A fast-growing e-commerce brand was struggling with rising inbound support volume, primarily driven by repeat, low-complexity requests, resulting in excessive manual handling and misallocated team effort. Alice and her team audited support workflows and customer feedback to identify where automation could safely replace manual work, identified the best vendor to support this effort, and then redesigned workflows to route simple requests through automation and self-service while preserving clear escalation paths for complex or sensitive issues.

This shift reclaimed meaningful support capacity without adding headcount, with up to 70% of incoming support volume handled through automation and self-service, faster response times for high-priority cases, and customer satisfaction consistently maintained above 95% CSAT.

A multi-product portfolio lacked clarity on which customer needs were table stakes versus true differentiators, leading to unfocused product design and imprecise segmentation. Drawing on customer support data, qualitative feedback, and behavioral insights, Alice partnered with product and design teams to surface recurring baseline needs and distinguish them from segment-specific drivers of value.

These insights were translated into more precise product requirements and sharper segmentation targets, helping teams prioritize long-term roadmap investments more effectively and align CX, product, and portfolio strategy around what mattered most to customers. As a result, teams were able to focus design efforts on a smaller set of validated needs, reducing speculative feature work and improving confidence in portfolio-level decisions.