A leading online retail platform operating across some of Asia’s most competitive e-commerce markets was scaling fast, but its CX training model could not keep pace. With a 600-person operation supporting both consumers and merchants, new agents took at least six months to reach full proficiency on theory-heavy training built around classroom instruction, documentation, and knowledge checks.
This created a compounding cycle of underprepared agents struggling on live customer interactions, which drove stress and early attrition that, in turn, increased pressure on hiring, compressed training further, and produced even fewer prepared agents. Training throughput eroded at every stage, and the downstream impact showed up in CSAT scores, wait times, and service inconsistency.
Download case studyTDCX deployed its privacy- and data-safe AI-powered Roleplay Simulator, where agents practiced against AI-generated customers with controllable personality types, emotional states, and complexity levels.
The simulator expanded to various languages with both voice and chat capability, replicating emotional nuances, regional conversational norms, complaint patterns, and cultural expectations.
Trainers and leaders had full control over simulation parameters, including customer personalities, scenario difficulty, and interactions tailored to specific product categories, policy updates, or seasonal campaigns.
The simulator gave trainers scale and precision by enabling them to oversee dozens of simultaneous practice sessions. Scored performance allowed data-informed coaching targeted at each agent’s specific areas of need.



