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QualityKioskʼs AI-Powered Monitoring Helps E-commerce Giant Optimize Payments Processing

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Industry & Segment

Retail & ecommerce

Objective

To deliver an AI-powered synthetic monitoring solution that provides end-to-end visibility into critical payment journeys. It aims to proactively detect performance bottlenecks and enhance transaction reliability across web and mobile channels. Ultimately, the goal is to ensure seamless customer experiences and reduce business impact from payment failures.

Platform

Qlenium

Client Overview

One of the leading Indian e-commerce players, managing over 250,000 transactions every week, partnered with us to optimize its payment processing across its website and mobile channels. The client wanted to proactively failproof its payment performance to enhance customer experience and streamline user journeys. With proactive and end-to-end payment journey monitoring, QualityKiosk enabled the e-commerce giant to optimize performance for frictionless and scalable buying journeys. The client is a leading Indian e-commerce platform, backed by a major conglomerate. It serves millions of customers nationwide and specializes in curated fashion, footwear, accessories, beauty, and luxury products. The e-commerce platform operates through web and mobile applications, delivering a seamless and authentic online shopping experience.

Business Objectives

The customer needed end-to-end visibility into payment journeys across gateways and channels through a centralized system to:

  • Gain an integrated view of payment journeys across gateways, channels, web, mobile, and APIs.
  • Identify and resolve transaction bottlenecks to prevent failures and performance degradation.
  • Improve transaction performance to speed up successful checkouts and reduce friction.
  • Enhance customer experience by minimizing disruptions and cart abandonment.
  • Reduce cart abandonment rates through more reliable payment flows.
  • Eliminate monitoring silos by centralizing visibility and reporting.

QK Platforms Used

Qlenium

Our proprietary synthetic monitoring solution, built on Selenium and Playwright, enabled high-precision automated monitoring across web applications, Mobile, APIs, and digital services. Available with cloud and hybrid deployment options, the solution uses bots to orchestrate synthetic tests every 15 minutes. To streamline monitoring further, Qlenium enables auto-verification of incidents to eliminate false positives before escalating incidents.

AIBuddy

Designed to overcome the limitations of traditional testing automation, AIBuddy enables the automated execution of end-to-end synthetic monitoring scripts across security-restricted and Flutter-based mobile and exe-based applications. It does so by harnessing its non-DOM-dependent automation, AI-powered cross-verification, and human-in-the-loop validation.

AI-driven HAR Analyzer

QK's in-house innovation, the AI-driven HAR Analyzer, provides our internal teams with intelligent insights to accelerate diagnostics, enhance optimization, and drive competitive benchmarking for web applications. By automating the analysis of HAR data, it delivers consistent, scalable, and rapid insights, enabling faster, more accurate, and actionable recommendations for clients.

Discover how proactive monitoring can unlock seamless, high‑performing customer journeys. Get in touch with us today.

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Solution Implementation: AI-Powered Synthetic Monitoring

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Phase 1: Collaborative Requirement Gathering

  • QK collaborated with the client to understand critical payment flows across its web and mobile applications. Navigation flows and escalation matrices were meticulously documented to ensure complete alignment with client objectives.

 

Phase 2: Test Data Preparation & Script Automation

  • We created a centralized repository for managing test data assets and built automation scripts using Qlenium and AIBuddy. Accelerating the setup with reusable scripts, we automated synthetic test execution to simulate end-to-end payment flows across its web and mobile applications on diverse mobile and desktop device profiles. The monitoring solution was designed to adapt to different times of the day with pre-configured performance thresholds to minimize false positives.

 

Phase 3: Deployment

  • Automated Test Execution: We deployed bots to run synthetic tests every 15 minutes to monitor payment journeys across devices and channels around the clock. The bots monitor the availability and performance of payment journeys, flagging performance degradation through real-time SMS and email alerts. Additionally, the bots capture the network log analytics to gain insights into performance bottlenecks.
  • Intelligent Escalation: The monitoring solution enabled an intelligent escalation mechanism that reduced false
    positives with AI-powered cross-verification of incidents before they were reported to a monitoring engineer for review. The AI-human synergy ensures that only legitimate incidents are reported to level 1 stakeholders in the escalation matrix.
  • Comprehensive Reporting and Analysis: The incident reports captured error descriptions, screenshots, HAR files, error logs, and failure videos. Our AI-driven HAR analyzer enriched our reporting, providing in-depth insights into HAR data for accelerated root cause analysis and incident resolution. We also set up a bot to deliver daily and monthly exceptions and performance reports outlining the trends, issues, competitor benchmarking, and improvement recommendations.

Validation Strategy

Automated Coverage Analysis
A proprietary Validation & Coverage Analysis Module assessed the AI‑generated test cases by calculating overall requirement‑to‑test coverage, identification of missing or under‑represented scenarios, and percentage‑based coverage metrics. This ensured that gaps were detected early, driving consistency and completeness across all generated test artifacts.
SME Review & Enhancement
Subject Matter Experts performed a targeted review, not full manual authoring, to validate accuracy and business relevance. Their role included reviewing AI‑recommended scenarios, adding any high‑risk or edge‑case scenarios flagged through the coverage module and ensuring regulatory and domain‑specific completeness. SME intervention was optional and value‑driven, accelerating the validation cycle.
Structural and Standards Compliance Check
The platform ensured that each generated test case adhered to standardized structures, including test summary, description, expected results and test type. This reduced variability caused by human authors and ensured uniformity across teams.
Performance Testing Strategy
Once validated, test artifacts were exported into the client’s Test Management System for workflow alignment, traceability verification and compatibility with Agile/DevOps pipelines

Technical Results

250,000+ weekly

Transactions monitored

Every 15 minutes

Synthetic test frequency

96 tests/day

Synthetic tests per day (per flow)

24×7 (24 hours/day)

Monitoring coverage

Our Impact

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Gained End-to-end payment visibility: Deep contextual insights into transaction performance, failure, and success rates across devices and channels.

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Improved customer experience: 24×7 monitoring enabled proactive resolution of incidents and performance bottlenecks before they impact customer journeys.

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Reduced MTTR: Accelerated MTTR cycles by replacing reactive troubleshooting with proactive incident alerts and client-side analytics to assist quick RCA and faster resolution.

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Automated release monitoring: Provided early insights into release impact, enabling proactive identification of performance bottlenecks.

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Optimized resource utilization: Combining insightful reporting, in-depth performance analysis, and intelligent escalation, the client optimized resource utilization for maximized performance.    

RET-DIEX-2088

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