How Kuaishou E‑Commerce Built a Data Metric System to Power Decision‑Making

Indicator System Construction Necessity

In the context of Kuaishou e‑commerce, building a metric system is essential to provide data support for business decisions, enabling precise analysis of sales profit, user‑behavior conversion, and other key indicators to optimize product strategy and market positioning.

1. Kuaishou E‑Commerce Business Overview

The business follows the "people‑goods‑scene" model. The content scene, composed of live streaming and short videos, connects users and delivers value; live streams drive most transactions through curated content, product attraction, and marketing tools, while short videos focus on "planting grass" to inspire purchases. The shelf scene uses product cards to link with the content scene, enabling product discovery through store search, mall pages, and recommendation lists.

2. Business Challenges

Data product managers often experience low efficiency when evaluating the reuse of existing metrics for new business needs, slowing project progress and resource allocation. Data engineers may face unclear metric definitions and scopes, leading to uncertainty during implementation. After delivery, operators (e.g., e‑commerce operators) can encounter inconsistent metric names or vague definitions, making data interpretation difficult and hindering decision efficiency. Additionally, business personnel and managers may lack a holistic view of data performance, limiting strategic insight.

3. Metric System Construction Practices

The metric system is built around three stages of the user lifecycle—exploration, cultivation, and conversion—aligned with five operational scenarios: potential consumer identification, content‑commerce integration, IP‑based marketing interaction, merchant‑driven sales via influencers, and retention through membership and re‑engagement strategies. By mapping these scenarios to specific indicators, the system supports data production, querying, and usage across roles.

4. Metric System Management

Effective management involves defining clear metric definitions, standardizing naming conventions, and selecting appropriate visualization styles to convey insights to business users.

5. Summary

The constructed metric system provides a data‑driven foundation for Kuaishou e‑commerce, enhancing decision‑making, improving operational efficiency, and supporting continuous product and market optimization.

6. Q&A

Addressed common questions about metric definition clarity, implementation challenges, and usage best practices.