To enhance end‑to‑end user journeys across e‑commerce channels by leveraging AI‑powered observability for improved performance, reliability, and real‑time insights.
A leading Indian bank sought to optimize the merchant and user journeys across a popular e-tailer’s channels. This included enhancing the credit card onboarding journey for individual customers and streamlining the onboarding process success rate for merchants. In addition, the banking leader wanted to improve the transaction processing reliability of its digital ecosystem to drive uninterrupted and seamless end-user experiences. Anabot, QualityKiosk’s AIOps-driven analytics solution, combined with our ecient user journey mapping tools, enabled the bank to gain end-to-end visibility into customer and merchant journeys. This enabled them to gain actionable insights for streamlining onboarding and transaction success on the e-commerce platform.
To overcome these challenges, we implemented the following strategies:
• User Journey Mapping: QualityKiosk deployed proprietary and external data assimilation tools to map user journeys across profiles and transaction channels in real time. We integrated the existing APM tools in the solution stream to unify data, create a holistic view of customers, and accelerate Mean Time to Identify (MTTI). The deployment of end-to-end monitoring across user journeys enabled the bank to understand user preferences, develop solutions, and build dashboards, all within 90 days
• AI-Driven CX Analytics: We leveraged Anabot’s AI-driven analytics to identify and resolve technical issues, usability issues, and transaction processing challenges. Powered with intuitive data visualization, Anabot simplified the understanding of user journeys and transactions, enabling teams to identify anomalies, information routes, and transaction success rates, accelerating root cause analysis and issue resolution.
• Unified Data and Monitoring: QualityKiosk’s solution unified customer journey monitoring, eliminating the dependency on third-party tools for transaction failure. This significantly improved the investigation speed (MTTI), reducing average mean-time-to-repair (MTTR) from hours to minutes.
Proactively enhance customer experiences
Fast-track defect management
Eliminate recurring defects
Gain end-to-end visibility into user journey
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