Google Ads Dimensions & Metrics: Complete Reference 2026

Understanding the full landscape of Google Ads dimensions and metrics is essential for anyone running paid search, display, shopping, video, or Performance Max campaigns. Whether you're building custom dashboards, pulling data through the Google Ads API with GAQL queries, or analyzing reports in the Google Ads interface, knowing exactly what data is available — and what each field means — is the foundation of effective campaign optimization.

This guide provides a complete reference of every dimension and metric available in Google Ads as of 2026. We've organized them by level and category, included the API resource and field names for developers, and added practical context on when and how to use each one. We also cover recent changes that affect how you access and interpret your data.

What Are Google Ads Dimensions vs Metrics?

Before diving into the full reference, it's important to understand the difference between dimensions, metrics, and segments — three concepts that are fundamental to Google Ads reporting but serve different purposes.

Dimensions are descriptive attributes that define what you're looking at. They are the identifiers, settings, and properties that let you organize and filter your data. Examples include campaign name, ad group ID, keyword text, match type, and ad type. In the Google Ads API, dimensions come from resource fields (like campaign.name or ad_group.id). Dimensions answer the question: "How do I want to slice this data?"

Metrics are quantitative measurements that tell you how things performed. They are the numbers: impressions, clicks, cost, conversions, CTR, CPC. In the API, metrics live under the metrics object (like metrics.impressions or metrics.cost_micros). Metrics answer the question: "What happened with my ads?"

Segments are a special type of dimension that you can apply across any resource to break down performance. For example, you can segment your campaign metrics by device, network, day of week, or conversion action to identify which slices drive the best results. In GAQL, segments are specified in the SELECT clause alongside resource fields and metrics.

How Is Google Ads Data Structured?

Google Ads data follows a strict hierarchy: Account > Campaign > Ad Group > Ad / Keyword. Each level inherits configuration from above and adds its own settings. Campaigns define the type (Search, Display, Shopping, Video, PMax), bidding strategy, budget, and network targeting. Ad groups organize keywords, audiences, and default bids. Ads contain the creative (headlines, descriptions, URLs), and keywords define the search queries you bid on.

In the Google Ads API, data is queried using Google Ads Query Language (GAQL) — a SQL-like syntax where you SELECT resource fields, segments, and metrics FROM a specific resource (like campaign, ad_group, or keyword_view). Unlike the Meta API where metrics are returned through a separate Insights endpoint, the Google Ads API returns dimensions and metrics together in a single query. The segments object provides cross-cutting breakdowns comparable to Facebook's breakdown dimensions.

One important difference from other platforms: Google Ads uses micros for all monetary values in the API. A value of 1,500,000 micros equals $1.50 in actual currency. This applies to cost, bids, budgets, and all cost-related metrics. Always divide by 1,000,000 when displaying or calculating with API monetary values.

Campaign-Level Dimensions

Campaign-level dimensions define the top-level structure of your advertising. These fields identify the campaign and its core configuration — campaign type, bidding strategy, budget, network settings, and status. Use these dimensions to organize reporting by campaign and understand the strategic setup behind your results.

Ad Group-Level Dimensions

Ad group dimensions define the targeting and bidding context within a campaign. Ad groups contain your keywords (for Search), audience signals, and ads. These fields control how your ads are organized, what default bids apply, and the structural relationship between keywords and creative.

Keyword Dimensions

Keyword dimensions describe your search targeting criteria — the words and phrases you bid on, their match types, and their quality diagnostics. These are the most granular targeting dimensions in Search campaigns and directly impact when your ads appear, how much you pay, and where you rank. Quality Score components at the keyword level are among the most important diagnostics in the platform.

Ad & Creative Dimensions

Ad-level dimensions describe the individual ad units — their format, content, quality indicators, and status. Google Ads supports multiple ad types including Responsive Search Ads, Responsive Display Ads, image ads, video ads, Shopping product ads, and app ads. Understanding these dimensions is critical for creative analysis and optimization.

Core Performance Metrics

These are the fundamental metrics that measure how your ads are delivered and interacted with. Every Google Ads advertiser should understand these — they form the basis of all campaign analysis and optimization decisions. All monetary values in the API are returned in micros (multiply by 0.000001 for actual currency value).

Conversion Metrics

Conversion metrics measure the business outcomes driven by your ads — purchases, leads, sign-ups, phone calls, and other valuable actions. Google Ads distinguishes between Conversions (primary conversion actions included in Smart Bidding optimization) and All Conversions (which add secondary actions, cross-device, view-through, and modeled conversions). Understanding this distinction is critical for accurate reporting.

Shopping & Product Metrics

Shopping metrics apply to Google Shopping campaigns, Performance Max with product feeds, and free product listings. These dimensions and metrics combine your Merchant Center product data with advertising performance, letting you analyze results at the product level. Essential for e-commerce advertisers optimizing their product feed and bidding.

Video & YouTube Metrics

Video metrics measure how users engage with your video ad content on YouTube and across the Google Video Partners network. From view counts and completion rates to earned actions and subscriber growth, these metrics help you understand which videos capture attention and drive downstream engagement. Critical for YouTube advertising and Demand Gen campaigns with video assets.

Quality & Auction Metrics

Quality and auction metrics measure how your ads, keywords, and landing pages compare to competitors in the same auctions. Quality Score is the most important diagnostic in Google Ads — it directly impacts your Ad Rank, ad position, actual CPC, and whether your ad shows at all. Auction insights let you benchmark against specific competitors.

Audience & Targeting Breakdowns

Audience and targeting breakdowns are segments that let you split your metrics by who saw your ads, where they saw them, and when. These are essential for understanding which audiences, devices, locations, and times drive the best performance — and for making informed bid adjustments and targeting decisions.

Device Breakdown

Network Breakdown

Location Breakdowns

Time Breakdowns

Demographic Breakdowns

Audience Segment Breakdowns

Placement Breakdowns

Conversion Action Breakdowns

Search Terms Dimensions

Performance Max Dimensions

Performance Max campaigns use a unique structure with asset groups, listing groups, and AI-driven creative combinations. While PMax provides less granular reporting than standard campaigns, Google has progressively expanded the available dimensions and metrics. These fields are essential for understanding how PMax allocates budget and which creative assets drive performance.

Asset Group Dimensions

Asset Performance Labels

Listing Group Dimensions

Extension & Asset Metrics

Extensions (now called "assets" in the Google Ads interface) add supplemental information to your ads — additional links, phone numbers, locations, callouts, and structured snippets. Tracking extension performance helps you understand which assets enhance your ads and drive incremental clicks.

Display Network-Specific Metrics

Display campaigns use a different set of delivery and engagement metrics compared to Search. These metrics measure viewability, engagement with rich media, and audience reach across millions of websites and apps in the Google Display Network.

How to Use Google Ads Metrics for Optimization

Having access to 400+ metrics is powerful, but knowing which ones matter for your specific campaign types and goals is what separates effective advertisers from data-overwhelmed ones. Here's a practical framework for selecting the right metrics at each level.

For Search campaigns

Focus on Quality Score and its three components (expected CTR, ad relevance, landing page experience) to diagnose efficiency issues. Track search impression share and search lost IS (budget vs. rank) to understand whether you're missing opportunities due to budget constraints or poor Ad Rank. Monitor top impression % and absolute top impression % for brand campaigns where position matters. Use cost per conversion and ROAS as your primary optimization KPIs.

For Shopping campaigns

Analyze at the product level using product title, brand, and custom labels to identify winners and losers. Track conversion rate and ROAS by product to prioritize bid increases for high-performers and reduce bids on underperformers. Use impression share data to identify products losing visibility to competitors. Monitor benchmark CPC to understand competitive pricing dynamics.

For Video / YouTube campaigns

Use view rate and quartile completion rates (25%, 50%, 75%, 100%) to understand where viewers drop off. A sharp drop between 25% and 50% means your message isn't sustaining interest. Track earned views and earned subscribers to measure organic amplification from paid ads. For action campaigns, conversions and cost per conversion matter more than view rate.

For Performance Max campaigns

Focus on asset group-level conversions and conversion value since PMax offers limited granularity. Use asset performance labels (Best, Good, Low, Learning) to replace underperforming assets. Monitor search themes to understand which queries trigger your PMax ads. Track listing group performance for product-level optimization. Compare PMax performance against standard campaigns by ensuring conversion tracking is consistent across both.

For cross-campaign optimization

Compare cost per conversion and ROAS across campaign types to allocate budget effectively. Use device, location, and time of day segments to identify patterns that apply across campaigns — for example, if mobile converts better on weekends across all campaigns, apply bid adjustments accordingly. Use audience segment breakdowns to understand which audiences perform best across Search, Display, and Video.

What Changed in 2025-2026

Google has made significant changes to its advertising platform over the past two years, affecting both the available data and how campaigns operate. Understanding these changes is critical for anyone working with historical data, building dashboards, or optimizing campaign strategy.

Broad match AI expansion (2025)

Google continued expanding broad match keyword coverage with AI-powered intent matching. Broad match keywords now match queries with the same implied intent even when no individual words overlap. For example, a broad match keyword "affordable housing" might match "low-cost apartments near me." This means the search terms report is more important than ever for monitoring what queries actually trigger your ads. However, search terms visibility was further restricted for low-volume queries, making negative keyword management more challenging.

Performance Max reporting improvements (2025-2026)

Google expanded PMax reporting with asset group-level performance data, asset performance labels (Best, Good, Low, Learning) for individual creative assets, and search themes showing grouped query categories that triggered your ads. Channel-level reporting was added in late 2025, allowing advertisers to see a breakdown of PMax performance across Search, Shopping, Display, YouTube, Discover, and Gmail for the first time.

Enhanced Conversions expansion (2025)

Enhanced Conversions became the default recommended setup for conversion tracking. The feature now supports Enhanced Conversions for leads (matching offline conversion data to ad interactions using hashed first-party data) and Enhanced Conversions for web (improving online conversion measurement accuracy). Google also expanded consent mode v2 integration, requiring advertisers in the EEA to implement consent mode for conversions to be modeled when user consent is not granted.

Deprecations and removals

The average position metric (deprecated in 2019) was fully removed from historical data exports in 2025 — use search top impression % and absolute top impression % instead. Expanded Text Ads can no longer be created (since June 2022) but existing ones still serve and report data. Several Smart campaign features were consolidated into Performance Max. The Similar Audiences feature was fully sunset in 2023, with Google recommending optimized targeting and audience expansion as replacements.

AI-powered features in bidding and targeting (2026)

Google introduced AI Max for Search campaigns, which automatically applies broad match behavior, dynamic search ads functionality, and auto-generated assets to standard Search campaigns. This changes how keywords are matched and which creative is served, making search term analysis and asset performance monitoring even more critical. New brand exclusions for PMax were added to prevent Performance Max from cannibalizing branded Search traffic.

Common Mistakes When Analyzing Google Ads Data

Even experienced advertisers make these mistakes when working with Google Ads metrics. Avoiding them will save you from flawed analyses and poor optimization decisions.

1. Confusing Conversions and All Conversions

Conversions only includes primary conversion actions you've opted into Smart Bidding optimization. All Conversions adds secondary actions, cross-device, view-through, and modeled conversions. Comparing ROAS based on "All Conversions Value" against a target set for "Conversions" will make performance look better than it actually is. Always check which column your reports use.

2. Ignoring search impression share data

A campaign with a 5% conversion rate and 20% impression share is leaving massive opportunity on the table. Always check search lost IS (budget) and search lost IS (rank) to understand whether you need more budget or better Quality Score. These two metrics tell you exactly where to invest optimization effort.

3. Optimizing for CTR without context

A high CTR on irrelevant queries wastes budget. A keyword with 8% CTR but 0% conversion rate is worse than one with 2% CTR and 5% conversion rate. Always analyze CTR alongside conversion rate and cost per conversion. High CTR is only valuable when it drives qualified traffic.

4. Averaging ROAS across campaigns

ROAS is a ratio — averaging it across campaigns gives mathematically incorrect results. A campaign with $100 spend and 10x ROAS ($1,000 revenue) averaged with a campaign with $10,000 spend and 2x ROAS ($20,000 revenue) gives a misleading 6x average. The actual blended ROAS is ($1,000 + $20,000) ÷ ($100 + $10,000) = 2.08x. Always recalculate from summed totals.

5. Not checking match type distribution

With broad match AI expansion, your exact match keywords may be triggering on queries you don't intend. Regularly check the search terms report and segment keyword performance by match type to ensure broad match keywords aren't cannibalizing exact match or phrase match performance with lower-intent queries.

6. Overlooking the micros format in API data

The Google Ads API returns all monetary values in micros — a cost of 1,500,000 means $1.50, not $1.5 million. Forgetting to divide by 1,000,000 when building dashboards or automations leads to absurdly wrong cost figures. The metrics.cost_micros, metrics.average_cpc, metrics.average_cpm, and all bid fields use this format.

7. Treating Quality Score as a real-time metric

Quality Score is a historical diagnostic, not a real-time auction signal. Google uses a more granular, real-time version of quality signals in each auction. The Quality Score you see in your account is updated periodically and represents an aggregate assessment. Don't make panic changes based on a Quality Score drop of 1 point — look at the component signals (expected CTR, ad relevance, landing page) and trends over time.

8. Comparing PMax and standard campaigns without controlling for overlap

Performance Max campaigns compete in the same auctions as your standard Search and Shopping campaigns. Comparing their performance side-by-side without accounting for incremental lift is misleading — PMax may be taking credit for conversions that your standard campaigns would have captured anyway. Use conversion lift experiments and check for branded search query overlap between PMax and your brand Search campaigns.

9. Using conversion data without checking the attribution model

Google Ads defaults to data-driven attribution (DDA), which distributes conversion credit across multiple touchpoints. If you compare data from an account using DDA with one using last-click attribution, the numbers won't be comparable. Always check segments.conversion_attribution_event_type to know which model applies. When switching attribution models, expect a shift in how conversions are distributed across campaigns — top-of-funnel campaigns typically gain credit under DDA while last-click overweights bottom-funnel.

10. Ignoring conversion lag in recent data

Conversions often take days or weeks to be attributed back to the original click. Looking at the last 3-7 days of conversion data and making budget decisions will undercount conversions that haven't been attributed yet. Use the segments.conversion_lag_bucket segment to understand your typical conversion lag, then exclude the most recent days from optimization decisions. For B2B accounts, conversion lag can exceed 30 days — making the last month of data unreliable for decision-making.

Google Ads API: Key GAQL Query Patterns

For developers and analysts working directly with the Google Ads API, understanding common GAQL query patterns is essential for pulling the right data. Here are the most important patterns for the dimensions and metrics covered in this guide.

Basic campaign performance query

To pull campaign-level performance with core metrics, query the campaign resource and include the metrics you need in the SELECT clause. Add a WHERE clause to filter by date range and campaign status. The ORDER BY clause lets you sort results — for example, by cost descending to see your highest-spending campaigns first.

Keyword-level query with Quality Score

For keyword analysis, query the keyword_view resource which joins keyword dimensions with their performance metrics. Include ad_group_criterion.quality_info.quality_score along with the three component scores. Note that Quality Score is only populated for keywords with sufficient impression volume — low-traffic keywords may return null values.

Cross-segment queries

When you add segments like segments.device or segments.ad_network_type to a query, the results are automatically broken down by those segments. This means a campaign that previously returned one row will now return multiple rows — one per segment value. Be aware that some segment combinations are incompatible: the API will return an error if you try to combine segments that cannot be queried together (e.g., certain conversion segments with certain resource types).

Important API limitations

The Google Ads API has several limitations to be aware of. You cannot SELECT fields from incompatible resources in the same query — for example, you cannot get keyword text and campaign budget in a single query from the keyword_view resource. Some metrics like impression share are approximate and may show "--" when the data sample is too small (below the 10% threshold). Historical Quality Score data is only available for dates after the feature was introduced and may have gaps for keywords with insufficient traffic.

Rate limits also apply: the API allows 10,000 operations per day for most developer tokens, and complex queries against large accounts may time out. Use the PARAMETERS clause to set include_drafts and other parameters that affect query scope and performance.