Shopping campaign success isn't about spending more—it's about spending smarter. Analytics give you the visibility to identify what's working, cut what isn't, and scale what's profitable. Yet most advertisers barely scratch the surface of available data, making decisions on incomplete information.
This guide covers the full analytics landscape: from essential metrics every advertiser should track, to advanced techniques for product-level profitability analysis, brand performance segmentation, and competitive intelligence.
Essential Shopping Metrics
Before diving into advanced analytics, you need a solid foundation in core metrics. These are the building blocks for all Shopping campaign analysis, and understanding them is essential for choosing the right bidding strategies.
Cost & Spend Metrics
Cost (Spend)
Definition: Total amount spent on clicks
Why it matters: Your primary investment metric. Track cost at campaign, product group, and product levels to understand where budget flows.
Average CPC (Cost Per Click)
Definition: Cost / Clicks
Why it matters: Indicates auction competitiveness. Rising CPCs may signal increased competition or improved ad quality. For more on competitive dynamics, see Google's Auction Insights documentation.
Engagement Metrics
Impressions
Definition: Number of times your ads were shown
Why it matters: Measures visibility and reach. Low impressions indicate budget, bid, or Shopping campaign feed issues limiting exposure.
Click-Through Rate (CTR)
Definition: Clicks / Impressions × 100
Why it matters: Measures ad relevance and appeal. Low CTR suggests poor product images, titles, or pricing relative to competitors.
Conversion Metrics
Conversions
Definition: Number of completed purchase actions
Why it matters: The ultimate success metric. Ensure your conversion tracking is properly configured for accurate measurement.
Conversion Rate
Definition: Conversions / Clicks × 100
Why it matters: Measures landing page and checkout effectiveness. Low conversion rates point to site issues, not just ad problems.
Cost Per Conversion (CPA)
Definition: Cost / Conversions
Why it matters: Shows acquisition efficiency. Compare CPA to your target to assess profitability at the product level.
For the complete reference of all Shopping metrics, see our metrics glossary.
ROAS: The Profitability Metric
Return on Ad Spend (ROAS) is the most important metric for Shopping campaign profitability. It tells you how much revenue you generate for every dollar spent on advertising.
Calculating ROAS
ROAS = Conversion Value / Cost × 100
A ROAS of 400% means you earn $4 in revenue for every $1 spent on ads. Whether this is "good" depends entirely on your profit margins.
Break-Even ROAS
Your break-even ROAS is the point where ad spend equals profit (not revenue). Calculate it based on your gross margin:
Break-Even ROAS = 1 / Gross Margin %
| Gross Margin | Break-Even ROAS | Target ROAS (for profit) |
|---|---|---|
| 20% | 500% | 600%+ |
| 30% | 333% | 400%+ |
| 40% | 250% | 300%+ |
| 50% | 200% | 250%+ |
| 60% | 167% | 200%+ |
Key Insight
ROAS benchmarks are meaningless without margin context. A 300% ROAS is excellent for a 50% margin product but unprofitable for a 20% margin product. Always calculate your specific break-even point.
For detailed ROAS strategies and optimization techniques, see our ROAS guide.
Understanding Conversion Lag
One of the most misunderstood aspects of Shopping analytics is conversion lag—the delay between when a click occurs and when the conversion is recorded and attributed back to that click.
How Conversion Attribution Works
When a user clicks your ad on January 1st and converts on January 5th, Google Ads attributes that conversion back to January 1st (the click date), not January 5th (the conversion date). This means:
- Today's data is always incomplete—conversions are still coming in
- Yesterday's data is incomplete
- Data from 7-14 days ago is usually ~90% complete
- Data from 30+ days ago is typically fully matured
Common Mistake
Looking at yesterday's ROAS and panicking because it's low. The data hasn't matured yet. Always compare apples to apples by using date ranges that have had time to fully attribute conversions.
Accounting for Conversion Lag
Practical strategies for working with lagged data:
- Exclude recent days: When analyzing performance, exclude the last 7 days to avoid incomplete data
- Use "Days to Conversion" report: In Google Ads, this shows your typical conversion lag pattern
- Compare like periods: Compare last week to two weeks ago, not to yesterday
- Track trends, not snapshots: Look at directional movement over time, not single-day performance
For a complete explanation, see our conversion lag guide.
Product-Level Analytics
Campaign-level metrics hide the real story. A campaign with 300% ROAS might have products at 800% ROAS subsidizing products at -100%. Product-level analytics reveal these hidden patterns.
Where to Find Product Data
In Google Ads:
- Navigate to Products in the left menu
- View by Product group or individual Items
- Add columns for conversions, conversion value, ROAS
Product Performance Segmentation
Segment products into performance tiers based on ROAS and volume:
| Tier | Criteria | Action |
|---|---|---|
| Heroes | High ROAS + High volume | Maximize spend, increase bids |
| Potentials | High ROAS + Low volume | Increase bids to get more volume |
| Volume Drivers | Low ROAS + High volume | Optimize titles, reduce bids |
| Losers | Low ROAS + Low volume | Pause or exclude from campaigns |
Zero-Conversion Products
Products that accumulate cost without converting are pure budget waste. These "wasted spend" products are often hidden in aggregate metrics but can consume 20-40% of total spend in poorly optimized accounts.
For strategies on identifying and handling these products, see our zero-conversion products guide and wasted ad spend guide.
Brand Performance Analysis
If you sell multiple brands, understanding performance by brand reveals portfolio-level insights that product-level analysis misses.
Brand-Level Metrics to Track
- Brand ROAS: Which brands deliver the best return?
- Brand CPA: Cost to acquire a customer by brand
- Brand contribution: % of total revenue from each brand
- Brand impression share: Visibility by brand vs competitors
Common Brand Analysis Insights
- Margin vs ROAS mismatch: A brand with high ROAS but low margins may actually be less profitable than a lower-ROAS, higher-margin brand
- Volume vs efficiency tradeoff: Niche brands often have better ROAS but limited scale
- Competitive dynamics: Some brands face more auction competition, driving up CPCs
Analysis Example
Brand A: 250% ROAS, 60% margin = profitable. Brand B: 350% ROAS, 20% margin = barely break-even. Looking at ROAS alone would lead you to invest more in Brand B, but margin-adjusted analysis shows Brand A is actually more profitable per dollar spent.
For detailed brand analysis techniques, see our brand performance guide.
Building Effective Reports
Regular reporting creates accountability and surfaces trends before they become problems. The key is reporting on metrics that drive decisions, not vanity metrics.
Weekly Report Template
A weekly Shopping report should cover:
- Top-level KPIs: Cost, revenue, ROAS, conversions (vs prior week and prior year)
- Campaign breakdown: Performance by campaign with week-over-week changes
- Top/bottom products: Best and worst performers by ROAS or cost
- Search terms: New negative keyword candidates, emerging queries
- Action items: Specific changes to make based on data
Reporting Best Practices
- Consistent timeframes: Always compare the same day ranges (Mon-Sun vs Mon-Sun)
- Account for lag: Exclude recent days or note that data is incomplete
- Focus on actionable insights: Every data point should suggest a potential action
- Trend over snapshot: 4-week trends are more meaningful than single-week data
For reporting templates and workflows, see our Shopping reporting guide.
Competitive Analysis with Auction Insights
Auction Insights shows how your Shopping ads perform relative to competitors in the same auctions. This competitive intelligence helps explain performance changes and identify opportunities.
Key Auction Insight Metrics
- Impression share: Your impressions / total available impressions
- Overlap rate: How often a competitor's ad showed alongside yours
- Outranking share: How often your ad ranked above a competitor's
- Position above rate: How often a competitor's ad ranked above yours
Using Auction Insights
Common use cases:
- Diagnosing drops: If your impressions dropped, did a competitor increase presence?
- Competitive pressure: High overlap with aggressive competitors may require bid adjustments
- Market entry: New competitors appearing in Auction Insights signal market changes
For detailed competitive analysis strategies, see our Auction Insights guide.
Quick Metrics Reference
Here's a quick reference for the most commonly used Shopping metrics. For complete definitions and formulas, see our full metrics glossary.
| Metric | Formula | Good Benchmark |
|---|---|---|
| ROAS | Revenue / Cost | 300-500% (varies by margin) |
| CTR | Clicks / Impressions | 0.5-2% for Shopping |
| Conversion Rate | Conversions / Clicks | 1-3% typical |
| CPA | Cost / Conversions | Varies by AOV and margin |
| Impression Share | Your impr / Eligible impr | 30-60% is typical |
| Avg CPC | Cost / Clicks | $0.30-$1.50 typical |
Frequently Asked Questions
What is a good ROAS for Google Shopping?
A good ROAS varies by industry and margin. Generally, 300-400% (3-4x) is considered healthy for most e-commerce. High-margin products can be profitable at 200%, while low-margin products may need 500%+ to be viable. Calculate your break-even ROAS based on your profit margins.
What is conversion lag and why does it matter?
Conversion lag is the delay between a click and the attributed conversion. Google Ads attributes conversions back to the original click date, which can take 1-30 days depending on your conversion window. This means recent data is incomplete and will improve over time. Always account for conversion lag when analyzing performance.
How do I track product-level performance in Google Shopping?
In Google Ads, navigate to Products > Product groups to see performance by product. You can also use the shopping_performance_view in the Google Ads API for programmatic access. Third-party tools like SKU Analyzer combine this with Merchant Center data for complete product analytics.
What metrics should I track for Shopping campaigns?
Essential metrics include: ROAS (return on ad spend), conversion rate, cost per conversion (CPA), click-through rate (CTR), impression share, and average CPC. At the product level, track cost, revenue, conversions, and profitability to identify winners and losers.
Start Making Data-Driven Decisions
Analytics separate guessing from knowing. The advertisers who win in Shopping aren't necessarily spending the most—they're spending the smartest, using data to guide every decision.
Key takeaways:
- Understand your break-even ROAS based on actual margins, not industry benchmarks
- Always account for conversion lag when analyzing recent performance
- Product-level analysis reveals the winners and losers hidden in aggregate metrics
- Brand performance analysis helps optimize portfolio allocation
- Regular reporting creates accountability and surfaces trends early
- Competitive insights from Auction Insights explain performance changes
Tools like SKU Analyzer automate much of this analysis, combining Google Ads and Merchant Center data to surface product-level insights, identify wasted spend, and track brand performance without manual data wrangling.