Data Intelligence Driving Business Growth: Overview of CI, BI, and AI

The session introduces data intelligence as a driver of business growth, emphasizing its relevance to product operations, engineering, analysis, and management.

Background : Data applications face three major challenges—low analysis efficiency for business units, heavy workload for data teams, and high infrastructure costs with unclear value.

Data intelligence aims to push data consumption to the "last mile" by integrating three intelligent modules: CI (Customer Intelligence), BI (Business Intelligence), and AI (Artificial Intelligence), forming the formula DI = CI + BI + AI.

CI – Customer Intelligence : Focuses on user profiling, behavior analysis, and sentiment insights. Xiaomi builds a comprehensive user tag system across hardware, e‑commerce, and services, enabling precise audience targeting, personalized operations, and advertising support.

BI – Business Intelligence : Provides deep analytical capabilities beyond dashboards, including anomaly detection, root‑cause analysis, time‑series forecasting, and intelligent insights to improve analysis efficiency and support data‑driven decisions.

AI – Artificial Intelligence : Leverages large language models to transform data interaction from GUI to LUI, enabling conversational data queries, automatic insight generation, and seamless integration of enterprise knowledge into analytics.

The integrated platform supports multi‑scenario data consumption, offering tools such as TOPN, distribution analysis, and comparative metrics, while also delivering proactive notifications and natural‑language query capabilities.

Overall, the data intelligence framework enhances data accuracy, timeliness, and business impact, fostering a data‑driven culture that maximizes value across Xiaomi’s ecosystem.