PHARMA MAJOR USES NETDIAGNOSTICS ENTERPRISE TO BRING STABILITY & SCALABILITY TO BUSINESS CRITICAL APPLICATIONS
THE NETVISION ADVANTAGE FOR RETAIL
Fortune 500 Retailer leverages Cavisson NetVision to gain complete visibility across its complex, distributed application ecosystem. By correlating real user experience, application performance, integration points, and log/database insights, retailers proactively detect issues impacting customer journeys. This holistic monitoring approach has enabled faster RCA, improved system reliability, and a significant reduction in cart abandonment, ultimately driving higher customer satisfaction and profitability.
CHALLENGE
A Fortune 500 retailer was experiencing massive revenue losses during peak shopping seasons but couldn’t identify why customers were abandoning their shopping carts at critical conversion points. Traditional monitoring tools provided infrastructure metrics but failed to reveal the actual user experience issues, causing customers to leave without completing purchases.
Key Pain Points:
➣ Unable to identify which specific products or pages were causing conversion problems
➣ Inability to correlate technical performance with actual user behavior and cart abandonment
➣ No visibility into real user sessions to understand where customers were dropping off
➣ Lack of granular insights into page-level performance issues affecting the shopping journey
Where other legacy products failed to capture issue, NetVision helped us identify critical issues in production, much ahead of our peak sales day, resulting in eliminating severe revenue losses.
– Director of Performance Engineering, Fortune 500 Retailer
SOLUTION: COMPREHENSIVE DIGITAL EXPERIENCE MONITORING
Cavisson NetVision provided end-to-end Digital Experience Monitoring that went beyond traditional APM to capture real user interactions and correlate them with underlying technical performance issues.
Easy Implementation & Immediate Visibility
➣ Simple Tag Deployment: NetVision’s lightweight JavaScript tag was implemented across the retailer’s web application with minimal effort, instantly providing visibility into real user sessions.
➣ Real User Monitoring (RUM): Captured actual user interactions, page load times, and conversion funnel performance from real customers.
Advanced Performance Analytics
➣ HTTP Request/Response Monitoring: Captured complete HTTP data, including request/response headers for each page interaction, enabling precise troubleshooting.
➣ Page-Level Resource Analysis: Monitored which resources (images, scripts, stylesheets) were taking maximum time to load on each page
➣ Domain Response Time Tracking: Identified which third-party domains and services were causing delays in the customer journey.
Machine Learning-Powered Insights
➣ Predictive Alerts: ML-assisted alerts predicted performance degradation before it impacted customers
➣ Anomaly Detection: Automatically identified unusual patterns in user behavior and performance metrics.
➣ Performance Forecasting: Anticipated traffic spikes and potential bottlenecks during peak shopping periods.
Custom Event Tracking & Session Replay
➣ Cart Abandonment Events: Created custom events specifically to capture user sessions where customers couldn’t add items to the cart or complete checkout
➣ Session Replay Technology: Provided video-like playback of actual user sessions, revealing exactly what customers experienced during failed transactions.
➣ User Journey Mapping: Tracked complete customer paths from landing page to checkout, identifying exact drop-off points.
Root Cause Analysis & Correlation
➣ Error Context Correlation: Automatically correlated user experience issues with underlying technical problems
➣ Code-Level Visibility: Provided package, class, and method-level insights when performance issues occurred.
➣ Log Correlation: Connected user experience problems with specific application logs and database queries in real-time.
COMPREHENSIVE BENEFITS FULFILLED
Immediate Revenue Recovery
➣ Eliminated Cart Abandonment: Fixed critical issues causing customers to abandon purchases
➣ Increased Conversion Rates: Improved checkout completion rates across all devices and browsers
➣ Revenue Protection: Prevented millions in potential lost sales during peak shopping periods
Enhanced User Experience Insights
➣ Device/Location/Browser Analysis: Comprehensive understanding of performance across different user segments
➣ User Behavior Analytics: Heat maps, click maps, scroll maps, and attention maps revealed user engagement patterns
➣ Conversion Funnel Optimization: Identified and resolved bottlenecks at each stage of the customer journey
Operational Excellence
➣ Quick Root Cause Analysis: Reduced issue resolution time from days to minutes
➣ Proactive Issue Detection: Identified problems before they impacted customers
➣ Real-Time Alerting: Immediate notifications for performance degradation and user experience issues
Advanced Analytics & Reporting
➣ Business Transaction Monitoring: Top transactions, flow paths, and conversion metrics
➣ Error Analysis: Comprehensive exception and error tracking with business impact correlation
➣ Performance Trending: Historical analysis and capacity planning insights
KEY DISCOVERIES THROUGH DIGITAL EXPERIENCE MONITORING
CRITICAL USER EXPERIENCE ISSUES IDENTIFIED:
False “Out of Stock” Messages
➣ Session replay revealed multiple products showing incorrect “Out of Stock” status to users attempting to add items to cart.
➣ Real user monitoring showed high abandonment rates, specifically on these product pages.
➣ Root cause traced to underlying inventory service issues within minutes.
Mobile Performance Problems
➣ Mobile website monitoring detected an increase in 404 errors on product listing pages.
➣ Device-specific analysis revealed mobile users experiencing significantly slower load times.
➣ Touch interaction problems identified through user behavior analysis
Frontend JavaScript Errors
➣ JS Error Events are impacting end-user sessions and causing silent failures during checkout.
➣ Error correlation showed specific browser/device combinations were most affected.
➣ Real user data revealed errors occurring at critical conversion points.