Case Study: Leading Global e-Tailer achieves automated global mobile app performance testing, eliminating manual labor and improving accuracy with Appvance.ai

Global e-tailer uses AIQ’s machine-vision to performance-test their mobile app

Leading Global e-Tailer needed to improve and scale performance-testing of its iOS and Android consumer apps across North America, Europe and Asia to stay competitive. The company faced a manual, stopwatch-based visual testing process that was slow, inaccurate and hard to run at scale—so it turned to Appvance.ai and its AI-powered machine-vision to automate UI-level performance testing.

Appvance.ai implemented automated machine-vision tests that recognize screen elements and time visual events (e.g., product images appearing) across 500-run test sets, producing bell curves and a monthly leadership dashboard. The solution delivered measurable impact: 100% reduction in manual labor for visual performance testing, a 97% improvement in accuracy and statistical significance, a 27× increase in apps/locales tested, near-zero ongoing labor, continuous global testing and actionable competitive insights.