Data-driven customer insights program
The platform uses machine learning algorithms to automatically build a 360° customer profile, generating 58 types of dynamic labels by analyzing 200+ behavioral characteristics (including browsing paths, purchasing cycles, service records, etc.). Typical labels include "promotion-sensitive", "luxury preferences", etc., with an accuracy rate of 88%. The system automatically updates the labeling system every 24 hours to ensure the timeliness of the marketing strategy.
In an actual application case, a fashion brand identified lost customers through the "unfinished payment" tag, and with targeted coupon push, the abandonment recovery rate increased by 65%. The analytics module also supports cross-channel behavioral tracking, for example, if customers browse the products on the official website and then inquire through LINE, the system will automatically correlate the behavioral trajectory. Data shows that the average customer lifetime value (LTV) of enterprises using this feature has increased by 3.2 times.
This answer comes from the articleOmnichat: The AI tool that integrates multi-platform chat to boost sales and serviceThe
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