10 Essential E‑Commerce Metrics Every Analyst Should Master

What Are Data Metrics?

Data metrics are the angles through which we cut into data, telling us what to collect, monitor, and compare against historical performance.

Types of Metrics

Commonly used metrics include DAU, new registrations, PV, while business‑specific metrics might focus on new live‑stream hosts or hotel room bookings.

Basic Logic for Viewing E‑Commerce Data

1. From Event Sequence: Traffic → Behavior → Transaction

First, attract users (traffic), then watch them browse and add to cart (behavior), and finally complete payment (transaction).

2. From Problem‑Solving Perspective: Transaction → Traffic → Behavior

Start with the final result (transaction), assess whether traffic changes caused it, and if traffic is stable, drill down into behavior to spot anomalies in key steps such as search, product detail, add‑to‑cart, and order.

Common Data Metrics

1. Transaction Metrics (The Ultimate Goal)

GMV and Order Volume describe the result but cannot alone explain causes.

Conversion Rate = Introduced Orders / Traffic reflects how efficiently traffic turns into orders, affected by product category, promotional tactics, and traffic‑page relevance.

Average Order Value (AOV) = GMV / Introduced Orders shows the average spend per order, varying by category and influenced by bundling or discount strategies.

UV Value = GMV / Traffic indicates the average revenue per visitor, helping assess traffic quality and business‑page match.

2. Traffic Metrics (Determine Success)

UV & PV – UV counts unique visitors, PV counts page views; both are essential for gauging potential GMV.

Per‑Capita Browsing Times = PV / UV shows how many times each visitor browses the page on average, varying by scenario.

3. Behavior Metrics (Root Cause Analysis)

Click‑Through Rate = Module Clicks / Page Visitors measures user interest in a module.

Exposure Click‑Through Rate = Module Clicks / Module Exposures removes the bias of page depth, offering a fairer comparison of module attractiveness.

Exposure Rate = Module Exposures / Page Visitors reveals how deep users scroll and which screens receive attention.

Dwell Time indicates the average seconds a user stays on the page.

Thought prompts such as “When should we use click‑through vs. exposure click‑through?” and “Does higher exposure rate or longer dwell time always mean a better page?” are included to guide analysis.