How Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4%

Musinsa, Korea’s largest fashion platform with 16.4 million members and operations in 13 countries, built a customer data platform in 2025 to create marketing audiences from customer profiles and behavioral data, later adding an AI assistant that answers marketers’ natural-language statistical questions while explaining its methodology. Its Audience Engine manages roughly 1.1 billion user-to-audience mappings, creating scaling, workload contention, and operational challenges in its self-hosted ClickHouse environment, where compute and EBS storage were coupled and multiple jobs competed on a single cluster. After moving to ClickHouse Cloud in AWS’s Seoul region, Musinsa retained much of its existing configuration while gaining managed operations, separated S3-backed storage and compute, workload-specific resources, automatic idling, and vertical autoscaling. The company reports reducing storage costs by 86.5% and total cost of ownership by up to 71.4%, while replacing Databricks Auto Loader and an external Spark cluster with ClickPipes for simpler, more scalable real-time ingestion.

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