Omnichannel Support Automation for a UK Retail Group

Business Context

The client operated a multi-brand retail portfolio with seasonal demand spikes, high returns volume, and fragmented support channels. The service team used separate tools for email, chat, social, and order-management workflows, which led to long triage times and inconsistent customer experiences.

Core Challenges

1. Manual triage bottleneck: Agents spent significant time classifying straightforward requests (delivery status, returns, stock checks).
2. Knowledge inconsistency: Policy and promotional rules changed frequently, but response templates lagged.
3. Escalation friction: Complex tickets were escalated late, often without enough context for rapid resolution.

Delivery Approach

We implemented a three-layer support model:

1. AI triage layer: Intent detection, urgency classification, and automatic routing by issue type and customer value segment.
2. Resolution layer: Self-service responses grounded in approved policy content and real-time order/returns data.
3. Agent-assist layer: Suggested replies, summary generation, and recommended next action for escalated conversations.

Governance controls included response confidence thresholds, weekly transcript audits, and rollback-safe prompt versioning.

Implementation Timeline

• Weeks 1-2: Process mapping, intent taxonomy, baseline KPI instrumentation.
• Weeks 3-6: Knowledge grounding, escalation logic, API integration with order and returns systems.
• Weeks 7-9: Pilot launch on web chat and WhatsApp for two product lines.
• Weeks 10-12: Full rollout, QA automation, and service-team adoption coaching.

Operational Outcomes

The programme improved service responsiveness while reducing repetitive manual effort. Agent focus shifted from routine status questions to complex loyalty, billing, and exception-handling cases. Supervisors gained clearer operational visibility through intent-level KPI dashboards.

Next-Phase Roadmap

The client is now extending the assistant into post-purchase retention workflows, including proactive delivery updates, return-deflection journeys, and AI-generated follow-up recommendations for high-value segments.