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Over the last couple of years, AI and ML have become essential aspects of delivering great customer experiences. From suggesting the next show to stream, to chatbots tackling customer queries, rolling out seamless shopping experiences or enabling quick payments through a Unified Payments Interface – AI is quietly shaping and increasing expectations across multiple digital interactions. When done right, AI enabled digital experiences can increase customer satisfaction, but when something goes wrong, it can cause significant customer frustration.
The creation of a problem-free, engaging user experience relies heavily on the ease of use of a platform, as well as its ability to handle high traffic volumes to deliver a consistent user experience (UX). However, the New Relic 2024 Observability Forecast found that 65% of Indian businesses experienced high-business-impact outages at least once a week, and 77% reported that downtime cost them $US1 million or more per hour. An E-commerce website with a complicated checkout process, or a streaming platform that constantly crashes can create problems. Such experiences are far from positive; and could potentially drive customers to your competitors, which is where intelligent observability – strengthened by AI – becomes so valuable.
Improving on User Experience
When it comes to UX, businesses must ensure they collect the necessary data to make informed decisions around what to improve and when. It’s likely that businesses will collect data from different sources, such as user reviews, usability tests, or through Google Analytics. Such data-driven insights monitor and help improve product experiences, and provide the information needed by developer teams to identify what needs to change, and allow businesses to focus on what matters most.
When optimising UX, real user monitoring becomes essential. It records and analyses digital customer interactions with an application, such as how long a web page takes to load or page errors. Real user monitoring enables businesses to better understand how customers interact with websites or mobile apps, and when coupled with intelligent observability, businesses can gain valuable insights into real-world user experiences. Once in place, teams can focus on areas to improve, and ensure they have the data necessary to measure changes over time to track improvements.
The ability to deliver a good digital user experience also requires deep visibility into applications across different layers of the tech stack. Application performance monitoring (APM) is crucial, but is only part of what’s needed. Intelligent observability that’s strengthened by AI takes things to the next level. It ensures that all aspects are monitored, including the front end, because these errors can be difficult to detect without monitoring, especially aspects such as browser compatibility issues and JavaScript errors. With these errors impacting the user experience, intelligent observability platforms can provide holistic user-centric performance metrics to help teams understand how a customer experiences an application.
Additionally, it is essential to prevent downtime by surfacing unforeseen insights, suggesting application and infrastructure optimisations, improving performance and reliability, and learning from incidents to predict failures before they take place. It improves productivity, system resilience, and greatly enhances user experiences.
Improved Productivity and Business Outcomes
Regardless of the industry – whether it’s streaming, E-commerce, healthcare or technology – observability strengthened by AI has become the essential differentiator. It enables IT teams to provide performant, reliable services and proactively resolve or prevent issues before they impact users. The Observability Forecast reveals that engineering teams in India devote 30% of their time to addressing interruptions—the equivalent of 12 hours each working week. AI-strengthened observability can dramatically change that, as automation ensures less time is spent on maintenance, and instead focuses on creating innovative experiences. Additionally, business leaders can make informed, timely decisions about new features to improve the customer experience.
Proactive Detection of Issues
Intelligent observability is great at finding patterns in what could otherwise appear to be unrelated data sets. By leveraging AI, it can collect various information from apps, historical performance, and outcomes from incident reports and chat logs, to identify potential threats to system reliability, which can often go unnoticed. Take the example of the highly-anticipated match between Real Madrid and FC Barcelona in October. Millions of fans logged in from India and around the world to watch it live, but when one streaming platform suffered a technical issue, access was blocked, and disgruntled fans took to social media to vent. With AI-strengthened observability, such issues can be anticipated well in advance and addressed to deliver a better experience for users.
Intelligent observability allows businesses to effectively monitor, analyse, and act on vast amounts of data, enhancing operations and improving customer experiences. By closely aligning observability metrics with business objectives, software engineers and business leaders can work together to drive success across their organisations. Observability can enable businesses to create a consistent experience, resulting in more satisfied customers.