Define and audit e-commerce analytics — conversion rate, AOV, CLV, cohort/funnel metrics, and the standard GA4 ecommerce event spec (view_item, add_to_cart, begin_checkout, purchase). Includes a dataLayer event validator. Triggers: defining commerce KPIs, instrumenting GA4 ecommerce events, auditing tracking.
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You cannot optimize what you mis-measure. Define the KPIs that actually move a store and instrument the standard ecommerce event spec correctly — platform-agnostic, with a validator for GA4 dataLayer events.
Gather: current tracking (GA4/GTM/other), business model (one-time vs subscription), key conversion actions, and goal (define KPIs, design/instrument events, or audit existing tracking).
| Mode | Trigger | Output |
|---|---|---|
| KPIs | kpis | KPI framework + dashboard spec |
| Events | events | Ecommerce event taxonomy + dataLayer spec |
| Audit | audit | Tracking gap + data-quality review |
| Metric | Formula | Watch for |
|---|---|---|
| Conversion rate | orders / sessions | Segment by device/channel |
| AOV | revenue / orders | Moves with promos/bundles |
| CLV | avg order value × frequency × lifespan | The number that justifies CAC |
| Cart abandonment | 1 − (checkouts / carts) | Diagnoses checkout friction |
| Repeat rate | repeat customers / total | Retention health |
| Sell-through | units sold / units received | Feeds inventory-stock forecasts |
Rule: Pair every acquisition metric with a margin metric — revenue growth on negative contribution margin is a trap.
The standard GA4 ecommerce funnel events, each carrying currency + an items[] array:
view_item_list → view_item → add_to_cart → begin_checkout → add_shipping_info → add_payment_info → purchase (plus remove_from_cart, refund).
Each items[] entry: item_id, item_name, price, quantity (+ optional item_brand, item_category, item_variant). purchase also needs transaction_id and value.
Validate a captured dataLayer against this spec:
python skills/commerce-analytics/scripts/ga4_ecommerce_validate.py # demo events
python skills/commerce-analytics/scripts/ga4_ecommerce_validate.py events.json
It reports PASS/FAIL per event with the missing required fields. For the full taxonomy and parameter reference, see references/ga4-ecommerce-events.md.
Common faults: missing transaction_id (duplicate purchases), value excluding/including tax inconsistently, items[] absent on purchase, double-firing (GTM + hardcoded). Cross-check store revenue vs GA4 revenue — variance > 5% means a tracking bug.
| Request | Output |
|---|---|
| KPIs | KPI framework + dashboard layout |
| Events | Event taxonomy + dataLayer spec |
| Audit | Gap analysis + data-quality scorecard |
Commerce tracking is COMPLIANT when the full funnel fires with valid items[] and currency, purchase carries a unique transaction_id, revenue reconciles within 5%, and KPIs pair growth with margin.
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