Shopify Ads Helper

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name: shopify-ads-helper description: Optimize Shopify-specific paid growth workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, and YouTube Ads with Shopify event integrity, ROAS diagnostics, scale planning, and funnel optimization.

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Shopify Ads Helper

Purpose

Core mission:

Verify Shopify pixel and attribution status for conversion optimization readiness.

Diagnose account structure and creative performance affecting ROAS.

Recommend scaling route and budget increments.

Improve landing page and conversion funnel outcomes.

When To Trigger

Use this skill when the user asks for:

Shopify ads troubleshooting

OCPX readiness in Shopify stack

ROAS fluctuation diagnosis in store campaigns

checkout and funnel optimization

High-signal keywords:

shopifyads, shop, ecommerce, checkout

pixel, attribution, tracking, campaign

roas, cpa, budget, scale, funnel

Input Contract

Required:

shopify_store_url

tracking_stack_summary

channel_performance_snapshot

checkout_metrics

Optional:

product_margin_data

collection_level_performance

creative_breakdown

shipping_policy_context

Output Contract

1. Shopify Tracking Health Summary 2. Channel and Structure Diagnosis 3. ROAS Volatility Interpretation 4. Scale Path with Budget Gates 5. Checkout and Funnel Optimization Plan

Workflow

1. Validate Shopify event mapping consistency. 2. Confirm attribution alignment across channels. 3. Audit campaign architecture per product/collection. 4. Isolate ROAS drivers by audience/creative/offer. 5. Propose staged budget lift and funnel fixes.

Decision Rules

If checkout completion is weak, prioritize on-site fixes over spend expansion.

If collection-level margins vary, apply differential bid and budget controls.

If attribution mismatch is high, rely on blended and platform views in parallel.

If shipping/offer changes happened recently, separate pre/post effects before action.

Platform Notes

Primary scope:

Shopify Ads ecosystem with Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads

Platform behavior guidance:

Keep Shopify conversion events normalized before cross-platform optimization.

Pair channel decisions with collection-level economics when available.

Constraints And Guardrails

Do not optimize on ROAS alone when margin is uneven across SKUs.

Flag data-lag effects for short lookback windows.

Keep budget changes incremental under attribution uncertainty.

Failure Handling And Escalation

If event schema is broken, return patch checklist and freeze scale actions.

If Shopify app conflicts affect tracking, escalate with app inventory and event log.

If billing or policy lock appears, route to platform owner with urgency level.

Code Examples

Shopify Event Mapping Check

events: product_view: ViewContent add_to_cart: AddToCart checkout_start: InitiateCheckout order_paid: Purchase status: pass_with_warnings

Budget Lift Gate

if blended_roas >= 2.8 and checkout_cvr >= 2.2: increase_budget_pct: 15 else: hold_budget: true

Examples

Example 1: Shopify ROAS drift

Input:

ROAS unstable after theme update

Output focus:

tracking validation

cause isolation

corrective actions

Example 2: Collection scaling

Input:

One collection outperforming others

Output focus:

collection-level budget logic

structure recommendations

risk guardrails

Example 3: Checkout drop

Input:

Add-to-cart steady, purchase down

Output focus:

checkout funnel fixes

retargeting adjustment

measurement checks

Quality Checklist

[ ] Required sections are complete and non-empty

[ ] Trigger keywords include at least 3 registry terms

[ ] Input and output contracts are operationally testable

[ ] Workflow and decision rules are capability-specific

[ ] Platform references are explicit and concrete

[ ] At least 3 practical examples are included

Example 1: Shopify ROAS drift

Input:

ROAS unstable after theme update

Output focus:

tracking validation

cause isolation

corrective actions

Example 2: Collection scaling

Input:

One collection outperforming others

Output focus:

collection-level budget logic

structure recommendations

risk guardrails

Example 3: Checkout drop

Input:

Add-to-cart steady, purchase down

Output focus:

checkout funnel fixes

retargeting adjustment

measurement checks