القائمة
The Shopping Ads skill delivers end-to-end management of Google Shopping campaigns and Merchant Center product feeds.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | shopping-ads |
| description | The Shopping Ads skill delivers end-to-end management of Google Shopping campaigns and Merchant Center product feeds. |
Part of Agent Skills™ by googleadsagent.ai™
The Shopping Ads skill delivers end-to-end management of Google Shopping campaigns and Merchant Center product feeds. Shopping ads are the highest-intent ad format in Google's ecosystem — users see the product image, price, and merchant name before clicking, resulting in qualified traffic with strong purchase intent. The difference between mediocre and exceptional Shopping performance almost always comes down to feed quality and campaign structure.
Product feed optimization is the foundation. The skill audits every feed attribute — title, description, product type, Google product category, GTINs, custom labels, images, pricing, availability — against Google's requirements and competitive best practices. Titles are optimized with search-relevant attributes (brand, color, size, material) front-loaded for maximum visibility. Descriptions are enriched with long-tail query-matching terms. Custom labels enable performance-based segmentation (margin tiers, best sellers, seasonal items) that powers intelligent bidding strategies.
Campaign structure extends feed optimization into bid management. The skill designs Shopping campaign architectures using priority settings, custom label segmentation, and negative keyword sculpting to control which products match which queries at what bids. For Standard Shopping, this means tiered campaigns with query-level control. For PMax Shopping, it means asset group segmentation aligned with product performance clusters. Supplemental feeds, competitive pricing intelligence, local inventory ads, and free listings round out the comprehensive Shopping strategy.
flowchart TD
A[Merchant Center] --> B[Feed Analysis Engine]
B --> C[Attribute Audit]
C --> C1[Title Optimization]
C --> C2[Description Enrichment]
C --> C3[Category Mapping]
C --> C4[Image Quality Check]
C --> C5[GTIN/MPN Validation]
B --> D[Custom Label Strategy]
D --> D1[Label 0: Margin Tier]
D --> D2[Label 1: Best Sellers]
D --> D3[Label 2: Seasonality]
D --> D4[Label 3: Price Range]
D --> D5[Label 4: New vs Existing]
B --> E[Competitive Intelligence]
E --> E1[Price Benchmarks]
E --> E2[Click Share]
E --> E3[Impression Share]
C1 --> F[Optimized Feed]
C2 --> F
C3 --> F
C4 --> F
C5 --> F
D1 --> F
D2 --> F
D3 --> F
D4 --> F
D5 --> F
F --> G[Campaign Structure]
G --> G1[Standard Shopping\nPriority Tiers]
G --> G2[PMax Shopping\nAsset Group Segmentation]
E1 --> H[Bid Strategy]
E2 --> H
E3 --> H
G1 --> H
G2 --> H
H --> I[Performance Monitoring]
I --> J[Product-Level ROAS]
I --> K[Query-Level Analysis]
I --> L[Competitive Position Tracking]
Product feed audit and optimization engine:
async function auditProductFeed(merchantId) {
const products = await getMerchantProducts(merchantId);
const diagnostics = await getFeedDiagnostics(merchantId);
const audit = {
totalProducts: products.length,
activeProducts: products.filter(p => p.status === 'active').length,
disapproved: products.filter(p => p.status === 'disapproved'),
warnings: diagnostics.warnings,
attributeAnalysis: analyzeAttributes(products),
titleOptimization: auditTitles(products),
descriptionQuality: auditDescriptions(products),
imageQuality: auditImages(products),
pricingAnalysis: analyzePricing(products),
customLabelStrategy: designCustomLabels(products)
};
return audit;
}
function auditTitles(products) {
const issues = [];
for (const product of products) {
const title = product.title;
if (title.length < 25) {
issues.push({ productId: product.id, issue: 'Title too short', current: title });
}
if (title.length > 150) {
issues.push({ productId: product.id, issue: 'Title exceeds optimal length', current: title });
}
if (!title.toLowerCase().includes(product.brand?.toLowerCase())) {
issues.push({ productId: product.id, issue: 'Brand missing from title', current: title });
}
const optimizedTitle = buildOptimizedTitle(product);
if (optimizedTitle !== title) {
issues.push({
productId: product.id,
issue: 'Title can be optimized',
current: title,
recommended: optimizedTitle
});
}
}
return { issues, optimizationRate: issues.length / products.length };
}
function buildOptimizedTitle(product) {
const components = [
product.brand,
product.title.replace(product.brand, '').trim(),
product.color,
product.size,
product.material,
product.gender
].filter(Boolean);
const optimized = components.join(' - ');
return optimized.substring(0, 150);
}
function designCustomLabels(products) {
const performanceData = products.map(p => ({
id: p.id,
revenue: p.revenue30d,
cost: p.cost30d,
roas: p.revenue30d / Math.max(p.cost30d, 0.01),
margin: p.margin,
clicks: p.clicks30d,
conversions: p.conversions30d
}));
return {
customLabel0: {
name: 'Margin Tier',
values: assignMarginTiers(performanceData),
biddingImplication: 'Higher bids on high-margin products'
},
customLabel1: {
name: 'Performance Tier',
values: assignPerformanceTiers(performanceData),
biddingImplication: 'Aggressive bids on top performers, reduced on low performers'
},
customLabel2: {
name: 'Seasonality',
values: assignSeasonality(products),
biddingImplication: 'Boost seasonal products during peak periods'
},
customLabel3: {
name: 'Price Competitiveness',
values: assignPriceCompetitiveness(products),
biddingImplication: 'Higher bids when price-competitive, lower when overpriced'
},
customLabel4: {
name: 'Product Lifecycle',
values: products.map(p => ({
productId: p.id,
label: p.daysListed < 30 ? 'new_arrival' : p.daysListed > 180 ? 'clearance' : 'established'
})),
biddingImplication: 'Promotional bids for new arrivals and clearance'
}
};
}
Supplemental feed and competitive pricing:
function buildSupplementalFeed(products, enrichmentData) {
return products.map(product => ({
id: product.id,
custom_label_0: enrichmentData[product.id]?.marginTier,
custom_label_1: enrichmentData[product.id]?.performanceTier,
custom_label_2: enrichmentData[product.id]?.seasonality,
custom_label_3: enrichmentData[product.id]?.priceCompetitiveness,
custom_label_4: enrichmentData[product.id]?.lifecycle,
sale_price: enrichmentData[product.id]?.promotionalPrice,
promotion_id: enrichmentData[product.id]?.activePromotion
}));
}
function analyzeCompetitivePricing(products, benchmarkData) {
return products.map(product => {
const benchmark = benchmarkData[product.id];
if (!benchmark) return { productId: product.id, status: 'no_benchmark_data' };
const pricePosition = product.price / benchmark.benchmarkPrice;
return {
productId: product.id,
yourPrice: product.price,
benchmarkPrice: benchmark.benchmarkPrice,
priceIndex: pricePosition,
status: pricePosition <= 0.95 ? 'price_leader'
: pricePosition <= 1.05 ? 'competitive'
: pricePosition <= 1.15 ? 'slightly_above'
: 'overpriced',
clickShareImpact: estimateClickShareImpact(pricePosition),
recommendation: pricePosition > 1.15
? 'Consider price reduction or value-add messaging'
: 'Maintain current pricing strategy'
};
});
}
Shopping Ads is a core e-commerce skill within Buddy™ Agent. The platform connects directly to Merchant Center, running continuous feed audits that detect disapprovals, attribute issues, and optimization opportunities in real time. When products get disapproved, Buddy™ immediately notifies the user with the specific violation and a fix recommendation.
Buddy™ automates supplemental feed management, updating custom labels based on rolling performance data without manual CSV uploads. The platform generates and applies custom label assignments on a configurable schedule (daily or weekly), ensuring bid strategies always reflect current product performance.
For competitive pricing, Buddy™ monitors price benchmark data and alerts users when their products become uncompetitive. It connects pricing intelligence with bid strategy, automatically reducing bids on overpriced products and increasing bids on price-competitive items to maximize ROAS.
| Platform | Supported |
|---|---|
| Claude Code | ✅ |
| Cursor | ✅ |
| Codex | ✅ |
| Gemini | ✅ |
shopping ads, product feed, merchant center, feed optimization, custom labels, supplemental feeds, product titles, shopping campaigns, google shopping, product listing ads, competitive pricing, local inventory ads, free listings, shopping ROAS, product feed audit
© 2026 googleadsagent.ai™ | Agent Skills™ | MIT License
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