A large U.S. home improvement retailer faced slow and inconsistent complaint resolution due to rule-based workflows in Dynamics 365. Manual triage and resolution processes increased handling time, raised service costs, and affected customer satisfaction. Blackstraw implemented predictive AI agents that automated complaint handling and resolution workflows. This led to 65% faster complaint resolution, 70% automated handling, improved customer satisfaction, and lower operational service costs.
The retailer depended on set rules and manual processes to handle customer complaints across service channels. As the number of complaints grew, these workflows became hard to manage, leading to inconsistent resolution results and a heavy dependence on customer service agents. The organisation needed a smarter, more proactive approach that could understand customer issues in real-time, apply policy-driven logic, and resolve cases efficiently while maintaining transparency and control.
Predictive Complaint Resolution Agents: Deployed AI agents capable of interpreting customer complaints in real time and predicting optimal resolution paths before case submission.
Context-Aware Data Retrieval: Integrated agents with order history, service records, and warranty data to support accurate, policy-compliant decisions.
Automated Execution Workflows: Enabled execution agents to automate downstream actions such as service scheduling, refunds, and customer communications.
Responsible, Explainable AI Design: Implemented policy-driven AI logic to ensure consistent, auditable, and explainable resolution outcomes.
Faster Complaint Resolution: Achieved 65% reduction in complaint resolution time through predictive automation.
High Automation Coverage: Automated 70% of complaint handling, significantly reducing manual effort.
Improved Customer Experience: Delivered more consistent and timely resolutions, improving customer satisfaction.
Lower Service Operations Cost: Reduced operational overhead by minimizing agent workload and rework.
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