Ecom Analytics

E-Commerce Analytics

Overview

E-commerce analytics measures online store performance across traffic, conversion, and revenue dimensions. This skill covers GA4 e-commerce tracking setup, funnel analysis, and key metric interpretation to diagnose why a store is or isn't performing.

Framework

IRON LAW: Diagnose by Funnel Stage, Not by Symptom

"Sales are down" is a symptom, not a diagnosis. Decompose into funnel stages:
Traffic × Conversion Rate × AOV = Revenue

If revenue drops 20%, is it because traffic dropped (acquisition problem),
conversion dropped (UX/pricing problem), or AOV dropped (product mix problem)?
Each requires a completely different fix.

E-Commerce Funnel & Key Metrics

GA4 E-Commerce Events

Diagnosis Framework

Phase 1: Traffic Check

• Is total traffic up/down/flat vs prior period?
• Which channels changed? (organic, paid, social, direct, referral)
• Is traffic quality declining? (bounce rate, pages/session by source)

Phase 2: Conversion Check

• Where is the biggest funnel drop-off?
• Compare: View → Add to cart → Checkout → Purchase
• Industry benchmark conversion rates: 1-3% overall, 5-10% add-to-cart

Phase 3: Revenue Check

• AOV trend: rising (upselling working) or falling (discounting eroding value)?
• Product mix: is revenue shifting to lower-margin products?
• Revenue per session: the master metric (traffic quality × conversion × AOV)

Phase 4: Retention Check

• Repeat purchase rate by cohort
• Time between first and second purchase
• LTV trend by acquisition channel

Output Format

# E-Commerce Performance Report: {Store}

## Summary Dashboard
| Metric | Current | Prior Period | Change | Status |
|--------|---------|-------------|--------|--------|
| Sessions | {N} | {N} | {%} | 🟢/🟡/🔴 |
| Conversion Rate | {%} | {%} | {%} | 🟢/🟡/🔴 |
| AOV | ${X} | ${X} | {%} | 🟢/🟡/🔴 |
| Revenue | ${X} | ${X} | {%} | 🟢/🟡/🔴 |

## Funnel Analysis
| Stage | Volume | Rate | Drop-off | Benchmark |
|-------|--------|------|----------|-----------|
| Sessions | {N} | 100% | — | — |
| Product Views | {N} | {%} | {%} | — |
| Add to Cart | {N} | {%} | {%} | 5-10% |
| Checkout | {N} | {%} | {%} | 40-60% of ATC |
| Purchase | {N} | {%} | {%} | 1-3% overall |

## Diagnosis
- Primary issue: {funnel stage} — {specific problem}
- Root cause: {analysis}

## Recommendations
1. {action targeting the diagnosed stage}

Gotchas

• Conversion rate is meaningless without traffic quality context: A 5% conversion rate from email (high-intent) and 0.5% from display ads (low-intent) are both normal. Don't compare across channels.
• GA4 sessions ≠ Universal Analytics sessions: GA4 uses event-based model. Session timeout and attribution rules differ. Expect 5-15% discrepancy during migration.
• Mobile conversion is always lower: Mobile: 1-2%, Desktop: 3-5% is typical. Don't mix them in one number — analyze separately.
• Seasonality matters: Compare same period YoY, not just MoM. E-commerce has strong seasonal patterns (11.11, Christmas, Chinese New Year).
• Revenue ≠ profit: A 20% revenue increase from aggressive discounting may reduce profit. Track margin alongside revenue.

References

• For GA4 setup guide, see references/ga4-setup.md
• For e-commerce benchmark data by industry, see references/ecom-benchmarks.md