Outbrain is one of the leading native advertising platforms, delivering content recommendations across premium publisher sites to drive discovery, engagement, and conversions. Whether you're running content amplification campaigns, driving qualified traffic, or optimizing for conversions, understanding every available dimension and metric is essential for maximizing your native advertising ROI.
This guide provides a complete reference of every dimension and metric available in Outbrain as of 2026. We've organized them by category, explained what each one measures, and included practical guidance on how to use them for campaign reporting and optimization.
What Are Outbrain Dimensions vs Metrics?
Before exploring the full reference, it's important to clarify the difference between dimensions and metrics in Outbrain — two categories that serve fundamentally different purposes in advertising data.
Dimensions are descriptive attributes that identify and categorize your data. They are the labels that let you organize, filter, and segment reports. Examples include campaign name, content title, publisher section, country, and device type. Dimensions answer the question: "How do I want to slice this data?"
Metrics are quantitative measurements that tell you how your campaigns performed. They are numbers: impressions, clicks, CTR, CPC, spend, conversions, and CPA. Metrics answer the question: "What happened with my campaigns?"
In Outbrain's Amplify API, dimensions are specified through the groupBy parameter, while metrics are selected through specific field parameters. The Amplify dashboard provides a visual interface for building reports with both.
How Is Outbrain Data Structured?
Outbrain data follows a hierarchy of Account (Marketer) > Campaign > Promoted Content (Ad). The marketer account holds all campaigns. Campaigns define targeting, budget, and bidding strategy. Promoted content items are the individual ads — each with a title, image, and destination URL. Performance data can be queried at any level and segmented by publisher section, geography, device, and other dimensions.
Outbrain's data model also includes sections — specific areas within publisher sites. A single publisher may have multiple sections (e.g., CNN Homepage, CNN Politics, CNN Business), each with different audience profiles and performance characteristics. Section-level reporting is one of Outbrain's most granular and useful dimensions for optimization.
Campaign Dimensions
Campaign-level dimensions define the structure and configuration of your Outbrain advertising. These fields identify the campaign and its settings — objective, budget, targeting, and bid strategy.
| Dimension | API Field | Description |
|---|---|---|
| Campaign ID | campaignId | Unique identifier for the campaign |
| Campaign Name | name | Name of the campaign as defined by the advertiser |
| Campaign Status | enabled | Whether the campaign is active (true/false) combined with approval status |
| Campaign Objective | objective | Campaign goal: TRAFFIC, CONVERSIONS, AWARENESS, APP_INSTALLS, VIDEO_VIEWS, LEAD_GENERATION |
| Budget | budget | Campaign budget configuration (daily or total) |
| Budget Type | budgetType | Budget model: DAILY or LIFETIME |
| Daily Budget | dailyBudget | Maximum daily spend in account currency |
| Total Budget | totalBudget | Total campaign spend cap for lifetime-budget campaigns |
| Bid Strategy | bidStrategy | Bidding approach: CPC (fixed), CBS (Conversion Bid Strategy), SEMI_AUTOMATIC, FULLY_AUTOMATIC |
| CPC Bid | cpc | Maximum or target cost per click in account currency |
| Target CPA | targetCPA | Target cost per acquisition for CBS campaigns |
| Start Date | startDate | Campaign start date |
| End Date | endDate | Campaign end date (if set) |
| Targeting - Countries | targeting.countries | Targeted countries by ISO code |
| Targeting - Platforms | targeting.platforms | Targeted platforms: DESKTOP, MOBILE, TABLET |
| Targeting - Interests | targeting.interests | Interest-based audience segments targeted by the campaign |
| Targeting - Lookalike | targeting.lookalikeAudiences | Lookalike audience segments based on conversion data |
| Created Date | creationTime | Timestamp when the campaign was created |
| Last Modified | lastModified | Timestamp of the last change to campaign settings |
Content (Ad) Dimensions
Content dimensions describe the individual promoted content items within a campaign. Each item consists of a title, image, and destination URL — the creative elements that appear in publisher recommendation widgets. These fields are essential for creative performance analysis.
| Dimension | API Field | Description |
|---|---|---|
| Content ID | id | Unique identifier for the promoted content item |
| Content Title | text | Headline text of the promoted content shown in recommendation widgets |
| Landing Page URL | url | Destination URL the content links to |
| Image URL | imageUrl | URL of the thumbnail image for the promoted content |
| Content Status | enabled | Whether the content item is active combined with approval state |
| Approval Status | approvalStatus | Content review state: APPROVED, PENDING, REJECTED |
| Rejection Reason | rejectionReasons | Why the content was rejected (if applicable): policy violations, image quality, misleading text |
| Content Type | contentType | Format: LINK, VIDEO, APP_INSTALL, CAROUSEL |
| Brand Name | siteName | Advertiser brand name displayed alongside the content |
| CTA Text | callToAction | Call-to-action button text: Read More, Learn More, Shop Now, Download, Sign Up |
| Description | description | Optional description text shown below the title in supported placements |
Section Dimensions
Sections are one of Outbrain's most unique and valuable dimensions. A section represents a specific area within a publisher site — for example, the homepage widget, the technology section, or the lifestyle section. Section-level reporting lets you optimize placement strategy with more precision than site-level analysis alone.
| Dimension | API Field | Description |
|---|---|---|
| Section ID | sectionId | Unique identifier for the publisher section |
| Section Name | sectionName | Name of the section (e.g., "CNN - Homepage", "BBC - Sports") |
| Publisher Name | publisherName | Parent publisher site name |
| Publisher ID | publisherId | Unique identifier for the publisher |
| Section Category | sectionCategory | Content category of the section: News, Entertainment, Sports, Business, Technology, Lifestyle, etc. |
| Section URL | sectionUrl | URL pattern of the publisher section |
| Block/Include Status | sectionBlocked | Whether the section is on the campaign's block list or inclusion list |
Core Performance Metrics
Core performance metrics measure the fundamental delivery and cost efficiency of your Outbrain campaigns. These are the baseline metrics every advertiser should track to understand campaign reach, engagement, and cost.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Impressions | impressions | Total number of times your content was displayed in recommendation widgets | Counts every display, including below-fold placements the user may not have seen |
| Clicks | clicks | Total clicks on your promoted content | Clicks on the title, image, or CTA that redirect to your landing page |
| CTR | ctr | Click-through rate | (Clicks ÷ Impressions) × 100. Native ad benchmarks: 0.3-0.8% |
| CPC | cpc | Average cost per click | Spend ÷ Clicks. Actual CPC may differ from bid CPC due to auction dynamics |
| Spend | spend | Total amount spent in account currency | Actual expenditure after auction and bid strategy adjustments |
| CPM | cpm | Cost per 1,000 impressions | (Spend ÷ Impressions) × 1,000 |
| Daily Average Spend | averageDailySpend | Average daily expenditure over the selected period | Total Spend ÷ Number of active days |
| Budget Pacing | budgetUtilization | Percentage of allocated budget actually spent | Low pacing indicates targeting is too narrow or bids too low |
Conversion Metrics
Conversion metrics measure the business outcomes from your Outbrain campaigns — tracked through the Outbrain Pixel installed on your website. These metrics are critical for campaigns optimized toward performance goals like purchases, signups, or lead generation.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Conversions | conversions | Total number of conversion events tracked by the Outbrain Pixel | Sum of all defined conversion events within the attribution window |
| CPA | cpa | Cost per acquisition (conversion) | Spend ÷ Conversions |
| Conversion Rate | conversionRate | Percentage of clicks that resulted in a conversion | (Conversions ÷ Clicks) × 100 |
| Conversion Value | conversionValue | Total monetary value of all conversions | Revenue values passed through the pixel conversion event |
| ROAS | roas | Return on ad spend | Conversion Value ÷ Spend |
| Revenue Per Conversion | revenuePerConversion | Average value per conversion event | Conversion Value ÷ Conversions |
| View-Through Conversions | viewThroughConversions | Conversions from users who saw the ad but did not click | Default attribution window: 1 day after ad view |
| Click-Through Conversions | clickThroughConversions | Conversions from users who clicked the ad | Default attribution window: 30 days after click |
| Conversions by Event | conversionsByEvent | Conversion count broken down by each defined conversion event | Separate counts for purchases, signups, page views, etc. |
Engagement Metrics
Engagement metrics measure what happens after the click — how deeply users interact with your landing page and website. These post-click metrics are essential for evaluating traffic quality and ensuring your campaigns drive meaningful user behavior, not just empty clicks.
| Metric | Description |
|---|---|
| Bounce Rate | Percentage of sessions where the user viewed only the landing page and left without any further interaction |
| Page Views Per Session | Average number of pages viewed per visit from Outbrain traffic |
| Average Session Duration | Average time spent on the website per visit from Outbrain (in seconds) |
| Engaged Clicks | Clicks that resulted in at least 2 page views or 30+ seconds on site |
| Engaged Click Rate | Percentage of total clicks classified as engaged |
| Cost Per Engaged Click | Average cost per click that resulted in meaningful engagement |
| Scroll Depth | Average percentage of the landing page scrolled through by visitors |
| Content Consumption Rate | Percentage of visitors who consumed at least 75% of the landing page content |
Why post-click metrics matter: Native advertising competes with editorial content. A compelling headline can drive clicks, but if visitors immediately bounce, the traffic adds no business value. Outbrain's algorithm also uses engagement signals to determine content quality — campaigns with high engagement rates tend to receive better placement and lower CPCs over time.
Publisher Breakdowns
Publisher breakdowns reveal how your campaigns perform across different websites and sections in the Outbrain network. This data is critical for placement optimization — identifying premium sites that drive conversions and blocking underperforming sites that waste budget.
| Dimension | Description |
|---|---|
| Publisher Site | Top-level publisher domain where the ad was shown (e.g., cnn.com, bbc.com, msn.com) |
| Publisher Section | Specific page or section within the publisher site (e.g., Homepage, Sports, Technology) |
| Publisher Category | Content category of the publisher: News, Entertainment, Sports, Finance, Lifestyle, Technology |
| Publisher Tier | Quality tier classification: Premium, Standard, or Long-Tail publishers |
| Placement Position | Where the widget appears on the page: below-article, mid-article, sidebar, homepage feed |
| Widget Type | Format of the recommendation widget: standard grid, feed-style, video widget |
| Per-Publisher Metrics | All core and conversion metrics available per publisher: impressions, clicks, CTR, CPC, spend, conversions, CPA |
Audience Breakdowns
Audience breakdowns let you segment any metric by user characteristics — where they are located, what device they use, and what interests they have. These dimensions are essential for understanding who your content resonates with and optimizing targeting for maximum performance.
Geographic Breakdown
| Dimension | Description |
|---|---|
| Country | Country of the user viewing the ad (based on IP geolocation) |
| Region / State | State or administrative region within the country |
| Metro / DMA | Metropolitan area or Designated Market Area (US markets) |
| City | City-level geolocation (available in select markets) |
Device and Technology Breakdown
| Dimension | Description |
|---|---|
| Device Type | Device category: Desktop, Mobile, Tablet |
| Operating System | OS of the user's device: Windows, macOS, iOS, Android, Linux, ChromeOS |
| OS Version | Specific version of the operating system |
| Browser | Web browser: Chrome, Safari, Firefox, Edge, Samsung Internet, Opera |
| Browser Version | Specific version of the web browser |
| Connection Type | Network connection: WiFi, Cellular, Broadband |
Interest Segment Breakdown
| Dimension | Description |
|---|---|
| Interest Category | User interest segment based on browsing behavior: Technology, Finance, Travel, Health, Sports, Entertainment, Fashion, etc. |
| Interest Sub-Category | More granular interest classification within a parent category |
| Custom Audience | Advertiser-defined audience segments based on pixel data, CRM uploads, or lookalike modeling |
| Lookalike Segment | Audience segment modeled to resemble high-value converters from your campaigns |
How to Use These Metrics for Campaign Optimization
Effective Outbrain optimization requires aligning your metrics with your campaign objectives. Here's a practical framework for selecting the right metrics at each optimization stage.
For content amplification campaigns
Focus on impressions, CTR, and CPC. Compare CTR across different content titles and thumbnails to identify which creative combinations resonate most with publisher audiences. Track engagement metrics (bounce rate, session duration, page views per session) to ensure clicks translate into actual content consumption. Use section-level reporting to find premium placements where your content gets the highest read rates.
For conversion-focused campaigns
Prioritize CPA, conversion rate, and ROAS. Break down conversions by publisher section to identify which placements drive the best conversion rates — section-level optimization is often more impactful than campaign-level bid changes. Monitor CBS performance if using Conversion Bid Strategy — check that actual CPA is trending toward your target and that the algorithm has enough conversion volume to optimize effectively.
For creative testing
Compare CTR and conversion rate across promoted content items with different titles and images. Allow at least 1,000-2,000 impressions per variation before drawing conclusions. Track bounce rate per content item — a high-CTR title with a high bounce rate indicates the headline creates incorrect expectations. The best-performing creative balances click appeal with landing page relevance.
For publisher optimization
Use the section-level breakdown to identify your top-performing placements. Sort by CPA or engaged click rate rather than CTR — some sections generate high click volumes but poor post-click quality. Build section block lists for placements with consistently high CPAs and create section inclusion campaigns targeting only your best-performing sections. Review section performance weekly, as publisher site quality can shift with content cycles.
For audience optimization
Break down performance by device type, country, and interest segment. Mobile and desktop users often show different conversion patterns — consider separate campaigns with different bids for each. Use interest segment data to refine targeting over time, expanding into high-performing segments and excluding low-performers. Compare geographic CPA to identify countries or regions where your offer converts most efficiently.
Outbrain vs Taboola: Metric Comparison
Since Outbrain and Taboola are the two leading native advertising platforms, understanding how their metrics compare is essential for cross-platform reporting and budget allocation.
Equivalent metrics
Most core metrics map directly between the two platforms: impressions, clicks, CTR, CPC, spend, conversions, CPA, and ROAS mean the same thing and are calculated the same way. The primary difference is in naming conventions — Outbrain uses "promoted content" while Taboola uses "campaign items"; Outbrain uses "sections" while Taboola uses "sites" as the primary publisher dimension.
Key differences
Taboola provides visible impressions and viewability rate as standard metrics, while Outbrain's viewability data is less prominently surfaced. Outbrain's section-level granularity is more detailed than Taboola's site-level reporting. Taboola's Smart Bid metrics (multiplier, predicted conversion rate) are more transparent than Outbrain's CBS internals. Both platforms offer similar engagement metrics but may calculate bounce rate slightly differently based on session definitions.
Common Mistakes When Analyzing Outbrain Data
Avoid these frequent errors that lead to suboptimal native advertising decisions.
1. Optimizing only at the campaign level
Campaign-level metrics hide huge performance variation across publisher sections. A campaign with a $10 average CPA might have sections converting at $3 and sections converting at $50. Always drill down to section-level reporting to identify and act on these disparities. Block underperforming sections and increase exposure on high-performing ones.
2. Ignoring engagement quality metrics
In native advertising, a click is not inherently valuable. If 60% of clicks result in immediate bounces, you're paying for traffic that adds no business value. Monitor bounce rate, session duration, and engaged click rate alongside CTR and CPC. Optimize toward engaged clicks rather than total clicks for better campaign economics.
3. Changing bids during CBS learning phase
Outbrain's Conversion Bid Strategy needs sufficient conversion volume (30-50 per week) to optimize bids effectively. Making bid changes, budget adjustments, or targeting changes during the learning phase resets the algorithm. Allow at least 1-2 weeks of stable data before evaluating CBS performance. If conversion volume is too low, use a higher-funnel event as the optimization target.
4. Comparing CTR benchmarks across platforms
Native ad CTR on Outbrain (typically 0.3-0.8%) is not comparable to social media ad CTR (1-3%) or search ad CTR (3-10%). Each format has fundamentally different user intent and interaction patterns. Benchmark your Outbrain CTR against other native advertising campaigns, not against your Facebook or Google Ads performance.
5. Not testing enough creative variations
Title and thumbnail combinations have enormous impact on native ad performance. A slight headline change can double CTR. Run at least 3-5 title variations and 2-3 thumbnail variations per campaign. Let each variation accumulate sufficient impressions (1,000+) before pausing underperformers. Continuously refresh creative to combat audience fatigue — native ad performance typically declines after 2-4 weeks with the same creative.
6. Treating view-through conversions equally to click-through conversions
View-through conversions occur when someone sees your ad, doesn't click, but later converts on your website. While these have value, they are inherently lower-confidence attributions than click-through conversions. Separate click-through conversions from view-through conversions in your reporting and weight them differently in ROAS calculations. Consider shortening the view-through window to 1 day for more conservative attribution.
