Google released version 23 of the Google Ads API on January 28, 2026, marking the first update of the year and signaling a significant shift in the platform’s development approach. This release introduces enhanced Performance Max transparency through ad network type breakdowns, AI-powered natural language audience building, granular invoice data at the campaign level, and precise datetime scheduling capabilities that replace legacy date-only fields.
The v23 release represents Google’s commitment to a faster monthly release cadence throughout 2026, enabling developers and advertisers to access new capabilities more rapidly than the previous quarterly update cycle. With Google Ads API v19 sunsetting on February 11, 2026, understanding the v23 features and planning migration strategies has become a critical priority for development teams managing advertising automation.
This comprehensive guide examines every major feature introduced in Google Ads API v23, provides technical implementation details, outlines migration requirements, and offers strategic recommendations for leveraging these capabilities to improve campaign performance and operational efficiency.
Understanding the Faster Release Cadence and What It Means for Developers
Beginning with v23, Google has transitioned from quarterly API releases to a monthly cadence throughout 2026. This accelerated schedule fundamentally changes how development teams must approach API maintenance, testing, and feature adoption.
The Impact of Monthly Releases
The shift to monthly releases provides several advantages for the advertising ecosystem. New features reach production environments faster, reducing the lag between platform capabilities in the Google Ads UI and programmatic access through the API. Bug fixes and performance improvements deploy more frequently, allowing developers to address issues without waiting months for the next major version.
However, this faster cadence also introduces new challenges for development teams. Testing cycles must compress to accommodate monthly updates rather than quarterly ones. Version deprecation timelines may accelerate, requiring more frequent migration planning. Development resources need allocation for ongoing API maintenance rather than periodic major upgrades.
Organizations using the Google Ads API should establish continuous integration practices that accommodate this new rhythm. Automated testing frameworks become essential for validating new versions quickly. Monitoring systems should track API version usage across all production systems to identify deprecation risks early. Development roadmaps must include regular time allocations for API upgrades rather than treating them as occasional projects.
Current Version Lifecycle and Sunset Schedule
As of January 2026, the Google Ads API maintains multiple active versions with staggered deprecation dates. Understanding this lifecycle helps teams plan migration timelines and avoid service disruptions.
Google Ads API v19 reaches end-of-life on February 11, 2026, requiring immediate attention from any teams still operating on this version. After the sunset date, all requests to v19 endpoints will fail, causing campaign management disruptions for unprepared organizations.
Versions v20 through v22 remain supported through mid-to-late 2026, though specific sunset dates will be announced as newer versions release. Version v23, as the current release, will maintain support through approximately January 2027 based on Google’s typical 12-month support window.
Development teams should audit their current API version usage immediately to identify any v19 dependencies and prioritize migration work accordingly.
Performance Max Campaign Transparency: Ad Network Type Breakdowns
One of the most significant enhancements in Google Ads API v23 addresses a long-standing complaint about Performance Max campaigns: the lack of visibility into which advertising networks drive results. Prior to v23, Performance Max reported aggregate metrics without attribution to specific surfaces like Search, YouTube, Display, or Discover.
Technical Implementation of Network Breakdowns
The v23 release enables segmentation by ad network type within Performance Max campaign queries. Developers can now request performance data broken down by the specific Google advertising network where ads appeared.
When querying Performance Max campaign metrics through the GoogleAdsService, adding the segments.ad_network_type
- SEARCH: Google Search and search partner sites
- YOUTUBE_SEARCH: YouTube search results
- YOUTUBE_WATCH: YouTube video watch pages
- DISPLAY: Google Display Network
- DISCOVERY: Google Discover feed
Each network segment returns the full range of performance metrics including impressions, clicks, conversions, conversion value, cost, and derived metrics like click-through rate and cost per conversion. This granular visibility enables performance analysis previously impossible with Performance Max campaigns.
Strategic Applications of Network-Level Data
The ability to segment Performance Max performance by network unlocks several strategic capabilities that were previously unavailable to advertisers.
Budget allocation decisions become more informed when campaign managers understand which networks generate the highest return on ad spend. If data reveals that YouTube Watch placements drive significantly higher conversion rates than Display Network placements, that insight influences creative strategy, asset selection, and potentially campaign structure decisions.
Cross-campaign analysis improves when advertisers can compare Performance Max results by network against dedicated Search, YouTube, or Display campaigns. This comparison reveals whether Performance Max provides incremental reach and conversions or simply cannibalizes existing campaign performance on specific networks.
Asset performance optimization gains new dimensions when network data combines with asset-level reporting. Analyzing which image assets perform best on Display Network versus which video assets excel on YouTube enables more targeted creative development and asset group construction.
Competitive intelligence becomes possible when network breakdowns reveal unexpected performance patterns. Discovering that a Performance Max campaign drives strong Search network results despite minimal Search-focused assets suggests strong brand demand that might warrant dedicated Search campaigns to capture additional volume.
Limitations and Considerations
While network-type breakdowns provide valuable visibility, advertisers should understand the limitations of this data and avoid over-interpreting results.
Google’s algorithm still controls budget allocation between networks automatically within Performance Max campaigns. Network performance data reveals outcomes but does not enable direct budget control by network. Strong performance on one network does not guarantee that shifting budget toward that network (even indirectly through campaign settings) will improve overall results, as the algorithm may already be optimizing toward the best-performing opportunities.
Attribution complexities remain present in Performance Max campaigns. A conversion attributed to Display Network in the data may have resulted from earlier touchpoints on Search or YouTube. The network breakdown shows where the final interaction occurred but does not capture the full customer journey across networks.
Comparison between Performance Max network segments and dedicated network campaigns requires careful methodology. Performance Max campaigns target different auction dynamics, use different bidding strategies, and compete in different inventory spaces compared to dedicated Search or Display campaigns, making direct performance comparisons potentially misleading.
AI-Powered Audience Building with Natural Language Processing
Google Ads API v23 introduces a capability that represents a significant evolution in audience targeting: the ability to generate structured audience definitions from natural language descriptions using generative AI.
The GenerateAudienceDefinition Method
The new AudienceInsightsService.
The method accepts several input parameters that guide the AI’s interpretation. The core parameter, audience_, takes a natural language string describing the desired audience characteristics. Supporting parameters include customer_id for account context, country_code for market-specific audience matching, and optional language_code for description language.
The API processes the natural language description through Google’s language models to extract targeting intent. The system identifies demographic signals (age, gender, parental status, household income), interest and affinity categories, behavioral indicators (in-market audiences, life events), and geographic targeting suggestions embedded in the description.
The response provides a structured audience definition containing Google Ads targeting parameters that match the description’s intent. This includes relevant audience segment IDs, demographic targeting recommendations, interest category suggestions, and confidence scores indicating how well each recommendation matches the original description.
Practical Use Cases and Implementation Strategies
The natural language audience generation capability streamlines workflows that previously required extensive manual configuration and platform expertise.
Campaign planning accelerates when marketing teams can articulate target audiences in business language rather than learning Google Ads’ technical taxonomy. A description like “health-conscious millennials interested in sustainable living and organic products” automatically translates into appropriate affinity audiences, in-market categories, and demographic targeting without requiring manual navigation through hundreds of audience options.
Testing and experimentation become more accessible when generating multiple audience variations from slightly different descriptions takes seconds rather than minutes. Teams can rapidly create A/B tests comparing “eco-conscious parents shopping for children’s products” against “environmentally aware families interested in sustainable kids’ brands” to determine which framing produces better audience match.
Client communication improves when agency teams can discuss audiences in natural business language during strategy sessions and then automatically generate technical implementations. The ability to translate “We want to reach small business owners interested in efficiency tools who search for productivity software” directly into targeting parameters eliminates translation errors between strategy and execution.
Documentation and knowledge management benefit when audience strategies store as human-readable descriptions alongside technical configurations. Future team members can understand targeting intent without decoding complex combinations of audience IDs and parameters.
Limitations and Quality Considerations
While the natural language audience generation represents a powerful capability, users should approach it with realistic expectations and appropriate validation practices.
The AI model interprets descriptions based on available audience segments within Google Ads. If a description includes targeting criteria not represented by existing audience segments, the system approximates with the closest available options or omits unsupported elements. Users should validate that generated audience definitions actually match their intent rather than assuming perfect translation.
Description specificity significantly impacts output quality. Vague descriptions like “people who might buy our product” produce generic audience suggestions. Detailed descriptions including demographics, interests, behaviors, and contextual information produce more precise and actionable audience configurations.
Market and language variations affect interpretation accuracy. The system’s training data and audience segment availability vary by country and language. Descriptions that work well for US English audiences may produce less accurate results for other markets where audience segment coverage differs.
The technology augments rather than replaces human expertise. Generated audiences should undergo review by experienced practitioners who can evaluate whether the technical implementation truly matches strategic intent and campaign goals.
Precision Campaign Scheduling with DateTime Fields
Google Ads API v23 replaces the legacy date-only campaign scheduling fields with new datetime fields that enable minute-precision timing for campaign start and end times.
Technical Changes in Campaign Timing
Previous API versions used Campaign.start_date and C fields accepting date values in YYYY-MM-DD format. These fields scheduled campaigns to start at midnight and end at midnight in the account’s time zone, providing only day-level precision.
Version 23 introduces Campaign.start_ and Campaign.end_ fields accepting full datetime values in ISO 8601 format with time zone information. These fields support scheduling campaigns to start and end at specific times rather than only at day boundaries.
The datetime fields accept values like 2026-02-14T12:00:00-05:002026-03-01T23:59:59+00:00
This change applies to specific campaign types initially, with gradual expansion to additional campaign types in future releases. Development teams should consult the v23 release notes for the complete list of supported campaign types and check for updates in subsequent versions.
Strategic Applications for Precise Timing
The ability to schedule campaigns with minute precision enables several time-sensitive advertising strategies that were previously difficult or impossible to execute programmatically.
Flash sale coordination becomes reliable when campaigns can launch exactly when promotional pricing activates and end precisely when deals expire. A campaign can start at 12:00:00 PM when inventory becomes available and end at 11:59:59 PM when the sale concludes, ensuring ad spend aligns perfectly with actual offer availability.
Global campaign synchronization becomes practical when datetime fields include explicit time zone information. A worldwide product launch campaign can start at 9:00 AM local time across all markets by setting the appropriate datetime with time zone offset for each regional campaign, ensuring consistent timing despite time zone differences.
Event-based advertising gains precision when campaigns align with scheduled events. A campaign promoting a live webinar can start 24 hours before the event, intensify in the final hours, and end exactly when the webinar begins, matching advertising pressure to registration deadlines and event timing.
Competitive timing strategies become executable when campaigns can launch and pause at specific moments. Responding to competitor promotions, adjusting for known traffic patterns, or coordinating with external events requires the timing precision that datetime scheduling provides.
Migration Considerations for Existing Date Fields
Development teams must understand how the transition from date to datetime fields affects existing code and campaign management practices.
The legacy start_date and end_date
Code that reads campaign timing must handle both legacy date fields and new datetime fields during the transition period. Defensive coding practices should check which fields contain data and interpret them appropriately.
Campaign creation code should transition to datetime fields, using midnight timestamps for campaigns that don’t require specific start times. Setting start_date_time to 202 in the account time zone produces equivalent behavior to the legacy date-only field while preparing code for future datetime requirements.
Error handling should account for the new validation rules associated with datetime fields. Campaigns using total budget settings must now specify end datetime rather than just end date, as the API requires a specific endpoint for budget pacing calculations.
Enhanced Billing Transparency with Granular Invoice Details
The InvoiceService in Google Ads API v23 introduces significantly enhanced invoice detail retrieval, providing campaign-level cost breakdowns, itemized regulatory fees, and adjustment information that were previously unavailable through programmatic access.
New Invoice Detail Capabilities
The InvoiceService. method now accepts an optional parameter include_granular_ that, when set to true, returns expanded invoice data in the response.
Campaign-level cost mapping represents the most significant enhancement. Each invoice now includes line items breaking down costs by individual campaign, enabling precise allocation of spending across campaigns without requiring separate query aggregation. This granularity matches what Google Ads UI users see in billing reports but makes it programmatically accessible for automated financial systems.
Regulatory fee itemization provides detailed breakdowns of fees required by government regulations in various markets. Rather than showing a single line for regulatory costs, the detailed invoice data separates fees by type and jurisdiction, improving compliance reporting and financial transparency.
Adjustment tracking captures credits, refunds, and billing corrections at a granular level. The expanded invoice data includes adjustment line items showing the campaign or service affected, the adjustment reason, and the financial impact, enabling more accurate reconciliation between billed amounts and actual campaign spending.
Implications for Agencies and Multi-Account Management
The enhanced invoice detail capabilities address pain points particularly acute for agencies and organizations managing multiple Google Ads accounts.
Client billing processes simplify when invoice data maps directly to campaign costs without requiring manual aggregation. Agencies can programmatically extract campaign-level costs from invoices and map them to client accounts, eliminating the time-consuming manual process of allocating monthly bills across client portfolios.
Financial reconciliation improves when regulatory fees and adjustments contain sufficient detail for accounting system requirements. The granular data enables automatic matching between Google Ads invoices and internal financial records, reducing the manual review required for each billing cycle.
Budget tracking becomes more accurate when campaign costs include all associated fees and adjustments. Organizations can build automated budget monitoring systems that consume invoice data and compare actual spending against budgets at the campaign level, generating alerts when campaigns approach budget limits.
Tax and compliance reporting benefits from detailed regulatory fee information. Organizations operating across multiple jurisdictions can extract fee data specific to each market, supporting VAT/GST compliance, regulatory reporting requirements, and financial audits without manual data compilation.
Demand Gen Campaign Enhancements
While Performance Max received the headline features in v23, Demand Gen campaigns also gained significant new capabilities affecting both planning and reporting.
Surface-Specific Conversion Rate Forecasting
The ReachPlanService. method now includes surface-level granularity in its response data. Rather than providing a single conversion rate forecast for Demand Gen campaigns, the service returns differentiated forecasts for Gmail, YouTube Shorts, Discover feed, and other Demand Gen surfaces.
This enhancement addresses the reality that conversion rates vary substantially across surfaces. YouTube Shorts typically drives different user behavior compared to Gmail sponsored promotions or Discover feed placements. Surface-specific forecasts enable more accurate campaign planning and budget allocation when setting up new Demand Gen initiatives.
Advertisers can use surface-specific conversion rate data to inform asset creation strategy. If forecasts indicate significantly higher conversion rates on YouTube Shorts compared to Gmail for a particular audience and offer combination, that insight suggests prioritizing video asset development for optimal campaign performance.
Budget allocation decisions benefit from understanding expected conversion rate differences across surfaces. While advertisers cannot directly control budget distribution between surfaces in Demand Gen campaigns, knowing where the algorithm will likely find the best performance informs overall budget setting and performance expectations.
Asset Automation Capabilities
Version 23 introduces new asset automation types for Demand Gen campaigns that leverage AI to generate creative variations automatically.
The GENERATE_DESIGN_VERSIONS_ automation type creates design variations from uploaded image assets by adding design elements, incorporating text overlays, and generating additional aspect ratios. This automation helps Demand Gen campaigns maintain creative freshness across placements without requiring manual design work for every variation.
The GENERATE_VIDEOS_FROM_ automation type produces video assets by combining existing images, text assets, and other creative elements. The generated videos can serve as new assets within Demand Gen campaigns or convert to Demand Gen Video Responsive Ads, expanding campaign reach to video inventory without requiring video production resources.
These automation capabilities are enabled by default for new Demand Gen Multi Asset Ads, reflecting Google’s strategic push toward AI-powered creative optimization. Advertisers who prefer maintaining full creative control can opt out through campaign settings, though Google’s recommendation favors enabling automation for maximum campaign flexibility.
Shopping Performance Enhancements
Google Ads API v23 extends competitive metrics and conversion-date reporting to Shopping campaigns, addressing gaps in programmatic reporting capabilities.
Competitive Metrics for Shopping Performance View
The ShoppingPerformanceView resource now supports competitive impression share metrics that previously required UI access or custom report downloads. Available metrics include:
Search budget lost impression share reveals the percentage of potential impressions lost due to insufficient daily budget. This metric helps identify when Shopping campaigns constrain performance through budget limitations rather than bid strategy or product competitiveness.
Search rank lost impression share shows the percentage of potential impressions lost because product bids were too low relative to competition. This metric distinguishes budget constraints from competitiveness issues, enabling targeted optimization responses.
Search budget lost absolute top impression share and search rank lost absolute top impression share provide similar insights specifically for absolute top-of-page placements, where Shopping ads receive maximum visibility and typically higher conversion rates.
These competitive metrics enable automated optimization scripts that adjust budgets or bid strategies based on opportunity signals. A script might automatically increase campaign budgets when budget lost impression share exceeds a threshold, or raise bid adjustments when rank lost impression share indicates competitiveness issues.
Conversion Date Segmentation
ShoppingPerformanceView now supports metrics segmented by conversion date rather than only click date. This includes conversions by conversion date, conversion value by conversion date, and derived metrics like value per conversion calculated using conversion-date attribution.
Conversion date segmentation provides more accurate revenue reporting for organizations that measure performance based on when sales occur rather than when clicks happen. This alignment improves coordination between Google Ads reporting and internal sales tracking systems.
Month-over-month and year-over-year comparisons become more meaningful when conversion metrics align to the periods when conversions actually occurred. Click-date attribution can show misleading trends when conversion delays vary seasonally, while conversion-date metrics reflect actual performance timing.
Financial reconciliation improves when Google Ads conversion data matches the timing of actual transactions in e-commerce platforms and payment processors. Organizations can build automated reporting that directly compares Google Ads conversion value by conversion date against platform transaction totals without manual adjustment.
Incentives Service for Partner Integrations
A significant addition for Google’s partner ecosystem comes through the new IncentiveService, enabling programmatic management of Google Ads promotional credits and incentives.
Fetching and Applying Incentives
The IncentiveService. method allows partners to programmatically retrieve available promotional offers for users based on country, language, and optionally the user’s email address. This supports personalized “Choose Your Own” incentive programs where users select from multiple promotional options.
The IncentiveService. method enables programmatic application of selected incentives to Google Ads customer accounts, automating a process that previously required manual UI interactions or support team involvement.
These capabilities primarily benefit Google’s reseller partners, agencies with white-label offerings, and third-party platforms that integrate Google Ads account creation. The programmatic incentive workflow improves user experience during account setup and onboarding by automatically presenting and applying available promotional credits.
Applied Incentive Tracking
The new AppliedIncentive resource provides queryable information about incentives already redeemed on an account. This resource surfaces through standard GoogleAdsService search queries and includes data about incentive status, fulfillment progress, reward amounts, and relevant dates.
Programmatic access to incentive status enables automated reporting for partners managing large numbers of accounts. Rather than manually checking incentive status for each client account, partners can build dashboards that query incentive data across their portfolio and identify accounts approaching incentive expiration or milestone thresholds.
Customer communication improves when systems can automatically notify users about incentive status, remaining credit balances, and actions needed to maximize promotional value. Integration with CRM systems or customer portals becomes feasible with API access to incentive data.
Video Campaign Updates
Google Ads API v23 introduces several enhancements for video campaigns, particularly around asset controls and performance measurement.
Video Asset Feature Controls
The new AdVideoAssetInfo.ad_video_ field enables advertisers to specify which video ad features and formats the Google Ads system can apply to video assets. This addresses advertiser concerns about maintaining brand consistency and creative control while leveraging automated video capabilities.
Feature controls allow specification of whether video assets can be automatically cropped to different aspect ratios, whether the system can generate thumbnail variations, and which video ad formats can utilize the asset. These controls provide a middle ground between full automation and complete manual control, letting advertisers define boundaries for algorithmic creative optimization.
Audio Ad Audibility Metrics
Version 23 introduces audibility metrics for audio ads on YouTube, providing data about whether ads were audible and on how many impressions audibility could be measured. These metrics address the reality that not all audio ad impressions deliver sound due to user device settings, platform features, or user behavior.
Audibility measurement enables more accurate campaign evaluation for audio-focused creative. An audio ad with strong creative messaging may show low conversion rates not because the creative is ineffective but because a significant percentage of impressions delivered without sound. Audibility metrics distinguish creative quality issues from delivery environment issues.
Performance optimization can account for audibility when evaluating audio creative performance. Low-audibility placements might justify different bidding strategies or creative approaches compared to high-audibility environments where audio messaging reaches users effectively.
Life Event Targeting in Audience Insights
The addition of LIFE_EVENT_USER_INTEREST as a dimension in audience insights methods expands targeting capabilities for campaigns focused on significant life moments.
Life Event Dimension Capabilities
Life event targeting identifies users experiencing major life changes such as purchasing a home, getting married, graduating from college, having a baby, moving, or changing jobs. These moments often correlate with significant purchase intent across multiple product and service categories.
The new dimension integrates with several AudienceInsightsService methods including GenerateAudienceCompositionIns
Advertisers can now build audience strategies that combine life events with other targeting dimensions. Understanding that first-time homebuyers with high household income who show interest in home improvement content represent a valuable audience for certain products enables more sophisticated targeting strategies than life event data alone.
Implementation Considerations
While life event data provides valuable targeting capabilities, advertisers should understand its limitations and appropriate use cases. Life event signals derive from user behavior patterns and Google’s machine learning models rather than explicit user declarations. The signals indicate probability of experiencing a life event rather than confirmed status.
Life event audiences work best for products and services directly relevant to specific life transitions. Real estate services, wedding vendors, baby products, moving companies, and career services represent natural fits. Using life event targeting for loosely related products may produce weaker results than broader audience approaches.
Messaging and creative should align with life event targeting when campaigns explicitly target these audiences. Generic product messaging may miss opportunities to connect with users experiencing significant life transitions that create heightened purchase intent and emotional engagement.
Store Location Reporting with PerStoreView
Google Ads API v23 introduces the PerStoreView resource, providing programmatic access to store location performance data that previously required UI access or location extensions reports.
Store-Level Performance Analysis
PerStoreView enables querying performance metrics broken down by individual store locations for campaigns using location extensions or local inventory ads. Each store location reports impressions, clicks, conversions, and other metrics separately, enabling granular analysis of location-based campaign performance.
This capability proves particularly valuable for multi-location retailers using Google Ads to drive foot traffic. Understanding which locations generate the strongest response to advertising investment informs budget allocation, promotional strategy, and inventory management decisions.
Store-level data integrates with other business systems to provide comprehensive location performance analysis. Combining Google Ads location metrics with point-of-sale data, inventory systems, and customer relationship management platforms enables sophisticated attribution modeling that connects advertising exposure to in-store outcomes.
Geographic Optimization Applications
Programmatic access to store location performance enables automated optimization strategies that adjust campaigns based on individual location results.
Bid adjustments can vary by location based on historical performance data from PerStoreView. Stores demonstrating high conversion rates and strong return on ad spend justify higher bid modifiers, while underperforming locations might receive reduced bids or exclusion from certain campaigns.
Budget allocation across geographic campaigns becomes more sophisticated when store-level performance data informs spending decisions. Rather than distributing budget evenly across regions, automated systems can weight spend toward markets where specific store locations drive the strongest results.
Promotional strategy benefits from understanding which store locations respond best to advertising support. Stores showing high advertising efficiency might receive more frequent promotional campaigns, while locations with weak advertising response might benefit more from organic traffic or non-advertising marketing investments.
Vertical Ads Integration for Travel Campaigns
Version 23 introduces comprehensive support for vertical ads in travel search campaigns, enabling property promotion, booking link travel ads, and travel feed integration.
Vertical Ads Format Control
The new AdGroup.vertical_ads_ field allows advertisers running search campaigns with travel feeds to control which ad formats can serve. This addresses concerns about brand consistency and user experience by giving advertisers control over whether property promotion ads, booking link ads, or traditional text ads display for their campaigns.
Format control becomes particularly important for travel advertisers managing complex brand relationships and distribution strategies. A hotel brand might want property promotion ads for brand campaigns but prefer booking link ads for generic travel searches. Format settings enable this nuanced control without requiring separate campaigns for different ad types.
Travel Feed Targeting with Item Group Rules
The v23 release adds vertical_ads_item_group_ criterion type to AdGroupCriterion, enabling targeting of specific item groups from travel feeds. This provides product feed-like targeting capabilities for travel inventory, allowing campaigns to target specific hotel properties, destination groups, or property types based on feed attributes.
Item group targeting enables sophisticated campaign structures for travel advertisers with diverse inventory. A travel company could create separate ad groups targeting luxury properties, budget accommodations, or specific destination categories, each with tailored messaging, bids, and budget allocation.
Reporting Segmentation for Travel Ads
New segments for vertical ads enable performance analysis broken down by travel feed attributes. These include segments for hotel class, listing brand, geographic dimensions (city, country, region), partner account, and vertical type.
Detailed travel ad reporting addresses a significant pain point for travel advertisers who previously lacked visibility into which properties or categories drove campaign performance. The new segments enable analysis that connects advertising investment to specific inventory performance.
Revenue optimization becomes more sophisticated when performance data breaks down by property type, location, and brand. Travel advertisers can identify which inventory categories generate the best return on ad spend and adjust campaign strategy, bidding, and budget allocation accordingly.
Recommendation Service Enhancements
The v23 release includes a seemingly small but strategically significant addition to the RecommendationService: support for new customer modeling in campaign budget recommendations.
New Customer Budget Recommendations
The GenerateRecommendationsReq method now accepts an is_new_customer field that, when set to true for campaign budget recommendations, generates recommendations using a model specifically trained for new customer accounts without historical campaign data.
This addresses a significant limitation in recommendation quality for new advertisers. Standard budget recommendation models rely on account history to predict appropriate budget levels. New accounts without historical data received generic recommendations that often proved inaccurate for their specific business situations.
New customer models use different features and training data to generate recommendations appropriate for accounts without performance history. These models incorporate industry benchmarks, market data, and initial account setup information to provide more relevant budget guidance during the critical early stages of Google Ads adoption.
Implications for Partner and Agency Workflows
The new customer flag proves particularly valuable for partners and agencies onboarding multiple new advertisers. Automated onboarding workflows can programmatically request budget recommendations for new accounts and present data-informed starting budgets rather than arbitrary values or manual estimates.
Improved first-campaign budgets reduce the risk of new advertiser failure due to insufficient budget. Underfunding campaigns leads to limited data, poor performance due to budget constraints, and ultimately account abandonment. Better initial budget recommendations increase the likelihood of early campaign success and continued platform adoption.
Migration Guide and Best Practices for v23 Adoption
Successfully implementing Google Ads API v23 requires systematic planning, thorough testing, and careful version management. Organizations should follow a structured migration process to minimize disruption and maximize benefit from new capabilities.
Audit Current API Version Usage
The first step involves comprehensive auditing of current API version usage across all applications, scripts, and integrations. Teams should identify every system making Google Ads API calls and document the version each system uses.
Particular attention should focus on identifying any remaining v19 usage, as this version sunsets on February 11, 2026. Systems still using v19 require immediate migration priority to avoid service disruption.
Code audit tools can help systematize this process. Scripts that scan codebases for version-specific imports, endpoint URLs, and configuration files accelerate the identification process. For organizations with distributed development teams or multiple applications, automated auditing may be the only practical approach to comprehensive version inventory.
Update Client Libraries
Google provides official client libraries for multiple programming languages that abstract version management and request construction details. Organizations using these libraries should update to the latest library versions that support v23.
Python developers should upgrade the google-ads library to version 25.0.0 or later. Java developers need version 33.0.0 or later of the Google Ads API client library. PHP, .NET, Ruby, and other supported languages each have corresponding version requirements documented in Google’s client library documentation.
Library updates typically require more than just changing a version number in a dependency file. Code may need adjustments to accommodate API changes, new required parameters, or deprecated methods. Thorough testing after library updates prevents surprises in production environments.
Test in Sandbox or Test Accounts
Before deploying v23 changes to production systems, thorough testing in isolated environments validates that updates work correctly and don’t introduce regressions. Google provides test accounts specifically for API development and testing purposes.
Test scenarios should cover all API operations the application performs, with particular attention to features affected by v23 changes. Campaign creation, reporting queries, audience management, and any other API interactions need validation with the new version.
Performance testing ensures that v23 updates don’t introduce latency or throughput issues. While API version updates typically don’t significantly affect performance, new features or expanded response data could impact application efficiency.
Error handling testing validates that applications appropriately handle new error types introduced in v23. The incentives service, for example, introduces new error codes that applications should handle gracefully even if they don’t actively use incentive features.
Implement New Features Incrementally
Organizations should consider phased implementation of v23 features rather than attempting to adopt everything simultaneously. Prioritizing features by business value and implementation complexity creates a manageable rollout schedule.
High-priority features like Performance Max network breakdowns might warrant immediate implementation due to their significant business value. Lower-priority features can be scheduled for later implementation phases, allowing development resources to focus on maximum-impact capabilities first.
Each feature implementation should include monitoring and validation to ensure the new capability delivers expected benefits. Performance Max network data, for example, should be validated against total campaign metrics to ensure data integrity before building optimization systems that depend on network-level insights.
Establish Ongoing Version Management Processes
The shift to monthly API releases requires different operational practices compared to quarterly updates. Organizations need sustainable processes for staying current with API changes without disrupting ongoing development work.
Regular review cycles should monitor Google’s release announcements and evaluate new versions for adoption. A monthly or bi-monthly schedule for reviewing API updates and planning adoption timelines prevents versions from aging into sunset territory unexpectedly.
Automated testing pipelines that can quickly validate new API versions against existing application functionality reduce the burden of frequent updates. Investment in test automation pays ongoing dividends as release cadence accelerates.
Documentation practices should track which API versions each application uses and maintain migration plans for moving to newer versions before sunset dates arrive. This documentation proves invaluable when team members change or when multiple applications require coordinated updates.
Frequently Asked Questions About Google Ads API v23
What is Google Ads API v23 and when was it released?
Google Ads API v23 is the latest version of Google’s programmatic interface for managing advertising campaigns, released on January 28, 2026. This release marks the first update of 2026 and signals Google’s transition to a monthly release cadence throughout the year, enabling faster delivery of new features to developers and advertisers.
What are the main new features in Google Ads API v23?
The primary features in v23 include ad network type breakdowns for Performance Max campaigns (showing performance by Search, YouTube, Display, and Discover), AI-powered natural language audience building through GenerateAudienceDefinition, precise datetime campaign scheduling replacing date-only fields, granular campaign-level invoice details, surface-specific Demand Gen conversion rate forecasting, Shopping competitive metrics, programmatic incentive management, and comprehensive travel vertical ads support.
When does Google Ads API v19 sunset?
Google Ads API v19 reaches end-of-life on February 11, 2026. After this date, all requests to v19 endpoints will fail. Organizations still using v19 must prioritize immediate migration to v20 or higher to avoid service disruptions. This represents one of the shortest migration windows in recent Google Ads API history due to the accelerated release schedule.
How does the Performance Max ad network type breakdown work?
The v23 ad network type breakdown allows querying Performance Max campaign metrics segmented by specific advertising networks including Search, YouTube Search, YouTube Watch, Display, and Discover. Developers add segments.ad_network_type
What is the GenerateAudienceDefinition feature and how does it work?
GenerateAudienceDefinition is a new method in AudienceInsightsService that uses natural language processing and generative AI to convert free-text audience descriptions into structured Google Ads targeting parameters. Users provide descriptions like “eco-conscious parents in urban areas shopping for sustainable children’s products” and receive back concrete audience segments, demographic targets, and interest categories matching that description.
Can I still use the old start_date and end_date fields for campaign scheduling?
The legacy start_date and end_datestart_date_time and end_ fields that provide minute-precision scheduling with explicit time zone support. New code should use datetime fields exclusively to prepare for eventual removal of legacy date fields.
What are the new InvoiceService capabilities in v23?
The v23 InvoiceService enhancement adds granular invoice details when setting include_granular_ to true. This returns campaign-level cost breakdowns showing exactly how spending distributed across individual campaigns, itemized regulatory fees by jurisdiction and type, and detailed adjustment information for credits, refunds, and corrections. This data significantly improves financial reconciliation and client billing for agencies.
How does the monthly release cadence affect my development process?
The monthly release cadence requires more frequent attention to API updates compared to the previous quarterly schedule. Development teams need compressed testing cycles to evaluate new versions, more frequent client library updates, and potentially accelerated deprecation timelines. Organizations should establish continuous integration practices, automated testing frameworks, and regular review cycles to sustainably manage monthly updates without disrupting ongoing development work.
What programming languages does Google Ads API v23 support?
Google provides official client libraries supporting v23 for Python, Java, PHP, .NET, Ruby, Perl, and Go. Additionally, developers can use REST API access for any language capable of making HTTP requests. Each client library handles authentication, request construction, and response parsing, simplifying v23 integration compared to direct REST API usage.
Can I use Performance Max network breakdowns to control budget allocation by network?
No, the network breakdown feature provides visibility into performance by network but does not enable direct budget control. Google’s algorithm continues to manage budget allocation across networks automatically within Performance Max campaigns. The data informs strategic decisions about campaign structure, asset development, and overall budget setting but doesn’t allow specifying “spend X% on YouTube and Y% on Display.”
How accurate is the AI-generated audience definition feature?
The accuracy of GenerateAudienceDefinition depends heavily on description specificity and the availability of matching audience segments in Google Ads. Detailed descriptions including demographics, interests, behaviors, and context produce more accurate results than vague descriptions. The system approximates targeting intent using available audience segments but cannot create targeting options that don’t exist. All generated audiences should be reviewed by experienced practitioners before production use.
What happens if I don’t migrate from v19 before the sunset date?
After February 11, 2026, all requests to Google Ads API v19 endpoints will return errors and fail. Applications still using v19 will lose the ability to manage campaigns, retrieve reporting data, or perform any API operations, resulting in service disruptions. Manual UI access remains functional, but programmatic management breaks completely. Organizations must migrate before the sunset date to maintain automated campaign management capabilities.
Are there any breaking changes in v23 that will affect my existing code?
Version 23 includes several breaking changes that may affect existing implementations. The removal of CallAd support requires alternatives for call campaigns. New required parameters for certain operations may cause validation errors in existing code. Enhanced error handling for incentives introduces new error types. Organizations should thoroughly review the v23 release notes and test existing functionality after upgrading to identify any breaking changes affecting their specific implementation.
How can I test v23 features without affecting production campaigns?
Google provides test accounts specifically for development and testing purposes. Organizations can request test accounts through the Google Ads API support channels. These accounts allow full API access without spending actual advertising budget. Additionally, production accounts can be used with test campaigns that have minimal budgets and narrow targeting to validate v23 features before scaling implementation.
What is the typical support window for Google Ads API versions?
Google typically maintains support for API versions for approximately 12 months from initial release. With the monthly release cadence starting in 2026, this means multiple versions will remain supported simultaneously, but each version has a limited lifespan. Organizations should plan to stay within the two or three most recent versions to maintain adequate support windows and avoid approaching sunset dates unexpectedly.
Positioning for Success with Google Ads API v23
Google Ads API v23 represents more than an incremental update; it signals a strategic shift in how Google approaches API development and the role programmatic access plays in its advertising ecosystem. The transition to monthly releases reflects Google’s recognition that rapid feature delivery becomes increasingly critical as AI and automation expand across advertising platforms.
The v23 feature set reveals clear strategic priorities. Performance Max transparency addresses advertiser concerns while maintaining Google’s automation-first approach. AI-powered audience building lowers barriers to sophisticated targeting, expanding the pool of advertisers who can execute complex strategies. Enhanced reporting granularity supports the data-driven decision making that automation requires to succeed.
Organizations leveraging the Google Ads API should approach v23 adoption strategically rather than opportunistically. The Performance Max network breakdowns enable immediate analytical improvements for advertisers running these campaigns. The natural language audience building creates workflow efficiencies for teams managing multiple clients or accounts. Precision scheduling unlocks time-sensitive promotional strategies previously difficult to execute reliably.
The accelerated release cadence necessitates operational changes beyond simply updating code more frequently. Development teams need sustainable practices for continuous API evolution, including automated testing frameworks, systematic version monitoring, and regular update cycles. Organizations treating API updates as occasional projects will struggle with monthly releases, while those establishing continuous integration practices will gain competitive advantages from faster feature adoption.
The February 11, 2026 sunset of v19 creates immediate urgency for organizations still operating on this version. The compressed timeline between v23’s release and v19’s sunset reflects Google’s intention to maintain fewer active versions simultaneously despite more frequent releases. Teams should prioritize version auditing and migration planning immediately to avoid service disruptions.
Looking forward, the monthly release pattern established with v23 suggests continued rapid feature development throughout 2026. Organizations should expect ongoing enhancement of AI-powered capabilities, expanded automation options, and deeper reporting granularity as Google’s advertising platform evolution accelerates. Maintaining currency with API updates becomes not just a technical requirement but a competitive necessity for maximizing advertising effectiveness.
About ALM Corp
ALM Corp specializes in Google Ads API integration, campaign automation, and performance optimization for e-commerce businesses and marketing agencies. Our team provides comprehensive API development services including custom integration implementation, automated reporting systems, campaign management platforms, and migration consulting for organizations transitioning between API versions.
The Google Ads API v23 release introduces capabilities that align closely with ALM Corp’s expertise in programmatic advertising management. Our Performance Max optimization systems immediately benefit from network-type breakdowns, enabling more sophisticated performance analysis and strategic recommendations for clients. The natural language audience building capability integrates seamlessly with our automated campaign creation workflows, accelerating audience development while maintaining targeting precision.
For organizations navigating the v19 sunset deadline or planning v23 adoption, ALM Corp offers migration assessment and implementation services. We audit existing API integrations, identify version dependencies, develop migration roadmaps, and execute updates with minimal disruption to ongoing campaign management. Our experience across hundreds of Google Ads accounts enables efficient migration that protects campaign performance while adopting new v23 capabilities.
Contact ALM Corp to discuss how Google Ads API v23 features can enhance your advertising operations, schedule a migration assessment for v19 systems approaching sunset, or explore custom API integration solutions that leverage the latest platform capabilities for competitive advantage.
Sources
- Google Ads Developer Blog: Announcing v23 of the Google Ads API – http://ads-developers.
googleblog.com/2026/01/ announcing-v23-of-google-ads- api.html - Google for Developers: Google Ads API Release Notes – https://developers.google.
com/google-ads/api/docs/ release-notes - Search Engine Land: Google Ads API v23 brings PMax data, richer invoicing, scheduling – https://searchengineland.
com/google-ads-api-v23-468104 - SKU Analyzer: Google Ads API v23 Complete Guide to the January 2026 Update – https://skuanalyzer.com/
articles/google-ads-api-v23- update/ - Search Engine Roundtable: Google Ads API Version 23 Now Available – https://www.seroundtable.
com/google-ads-api-version-23- 40839.html
