#4 Success Story: Retail eCommerce & Customer Support
AI-Powered Process Automation for Customer Support & Onboarding
Goals
An eCommerce giant wanted to reduce manual effort in customer support and onboarding, shorten response times and process cycles across the customer lifecycle, improve customer experience while scaling customer and request volumes and establish a scalable, integrated system and process architecture. The goal of the project was to holistically automate core customer operations processes in eCommerce in order to significantly reduce manual effort in customer support and onboarding. At the same time, response times across the entire customer lifecycle were to be shortened while ensuring a consistent, high-quality customer experience, even as customer and request volumes continued to grow. A further objective was to establish a scalable, integrated process and system landscape capable of supporting sustainable growth as well as future automation and expansion initiatives.
By automating repetitive tasks and standard requests, teams are relieved from manual workloads and can focus on complex, value-adding customer interactions.
AI-driven classification and workflow orchestration enable faster handling of customer requests and smoother transitions between support and onboarding stages.
Consistent, AI-supported processes ensure high service quality and reliability even as customer demand and interaction volumes grow.
An iPaaS-based integration layer connects CRM, ERP, eCommerce, and support systems, creating a flexible foundation for future growth and automation initiatives.
Execution Strategy
Integrated iPaaS Architecture for End-to-End Customer Operations
We designed and implemented an iPaaS-based integration architecture to orchestrate customer data and workflows across CRM (Salesforce), ERP (SAP S/4HANA), eCommerce, and support systems. This created a unified, scalable backbone for customer operations and eliminated system silos across the customer lifecycle.
AI-Driven Automation of Support & Onboarding Processes
Targeted AI components were introduced to automate the classification, pre-qualification, and intelligent routing of customer support requests. In parallel, AI-supported onboarding workflows were implemented to guide customers and users through structured, context-aware information, FAQs, and process guidance, reducing manual intervention and increasing consistency.
End-to-End Workflow Orchestration & Monitoring
Customer-facing processes such as order-to-cash, service requests, and onboarding journeys were automated end-to-end. Workflow orchestration included monitoring, escalation logic, and KPI tracking to ensure transparency, reliability, and measurable performance across all customer operations processes.
Structured Delivery, Go-Live & Stabilization
The solution was delivered using a structured end-to-end delivery approach, including clear milestones, stakeholder alignment, and cross-functional coordination. A dedicated go-live and stabilization phase ensured smooth handover into operations, high user adoption, and sustainable performance from day one.
Outcomes
The project achieved remarkable success, marked by several key achievements:
Operational Efficiency & Team Enablement
AI-powered end-to-end automation significantly streamlined customer support and onboarding processes. Standard requests are now handled in a consistent and largely automated manner, relieving operational teams and enabling them to focus on more complex, value-added activities.
Faster Response Times & Consistent Customer Experience
Response times in customer support were substantially reduced. At the same time, automated pre-qualification and workflow orchestration ensure a consistent, high-quality customer experience across all relevant touchpoints.
Transparency & Scalable Customer Operations
Centralized monitoring and KPI tracking provided full visibility into the performance and quality of customer operations processes for the first time. The implemented integration and automation architecture now serves as a stable, scalable foundation for further AI-driven enhancements across the entire customer lifecycle.
Numbers
The AI-powered automation delivered a 30–40% increase in operational efficiency across customer support processes, accelerated customer response times by 27%, and resulted in a 35% improvement in key service and customer satisfaction metrics, including CSAT.
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