In the last few years, customer experience at every level has witnessed a paradigm shift. With digital technology taking over every industry and business function, customer interactions are now spread across multiple channels, devices, touchpoints, and interfaces. The scale of opportunities presented to companies as a result of this is simply immense. However, winning in this ‘digital first’ era will take more than just product differentiation; enterprises must look at improving customer experience on digital applications in a bid to improve loyalty, retention, and recall.
When considering customer experience, we are looking at both internal and external stakeholders – ranging from business users working with enterprise-grade technology to end-users who are offered market-facing products and services. In this context, quality assurance and customer satisfaction go hand-in-hand, extending beyond mere functional tests of a particular digital application, to non-functional parameters as well. These would include performance, compatibility, usability, security, and accessibility, not to mention smart UI and UX design.
So, how does one address all of these diverse facets across a singular testing and development pathway? Quality engineering for digital transformation initiatives could have the answer.
Aligning Quality Assurance to Customer Satisfaction Goals
Reaching pre-specified customer satisfaction targets will hinge on an enterprise’s ability to harness Business 4.0TM technology pillars– intelligent, agile, automated, and on the cloud. Next-gen quality engineering achieves this unique intersection between a futureproof transformation path and the need to constantly deliver functional and clutter-breaking digital applications. Here are its four key levers:
Analyzing user behavior to optimize customer experience quality - Analytics is now a must-have for any digital program, and with usage data volume rising exponentially, businesses need to apply an ‘intelligence layer’ to process all of this rapidly. We are seeing major investments in AI and intelligent algorithms to analyze end-user behavioral data (bounce rates, user inflow, or average time spent) interlinked with business goals (guests to subscribers or user visit to order conversion). This will help identify any roadblock to customer experience quality – for instance, a web page displaying high bounce rates could be symptomatic of underlying performance issues.
Leveraging agile to dynamically improve CX quality - Assessing CX quality for any digital application requires an agile execution model, capable of gauging CX maturity against changing market parameters (say, a browser’s market share in a location or performance of competitor applications). This will give enterprises a bird’s eye view of customer experiences and the elements which are primarily holding user attention. Simply put, an agile model will allow frequent assessment, capturing fluctuating customer satisfaction metrics and enabling timely digital application upgrades.
Automating the execution of CX overhaul - Given the rapid release of consumer/enterprise-grade devices and hardware, digital applications must also look at accelerated update cycles. The only way to ensure quality within ever-shortening timelines is to adopt machine-led quality engineering solutions, that apply a set of tools integrated into the execution ecosystem, automatically testing for various usage patterns. This will ensure that customer satisfaction levels are always maintained, regardless of device and individual release cycles.
Enabling ‘on-demand’ by moving ‘on-cloud’ - Keeping up with customer experience benchmarks for different digital ecosystems and staying a step ahead of competing applications, calls for massive investments in IT infrastructure. From new devices to browser versions and upgraded network conditions, enterprises are left spending heavily, and on a regular basis. Partnering with a technology provider, who could offer an end-to-end, cloud-hosted setup along with dynamic provisioning of additional infrastructure, will be the way forward.
Why Quality Engineering in Digital Transformation is Critical
We are now living in an omnichannel world where there is no static benchmark for customer experience quality or stable parameters for customer satisfaction. Research by Ovum suggests that customer experience improvement is the leading strategy that enterprises are employing to achieve digital transformation success. Yet, 80% of respondents are struggling with their CX initiatives, and the absence of in-house quality engineering experts is a major reason behind this.
There’s no denying it: seamless interactions and differentiated experiences can turn users (internal/external) into vocal advocates of a brand. That’s why taking advantage of the best available quality engineering expertise, working towards shared customer experience goals, can make a big difference. For example, an enterprise looking to test compatibility with a new device wouldn’t need to buy-in new infrastructure or tool licenses. A quality engineering partner would provide a cloud-based automation script (speeding up compatibility tests) as well as several browser-OS combinations as needed. The enterprise gains enormous savings and isn’t bogged down by license procurement or infrastructure setup that could possibly be rendered useless in future device lifecycles
Intelligence, agile, automation, and cloud together can ensure superior customer experience via proactive quality engineering.