Who is the Company

A multinational apparel retailer.

The Challenge

The company has a large retail footprint with hundreds of physical stores and a dozen wildly popular e-commerce websites. They also made significant inroads into several online marketplaces across the globe, especially the APAC and EU markets.

The company faced a major challenge in ensuring a uniform look and feel among its various websites. The company’s websites undergo a constant stream of content changes to ensure they continue being the leaders in their segments.

This rapid pace of change brought a lot of unforced inconsistencies among the websites, which resulted in a less than seamless user experience. The company engaged in a tedious and near-impossible process of visually comparing every page of every website to keep on top of changes.

The problem with the time-consuming manual process was that it not only drained company resources, but often visual discrepancies between websites were missed, resulting in customer confusion, dissatisfaction, and lost sales.

In brief, the company was looking to:

  • Reduce time spent reviewing visual changes: They needed to reduce the time spent manually reviewing their many websites.
  • Catch visual discrepancies in a timely fashion: They wanted a testing solution to highlight visual discrepancies between websites shortly after deploying changes.
  • Increase the coverage of their many websites: They needed the quality monitoring process to cover all pages of all websites.
  • Expand visual comparisons: They needed to expand their visual comparisons to include a wide range of browsers and operating systems.

    The Solution

    Following meetings with company stakeholders, our Quality Engineering team decided on an automated visual regression testing solution that would compare current screenshots of the various company websites against baseline screenshots.

    Our engineers compared different visual testing tools on the market, like Percy (BrowserStack), Sauce Visual (SauceLabs), and wdio-image-comparison-service (WebdriverIO service). For each tool, our team created a series of proof-of-concept implementations customized to the company’s needs. This comparison enabled us to weigh each testing stack’s pros and cons and ultimately choose SauceLabs.

    We then crafted a set of visual tests leveraging Sauce Visual. The final solution facilitates regular rapid visual test execution and maintains an excellent set of baseline images.


    We configured Travis CI, a continuous integration tool, to trigger automated visual regression builds in a timely manner.

    Here are a few key takeaways from our solution:

    • Automated visual regression testing: The new solution performs an automated visual comparison of all screens. Quality engineers can validate and approve screenshots by the tool daily.
    • Reduces manual testing effort: The new framework completely automates visual testing, reducing heavy resource requirements and preventing discrepancies from going unnoticed.
    • Comprehensive analysis of visual changes: The new system captures pixel perfect visual data from all sites. It notes all discrepancies, even the most minute ones.
    • Near real-time discrepancy data allows timely response: Visual regressions are identified almost as soon as they are introduced. Daily execution and validations are scheduled so that the baseline is always up-to-date. This allows the company to respond proactively to any issues.

    Business Impact

    • Tighter control over branding: Because the company can now quickly verify that website changes maintain visual integrity, its branding is not impaired. This leads to improved customer acquisition and retention.
    • Reduced drain on resources: Company resources previously involved in the tedious manual visual review process are now free to engage in more profitable pursuits.
    • Precise reporting of visual discrepancies improves customer satisfaction: Because company stakeholders can now see precisely where the discrepancies appear, they can quickly respond, resulting in minimal disruption and confusion in the customer experience.

    Technologies Used

    WebdriverIO
    Travis CI
    Sauce Visual (screener.io)

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