The client is described by Laivly as America's leading beauty retailer, a retail and e-commerce business whose customer service agents support multiple brands and products. Its agents handle complex email inquiries such as lost orders, damaged items, refunds and escalations, and the company experiences waves of extreme ramp around the Q4 holiday season, when it hires and trains large numbers of new agents. The retailer is not named in the case study.

Retail and e-commerce companies experience waves of extreme ramp that require lengthy hiring and training periods, which lead to operational inefficiencies and an increased cost to the program. This retailer's agents support multiple brands and products, so training typically takes eight weeks or more before a new agent is productive.

New agents were also handling complex problems such as lost orders, damaged items, refunds and escalations, creating costly inefficiencies. These issues were exacerbated during the hectic Q4 holiday ramp period, when inquiry volume climbed sharply. The result was slow agent speed-to-value, reduced first contact resolution (FCR), and lower quality assurance (QA) and customer satisfaction (CSAT) scores.

Ahead of its busy holiday ramp season, the retailer wanted to help new agents reach production faster while handling an increased volume of customer inquiries, without sacrificing the high-quality, consultative customer experience its customers expect.

Laivly began by reviewing the brand's workflows and email efficiency to establish a baseline, then measured the results after implementation over a six-week period.

The provider implemented Sidd, its AI-powered agent-assist technology, which works across any system used by agents, including the brand's loyalty program and order management platform. Sidd quickly compiles the information an agent needs to resolve a customer's query, such as the customer's name, loyalty ID and order history, and surfaces the pertinent details referenced in the customer's email so the agent does not have to hunt for them.

Laivly also guides agents through order workflows and automated approvals, such as processing returns or re-shipping damaged items, and presents a checklist of best actions so newer agents always know their next move. Using machine-learned data, the platform proactively suggests accurate, on-brand response templates that the agent can personalise for a fast, high-touch resolution. Agents do not need a separate login; Sidd logs into each brand's systems on their behalf.

With this support, agents left nesting ahead of schedule and reached production levels five weeks faster, while the retailer recorded a significant decrease in email handle time and savings across key KPIs within the shortened ramp period.

• 62% reduction in new-agent ramp time, with agents leaving nesting ahead of schedule
• 16% improvement in CSAT scores and 28% improvement in productivity
• 30% improvement in email handle time (EHT) over the six-week measurement period
• Agents reached production five weeks faster, generating $277K in savings from the shortened ramp
• 100% week-over-week usage rate of Laivly among agents
• Positive feedback from previously unhappy agents, supporting morale and retention