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Enabling the Future of Mobile Quality Excellence

Enabling the Future of Mobile Quality Excellence

There is no question that mobile devices and connectivity continue to drive digital transformation in Asia Pacific (APAC), as smartphone adoption rates are expected to soar to 91% by 2030. The sheer volume of apps — over seven million available across iOS and Android platforms, combined with fierce competition — means seamless mobile app experiences are now crucial for delivering high-quality customer journeys.

The problem is that users frequently encounter challenges such as slow loading times, unresponsive interfaces, and inconsistent functionality. These issues frustrate customers and undermine the overall user experience, eroding trust in the organization’s reliability. The repercussions of poor app performance are stark: businesses risk significant revenue losses and even reputational damage. It is estimated that Singapore businesses stand to lose up to SGD3.24M in revenue per year due to poor mobile app quality.

As mobile interactions increasingly become a preferred touchpoint for customers, integrating robust, AI-driven mobile testing strategies into development workflows is essential for businesses looking to deliver consistent app quality, exceptional user experiences, and better bottom lines.

Prioritizing a user-centric approach

Most IT professionals working on mobile app development and delivery recognize the importance of quality, but many simply lack the resources and support to invest in it. Developers face many challenges in testing mobile apps effectively due to increased pressure in shortening time-to-market, a shortage of skilled resources for manual testing, complex IT environments requiring seamless integration, and rapidly changing business requirements. This often results in poor user experiences and lower end-user retention, hurting bottom lines.

To avoid this, businesses should adopt a user-centric approach to mobile app design and resource allocation. More than just soliciting user feedback, this approach requires a profound understanding of user behaviors and preferences to create apps that are not only functional but also engaging and mobile-accessible. Businesses can align their products with customer needs and expectations by integrating design thinking, ongoing user testing, and iterative development practices. This ensures that applications are intuitive, responsive and deliver a satisfying experience — all of which is critical for driving user engagement and retention.

Manual testing is far from sufficient. Adequate resources must be invested in necessary tools or risk falling behind. In Singapore, nearly a third (31%) of senior IT professionals and app developers expect their organizations to invest upwards of SGD1.3M in mobile app quality and testing.

Embracing AI and automation is imperative

As businesses strive to meet these high standards of mobile app quality and user satisfaction, implementing AI and automation in testing presents a powerful solution.

According to IDC, the top 1,000 firms in Asia are expected to allocate over 50% of their core IT spending on artificial intelligence (AI) by 2025. More than a quarter (27%) of Singaporean businesses already use AI as part of their mobile app testing strategy, and another 70% plan to incorporate it into their development workflows.

AI-powered test automation benefits the business and IT teams in many ways, from increasing productivity, saving costs, and reducing the number of software defects. Leveraging intelligent user experience insights and performance analytics, developers can quickly spot failures and fix the issues promptly before launching the mobile app.

Furthermore, integrating automation into testing can enable better compatibility across devices. Automated mobile tests would allow developers to test an app on various devices and operating systems concurrently, reducing the time and effort required by manual testing. This ensures a faster delivery of flawless and smooth mobile experiences no matter which device the application is installed.

With enhanced end-user experience, app users are more likely to engage positively and productively, which could ultimately mean businesses can drive up sales and enjoy higher revenue.

Organizations that embrace AI and automation are better placed to modernize outdated application infrastructure and supercharge their testing capabilities to drive quality at the speed of innovation.

Bridging the skills gap is essential to meeting mobile app quality standards

The AI knowledge gap in the Asia Pacific is hindering widespread adoption as organizations struggle to understand how to integrate AI into their existing development workflows effectively.

To fully realize AI’s potential, businesses must prioritize employee upskilling. This involves implementing training and development programs that build expertise within IT teams, empowering individuals across various roles — from developers to project managers — to contribute effectively while reducing errors and enhancing productivity. In addition, incorporating codeless AI-driven tools can further bridge the gap, making advanced testing solutions accessible to a broader range of team members, regardless of their technical expertise. By empowering teams with the requisite skills and user-friendly tools, businesses can harness the technology’s transformative potential and drive innovation in mobile testing.

Mobile application excellence is intrinsically tied to an organization’s mobile testing strategy, with AI and automation now featuring as critical elements of success. While the AI-driven development and testing market is still maturing, the current landscape presents a unique opportunity for those who embrace these technologies. They will benefit across all key performance indicators, including higher productivity and better app quality. More importantly, this will increase sales, strengthen market competitiveness, and enhance user retention and customer loyalty.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/Deagreez

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