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
| Stage |
Metrics |
What It Tells You |
| Acquisition |
Sessions, Users, Traffic sources, CPC, CAC |
Are you attracting enough visitors? From where? At what cost? |
| Engagement |
Pages/session, Time on site, Bounce rate, Product views |
Are visitors interested? Are they browsing? |
| Conversion |
Add-to-cart rate, Checkout initiation rate, Purchase conversion rate |
Where in the funnel are they dropping off? |
| Revenue |
Revenue, AOV, Items per order, Revenue per session |
How much are they spending? Is the mix healthy? |
| Retention |
Repeat purchase rate, Purchase frequency, Customer lifetime value |
Are they coming back? |
GA4 E-Commerce Events
| Event |
Trigger |
Key Parameters |
view_item |
Product page view |
item_id, item_name, price, category |
add_to_cart |
Add to cart click |
items array, value, currency |
begin_checkout |
Checkout started |
items, value, coupon |
add_payment_info |
Payment entered |
payment_type |
purchase |
Order completed |
transaction_id, value, tax, shipping, items |
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
1---2name: ecom-analytics3description: "Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Use this skill when the user needs to evaluate online store performance, diagnose conversion drop-offs, set up e-commerce tracking, or create performance dashboards — even if they say 'why are sales down', 'optimize our online store', 'set up GA4 for e-commerce', or 'what metrics should we track'.".4---56# E-Commerce Analytics78## Overview910E-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.1112## Framework1314```15IRON LAW: Diagnose by Funnel Stage, Not by Symptom1617"Sales are down" is a symptom, not a diagnosis. Decompose into funnel stages:18Traffic × Conversion Rate × AOV = Revenue1920If revenue drops 20%, is it because traffic dropped (acquisition problem),21conversion dropped (UX/pricing problem), or AOV dropped (product mix problem)?22Each requires a completely different fix.23```2425### E-Commerce Funnel & Key Metrics2627| Stage | Metrics | What It Tells You |28|-------|---------|------------------|29| **Acquisition** | Sessions, Users, Traffic sources, CPC, CAC | Are you attracting enough visitors? From where? At what cost? |30| **Engagement** | Pages/session, Time on site, Bounce rate, Product views | Are visitors interested? Are they browsing? |31| **Conversion** | Add-to-cart rate, Checkout initiation rate, Purchase conversion rate | Where in the funnel are they dropping off? |32| **Revenue** | Revenue, AOV, Items per order, Revenue per session | How much are they spending? Is the mix healthy? |33| **Retention** | Repeat purchase rate, Purchase frequency, Customer lifetime value | Are they coming back? |3435### GA4 E-Commerce Events3637| Event | Trigger | Key Parameters |38|-------|---------|---------------|39| `view_item` | Product page view | item_id, item_name, price, category |40| `add_to_cart` | Add to cart click | items array, value, currency |41| `begin_checkout` | Checkout started | items, value, coupon |42| `add_payment_info` | Payment entered | payment_type |43| `purchase` | Order completed | transaction_id, value, tax, shipping, items |4445### Diagnosis Framework4647**Phase 1: Traffic Check**48- Is total traffic up/down/flat vs prior period?49- Which channels changed? (organic, paid, social, direct, referral)50- Is traffic quality declining? (bounce rate, pages/session by source)5152**Phase 2: Conversion Check**53- Where is the biggest funnel drop-off?54- Compare: View → Add to cart → Checkout → Purchase55- Industry benchmark conversion rates: 1-3% overall, 5-10% add-to-cart5657**Phase 3: Revenue Check**58- AOV trend: rising (upselling working) or falling (discounting eroding value)?59- Product mix: is revenue shifting to lower-margin products?60- Revenue per session: the master metric (traffic quality × conversion × AOV)6162**Phase 4: Retention Check**63- Repeat purchase rate by cohort64- Time between first and second purchase65- LTV trend by acquisition channel6667## Output Format6869```markdown70# E-Commerce Performance Report: {Store}7172## Summary Dashboard73| Metric | Current | Prior Period | Change | Status |74|--------|---------|-------------|--------|--------|75| Sessions | {N} | {N} | {%} | 🟢/🟡/🔴 |76| Conversion Rate | {%} | {%} | {%} | 🟢/🟡/🔴 |77| AOV | ${X} | ${X} | {%} | 🟢/🟡/🔴 |78| Revenue | ${X} | ${X} | {%} | 🟢/🟡/🔴 |7980## Funnel Analysis81| Stage | Volume | Rate | Drop-off | Benchmark |82|-------|--------|------|----------|-----------|83| Sessions | {N} | 100% | — | — |84| Product Views | {N} | {%} | {%} | — |85| Add to Cart | {N} | {%} | {%} | 5-10% |86| Checkout | {N} | {%} | {%} | 40-60% of ATC |87| Purchase | {N} | {%} | {%} | 1-3% overall |8889## Diagnosis90- Primary issue: {funnel stage} — {specific problem}91- Root cause: {analysis}9293## Recommendations941. {action targeting the diagnosed stage}95```9697## Gotchas9899- **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.100- **GA4 sessions ≠ Universal Analytics sessions**: GA4 uses event-based model. Session timeout and attribution rules differ. Expect 5-15% discrepancy during migration.101- **Mobile conversion is always lower**: Mobile: 1-2%, Desktop: 3-5% is typical. Don't mix them in one number — analyze separately.102- **Seasonality matters**: Compare same period YoY, not just MoM. E-commerce has strong seasonal patterns (11.11, Christmas, Chinese New Year).103- **Revenue ≠ profit**: A 20% revenue increase from aggressive discounting may reduce profit. Track margin alongside revenue.104105## References106107- For GA4 setup guide, see `references/ga4-setup.md`108- For e-commerce benchmark data by industry, see `references/ecom-benchmarks.md`
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