Google Ads API Metrics: Essential Fields for Shopping Campaign Analysis

If you're building custom analytics for Google Shopping campaigns, understanding the Google Ads API metric fields is essential. Queries like metrics.conversions_value appearing in your Search Console indicate users are looking for guidance on these API fields. This guide covers the most important metrics available through the Google Ads API for Shopping campaign analysis.

The Google Ads API provides access to hundreds of metrics. For Shopping campaigns, we'll focus on the fields that matter most for tracking revenue, costs, conversions, and competitive position at the product level.

Core Performance Metrics

These fundamental metrics track the basic performance of your Shopping ads: how often they're shown, clicked, and what they cost.

Conversion Metrics

Conversion metrics are the heart of Shopping campaign performance. They tell you what actually matters: did clicks turn into sales, and how much revenue did they generate?

ROAS calculation using API fields:

ROAS = metrics.conversions_value / (metrics.cost_micros / 1000000)

All Conversions vs. Conversions

Google Ads provides two sets of conversion metrics. Understanding the difference is crucial for accurate analysis:

Field	Includes
metrics.conversions	Only conversion actions marked "Include in Conversions"
metrics.all_conversions	All conversions including cross-device, view-through, and secondary actions
metrics.conversions_value	Value of included conversions only
metrics.all_conversions_value	Value of all conversion types

Impression Share Metrics

Impression share metrics reveal how much of the available market you're capturing. These are critical for understanding growth opportunities and competitive position.

Shopping-Specific Metrics and Segments

For Shopping campaigns, you'll often want product-level data. The shopping_performance_view resource combined with product segments gives you SKU-level analytics.

Key Segments for Product-Level Data

Segment	Description
segments.product_item_id	The offer_id from your product feed (your SKU)
segments.product_title	The product title from your feed
segments.product_brand	The brand attribute from your feed
segments.product_category_level1-5	Google product category hierarchy
segments.product_custom_attribute0-4	Custom labels from your feed
segments.date	Daily breakdown of metrics

Example GAQL Query for Product Performance

Here's a sample Google Ads Query Language (GAQL) query to retrieve product-level Shopping performance:

SELECT
  segments.date,
  segments.product_item_id,
  segments.product_title,
  segments.product_brand,
  metrics.impressions,
  metrics.clicks,
  metrics.ctr,
  metrics.cost_micros,
  metrics.conversions,
  metrics.conversions_value,
  metrics.search_impression_share,
  metrics.search_click_share
FROM shopping_performance_view
WHERE segments.date DURING LAST_30_DAYS
ORDER BY metrics.cost_micros DESC
LIMIT 1000

Additional Useful Metrics

Beyond the core metrics, these fields provide deeper insights for advanced analysis:

Metrics Not Available for Shopping

Some Google Ads metrics aren't available or behave differently for Shopping campaigns:

• Quality Score - Not available for Shopping; feed quality factors work differently
• Search Terms - Available through search_term_view but requires additional permissions
• Ad-level metrics - Shopping doesn't have traditional ads; product data comes from your feed
• Keyword metrics - Shopping targets products, not keywords

Best Practices for API Data Analysis

1. Account for Conversion Lag

Conversions can be attributed up to 90 days after a click (depending on your settings). Recent data will understate true performance. For accurate analysis, exclude the last 7-14 days or use the conversion lag report to understand your typical delay. This is especially important when optimizing your Shopping campaigns based on recent performance data.

2. Handle Nulls and Zeros

Some metrics return null when there's insufficient data (especially impression share metrics). Your code should handle these cases:

impression_share = row.metrics.search_impression_share or 0
if impression_share > 0:
    # Safe to use in calculations

3. Aggregate Appropriately

Some metrics can be summed (impressions, clicks, cost, conversions) while others must be recalculated from their components:

• Sum directly: impressions, clicks, cost_micros, conversions, conversions_value
• Recalculate: CTR (clicks/impressions), ROAS (value/cost), conversion rate (conversions/clicks)
• Average weighted: Impression share metrics (weight by eligible impressions)

4. Use Date Segments for Trends

Always include segments.date when building time-series dashboards. This lets you track performance changes over time and identify trends.

Frequently Asked Questions

Conclusion

Understanding Google Ads API metrics is essential for building custom Shopping analytics. The fields covered in this guide—from basic performance metrics like metrics.impressions and metrics.clicks to critical business metrics like metrics.conversions_value and impression share—provide the foundation for comprehensive campaign analysis.

Key points to remember:

• Cost fields use micros (divide by 1,000,000) as documented in the Google Ads reporting guide
• Percentage fields return decimals (0.65 = 65%)
• Use shopping_performance_view with product segments for SKU-level data
• Account for conversion lag when analyzing recent data
• Understand the difference between conversions and all_conversions

For more on interpreting these metrics once you have the data, see our metrics glossary, ROAS guide, and analytics guide. Tools like SKU Analyzer automate the API data collection and present these metrics in a unified dashboard, saving you from building and maintaining custom integrations.