in regression testing
  • Cross-device and browser compatibility issues

Our solution (testing approach)

  • End-to-end testing of shipment lifecycle
  • Validation of real-time tracking updates
  • Automation of critical workflows (tracking, updates)
  • API testing for data synchronization
  • Performance testing for peak shipment loads
  • Cross-browser and responsive testing

Tools & technologies

  • Selenium WebDriver (Automation Testing)
  • Postman (API Testing)
  • JMeter (Performance Testing)
  • JIRA (Bug Tracking)
  • BrowserStack (Cross-browser testing)
  • Jenkins (CI/CD Integration)

Test strategy & execution

A structured and performance-driven testing approach was followed:

  • Requirement analysis with logistics workflows
  • Test case design for shipment and tracking modules
  • Smoke and sanity testing for each release
  • Regression testing for system stability
  • Automation of repetitive and critical scenarios
  • Load testing to simulate peak shipment traffic

Key features tested

  • Shipment booking and order creation
  • Real-time tracking and status updates
  • Route optimization and fleet management
  • Notifications and delivery alerts
  • Dashboard analytics and reporting
  • Mobile responsiveness and usability

Results & metrics

  • Improved tracking accuracy by 70%
  • Reduced system downtime by 60%
  • Enhanced performance during peak loads by 80%
  • Achieved 85% automation coverage for critical modules
  • Improved operational efficiency and customer satisfaction

Process

  1. 1

    Requirement Analysis

    Understanding logistics workflows and system requirements

  2. 2

    Test Planning

    Defining QA strategy and scope

  3. 3

    Test Case Design

    Creating detailed test scenarios for shipment lifecycle

  4. 4

    Automation Setup

    Implementing automation for key workflows

  5. 5

    Test Execution

    Performing functional and API testing

  6. 6

    Bug Reporting

    Tracking defects and validating fixes

  7. 7

    Performance Testing

    Simulating peak shipment volumes

  8. 8

    Release Validation

    Final QA before production deployment

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