Case Study: Resident improves CSAT and reduces churn with MaestroQA

Resident boosts CSAT 30% with MaestroQA

Resident, an e-commerce home furnishings company, faced a challenge in understanding the root causes of customer dissatisfaction, particularly within their complex returns process. Their low-response-rate CSAT surveys showed problems but couldn't pinpoint where the experience was breaking down. Manual quality assurance was unreliable and couldn't provide the data needed to tie friction to business outcomes like cancellations and churn. They partnered with vendor MaestroQA to find a solution.

Using MaestroQA's AI-powered LLM Classifiers, Resident automatically categorized 100% of customer conversations by intent, replacing inaccurate manual tagging. This provided complete visibility into the customer journey. By analyzing this data, they identified specific process bottlenecks, leading to targeted policy changes and workflow redesigns. The solution delivered significant results, including a 30% increase in CSAT, a 120% decrease in agent ramp time, and helped prevent customer churn.

Resident