Overview

A leading global document management software provider needed an efficient way to capture UI screenshots for its mobile application across multiple languages. With support for 21 languages, the manual process of capturing localized UI screenshots was time-consuming, error-prone, and resource-intensive. The company sought an automation solution to eliminate manual effort, improve accuracy, and streamline its localization workflow.

Challenge

The mobile application had a dynamic user interface (UI) that required localized screenshots for all 21 supported languages. The traditional manual approach involved:

  • Navigating through the application and capturing screenshots in each language separately.
  • If 10 UI elements required screenshots, this amounted to 210 screenshots per device.
  • The process was repetitive and labor-intensive, consuming substantial time and manpower.

This inefficiency impacted productivity, delayed releases, and introduced the risk of human errors and inconsistencies in the screenshots. The company needed an automated approach to address these challenges and enhance localization efficiency.

Objective

The company aimed to automate the multilingual screenshot capturing process by:

  • Capturing screenshots in one primary language (English).
  • Automatically replicating the process for all other supported languages.
  • Running the process across multiple mobile devices in parallel to accelerate execution.
  • Ensuring accuracy, consistency, and quality in all captured screenshots.

Solution

The company partnered with Pcloudy to develop an advanced automation-driven solution for screenshot capturing. This solution leveraged test automation frameworks and cloud-based parallel execution to completely eliminate manual intervention.

Implementation Steps:

  • Script Development: A robust automation script was developed to navigate through the application, locate specific UI elements, and capture screenshots in English.
  • Multilingual Execution: The script was configured to automatically switch application language settings and execute the same process in all supported languages (e.g., French, German, Spanish, Italian, Arabic, Russian, Korean, etc.).
  • Parallel Execution: The process was further optimized by running tests on multiple mobile devices simultaneously using Pcloudy’s cloud-based testing infrastructure. This drastically reduced processing time and enhanced overall efficiency.
  • Automated Screenshot Validation: The solution ensured that the screenshots captured across languages were aligned, consistent, and met quality benchmarks, eliminating errors introduced by manual efforts.

Results & Benefits

By implementing this automation-driven solution, the company achieved significant improvements in its localization and testing processes:

  • 80% Reduction in Time Spent – The automation process drastically reduced the time required to capture multilingual screenshots, cutting down weeks of manual effort into hours.
  • Elimination of Manual Effort – QA teams no longer had to manually navigate and capture screenshots for each language, freeing them up for higher-value tasks.
  • 100% Accuracy & Consistency – The automated process ensured pixel-perfect screenshot capturing across all languages, removing human errors and inconsistencies.
  • Scalability & Faster Releases – The ability to execute tests in parallel on multiple devices allowed the company to scale its localization process effortlessly and release localized UI updates faster.

Impact

This solution revolutionized the company’s localization and UI validation workflows, making it:

  • More scalable – The automation framework can be easily extended to support new languages in the future.
  • More efficient – Resources are now focused on enhancing product quality rather than repetitive tasks.
  • More accurate – The standardized automation ensures every screenshot meets quality expectations.

With this automated screenshot capturing solution, the company now delivers high-quality localized UI experiences with significantly reduced effort and faster turnaround times. This approach has set a new benchmark in efficiency, accuracy, and scalability for multilingual application testing.