If you're running Google Shopping campaigns, you're likely frustrated by how scattered your data is. Performance metrics live in Google Ads. Product attributes are in Merchant Center. Pricing intelligence is somewhere else entirely. Getting a complete picture of how your products are actually performing requires jumping between platforms, exporting CSVs, and manual spreadsheet work.
This guide covers everything you need to know about Google Shopping analytics: the metrics that matter, where to find your data, and how to use it to optimize your campaigns. Whether you're looking to improve ROAS, eliminate wasted spend, or gain competitive pricing insights, you'll learn how to make data-driven decisions at the product level.
What is Google Shopping Analytics?
Google Shopping analytics refers to the collection, analysis, and interpretation of performance data from your Shopping campaigns. Unlike standard Google Ads reporting that focuses on campaigns and ad groups, Shopping analytics goes deeper—down to the individual product (SKU) level.
This matters because Shopping campaigns behave differently than Search or Display. Each product in your Merchant Center feed becomes a potential ad, and understanding which products drive results (and which drain budget) is essential for profitability.
Key Insight
Most e-commerce advertisers look at campaign-level metrics. The real optimization opportunities are at the product level, where you can see exactly which SKUs are profitable and which are wasting budget.
Effective Google Shopping analytics combines data from multiple sources:
- Google Ads: Performance data (cost, clicks, conversions, revenue)
- Merchant Center: Product attributes (titles, prices, categories, custom labels)
- Price Competitiveness Reports: How your prices compare to competitors
- Search Share Metrics: Your visibility in Shopping results
Key Metrics to Track in Google Shopping
Not all metrics are created equal. Here are the ones that actually drive decisions, organized by what they tell you about your campaigns. For detailed definitions of each metric, see our metrics glossary.
Performance Metrics
These metrics tell you how your Shopping campaigns are performing financially:
| Metric | What It Measures | Target Range |
|---|---|---|
| ROAS | Revenue generated per dollar spent | 3x-5x+ (varies by margin) |
| CPA | Cost to acquire one conversion | Below your profit margin |
| Conversion Rate | % of clicks that convert | 1-3% typical for Shopping |
| Revenue | Total conversion value | Growth over time |
| Cost | Total ad spend | Within budget, driving ROI |
Visibility Metrics
Search share metrics reveal how much of the available market you're capturing. These are especially important for competitive markets. For a deep dive, see our complete impression share guide.
- Impression Share: Percentage of impressions you received out of total available. Low impression share means you're missing opportunities.
- Click Share: Percentage of clicks you received out of total available. This factors in ad position and quality.
- Top Impression Share: How often your ads appear in the top positions above organic results.
According to Google's documentation on impression share, lost impression share typically comes from two sources: budget limitations or ad rank (bid and quality). Diagnosing which is causing your losses is the first step to improvement.
Efficiency Metrics
- CTR (Click-Through Rate): How compelling your product listings are. Low CTR often indicates poor images, titles, or pricing.
- CPC (Cost Per Click): What you're paying for each click. Rising CPCs may indicate increased competition.
- AOV (Average Order Value): How much customers spend per order. Higher AOV can offset higher CPCs.
Competitive Metrics
Price competitiveness data comes from Google Merchant Center's Price Competitiveness report:
- Benchmark Price: The average price competitors charge for the same or similar products
- Price Gap: The percentage difference between your price and the benchmark
- Competitiveness Status: Whether you're priced higher, lower, or in line with competitors
Where to Find Google Shopping Analytics Data
One of the biggest challenges with Shopping analytics is that data lives in multiple places. Here's where to find what you need:
Google Ads Interface
Google Ads provides performance metrics at the product level through the Products tab in your Shopping campaigns. You can see:
- Impressions, clicks, cost, and conversions per product
- Product-level ROAS and CPA
- Search impression share data
Limitations: The interface doesn't combine this with Merchant Center attributes well. You can't easily filter by brand, product type, or custom labels without custom reporting.
Google Merchant Center
Merchant Center houses your product feed data and competitive intelligence. For more detail on what's available, see our Merchant Center Analytics guide. Key data includes:
- Product attributes (title, description, brand, categories)
- Custom labels (0-4)
- Price competitiveness reports
- Product status and disapprovals
Limitations: No performance data. You can't see which products are generating conversions without leaving Merchant Center.
Third-Party Analytics Dashboards
The most effective approach is combining data from both sources into a unified view. Tools like SKU Analyzer connect to both Google Ads and Merchant Center APIs to provide:
- Product performance with full attribute data
- Price competitiveness alongside conversion metrics
- Custom label filtering and segmentation
- Wasted spend identification
- Brand and category-level rollups
Key Takeaway
Google Ads shows what's happening. Merchant Center shows what you're selling. Combining both gives you the complete picture of why things are happening.
How to Optimize Google Shopping Using Analytics
Data without action is just numbers. Here's how to use your Shopping analytics to make improvements that impact the bottom line.
1. Identify and Eliminate Wasted Spend
Wasted spend is money spent on products that don't convert. In most Shopping accounts, a significant portion of budget goes to products that generate clicks but zero sales.
How to find it:
- Filter products where Cost > $0 and Conversions = 0
- Look at a meaningful time window (30-90 days)
- Sort by cost descending to find the biggest budget drains
What to do about it:
- High-cost, no conversions: Consider excluding these products or dramatically lowering bids
- Moderate cost, no conversions: Investigate why—check pricing, product page, availability
- Low cost, no conversions: May just need more time/data; monitor but don't panic
Important
Google Ads conversion data can take up to 7 days to fully attribute due to conversion lag. Don't make decisions based on the last few days of data—look at completed weeks.
2. Find and Scale Top Performers (Pareto Analysis)
The Pareto principle applies strongly to Shopping campaigns: roughly 20% of products typically drive 80% of revenue. Finding these winners and scaling them is often the highest-impact optimization.
How to do it:
- Export product performance data with revenue
- Sort by revenue descending
- Calculate cumulative revenue percentage
- Identify the products that reach 80% of total revenue
Actions for top performers:
- Increase bids to capture more impression share
- Check if you're losing impression share to budget—increase budget if so
- Optimize product titles and images to improve CTR
- Ensure inventory stays in stock
3. Fix Pricing Issues
Price competitiveness directly impacts Shopping performance. Products priced significantly above competitors will struggle to convert, while underpriced products leave money on the table.
Use price competitiveness data to categorize products. You can also use custom labels to segment products by price tier for easier campaign management:
| Price Gap | Status | Action |
|---|---|---|
| > +15% | Significantly Overpriced | Lower price or reduce ad spend |
| +5% to +15% | Slightly Overpriced | Monitor conversion rate; consider adjustment |
| -5% to +5% | Competitive | Maintain; focus on other optimization |
| -5% to -15% | Slightly Underpriced | Consider price increase for margin |
| < -15% | Significantly Underpriced | Strong candidate for price increase |
4. Improve Search Visibility
Low impression share means you're missing potential customers. Diagnose and address visibility issues:
- Lost IS (Budget): Your budget is limiting impressions. Increase budget or focus spend on better-performing products.
- Lost IS (Rank): Your bids or ad quality are too low. Improve bids, product titles, images, or feed quality.
For competitive products with strong ROAS, aim for 70%+ impression share. For lower-priority products, 30-50% may be acceptable.
Setting Up a Google Shopping Analytics Dashboard
A well-designed dashboard turns raw data into actionable insights. Here's what to include:
Essential Dashboard Views
- Overview KPIs: High-level metrics (cost, revenue, ROAS, conversions) with period-over-period comparison
- Time Series Charts: Trend visualization for key metrics over 7, 30, 90 days
- Product Table: Sortable list of all products with performance metrics
- Brand Performance: Metrics rolled up by brand for portfolio analysis
- Wasted Spend Tracker: Products consuming budget without converting
- Price Competitiveness: Your prices vs. benchmark with gap analysis
Recommended Refresh Cadence
- Real-time (when possible): High-level KPIs for daily monitoring
- Daily: Product performance data
- Weekly: Merchant Center product feed updates, price competitiveness
Tools like SKU Analyzer automatically sync data from both Google Ads and Merchant Center, providing these views without manual data exports or spreadsheet maintenance.
Common Google Shopping Analytics Mistakes
Avoid these pitfalls that undermine effective Shopping optimization:
1. Only Looking at Campaign-Level Data
Campaign averages hide what's really happening. A 3x ROAS at the campaign level might include products at 10x ROAS (stars) mixed with products at 0x ROAS (budget drains). Always dig into product-level data.
2. Ignoring Conversion Lag
Google Ads uses a lookback window of up to 30 days (default 7 days for Shopping). Conversions are attributed to the click date, not the conversion date. This means recent data always looks worse than it actually is. Wait for complete data before optimizing.
3. Not Segmenting by Product Attributes
Different product categories, brands, and price points behave differently. A 2x ROAS might be terrible for high-margin products but acceptable for low-margin items. Use custom labels and product types to segment analysis.
4. Chasing Vanity Metrics
Impressions and clicks feel good but don't pay bills. Focus on metrics tied to profitability: ROAS, CPA, gross profit. A product with 100,000 impressions and 0 conversions is worse than one with 1,000 impressions and 10 conversions.
5. Making Changes Too Frequently
Google's algorithms need time to learn. Making daily bid changes based on incomplete data creates noise, not optimization. Establish a regular cadence (weekly for most changes) and let data accumulate. Our bidding strategies guide explains how to set the right optimization cadence for different bid types.
Frequently Asked Questions
What metrics matter most for Google Shopping analytics?
The most important metrics are ROAS (Return on Ad Spend), CPA (Cost Per Acquisition), Conversion Rate, and Impression Share. ROAS tells you how much revenue you're generating per dollar spent, while CPA shows the cost to acquire each customer. Impression Share reveals how much of the available market you're capturing.
How is Google Shopping analytics different from Google Ads reporting?
Google Ads shows campaign and ad group level data, while Google Shopping analytics focuses on product-level (SKU) performance. This includes individual product ROAS, price competitiveness vs competitors, and product-specific impression share. You need to combine data from Google Ads and Merchant Center for complete product analytics.
How often should I check my Google Shopping analytics?
Review high-level KPIs (ROAS, spend, revenue) daily. Conduct deeper product-level analysis weekly to identify trends and optimization opportunities. Monthly, perform comprehensive reviews including wasted spend analysis and pricing adjustments. Remember that conversion data can take 7 days to fully attribute.
Can I track performance by individual product SKU?
Yes. Google Ads provides product-level reporting through Shopping campaigns, showing metrics like cost, clicks, conversions, and ROAS for each SKU. Dedicated analytics tools combine this with Merchant Center data to add product attributes, pricing intelligence, and competitive benchmarks for comprehensive SKU-level analytics.
What is wasted spend in Google Shopping?
Wasted spend refers to advertising cost on products that generate clicks but no conversions. These products consume budget without producing revenue. Identifying and addressing wasted spend—by pausing products, adjusting bids, or improving listings—is one of the fastest ways to improve Shopping campaign profitability.
Conclusion
Google Shopping analytics isn't about tracking more data—it's about tracking the right data and acting on it. The difference between average and exceptional Shopping performance comes down to:
- Product-level visibility: Seeing beyond campaign averages to individual SKU performance
- Unified data: Combining Ads performance with Merchant Center attributes and pricing intelligence
- Actionable insights: Knowing exactly which products to scale, fix, or pause
- Regular optimization: Making data-driven decisions on a consistent cadence
Stop switching between platforms and spreadsheets. The e-commerce brands winning at Shopping advertising are the ones with clear visibility into what's working at the product level.