What Are Google Demand Gen Campaigns?
Google's advertising platform continues to evolve, and Demand Gen campaigns represent the next evolution in video-first advertising. Originally designed to help advertisers reach users during their discovery and consideration phases, Demand Gen campaigns combine the best elements of Video Action Campaigns with expanded reach across YouTube, Discover, and Gmail. With the automatic upgrade of Video Action Campaigns to Demand Gen now underway, advertisers need to understand how to optimize their campaigns for this new format while maintaining or improving performance.
The Evolution from Video Action Campaigns
Demand Gen campaigns emerged as Google's response to changing consumer behavior on its properties. While Video Action Campaigns focused primarily on driving conversions through video ads on YouTube, Demand Gen expands this concept to reach users earlier in their discovery journey. The campaign type leverages Google's AI to deliver visually rich ad experiences across multiple Google surfaces, meeting users where they naturally browse and explore content.
The key distinction lies in the funnel position. Video Action Campaigns were optimized for users already familiar with a brand or product and ready to take action. Demand Gen campaigns target users in the awareness and consideration stages, using engaging visual formats to spark interest and nurture potential customers toward conversion. This approach recognizes that modern consumers rarely follow a linear path to purchase, often discovering new brands and products through organic browsing before ever searching directly.
Demand Gen campaigns combine multiple ad formats within a single campaign structure, including video ads, image ads, and carousel formats that allow brands to showcase multiple products or messages. This flexibility enables advertisers to create more comprehensive creative strategies that address different stages of user engagement. The campaigns also benefit from Google's machine learning optimization, which automatically tests different combinations and placements to identify the most effective approaches for each advertiser's goals.
Key Features and Capabilities
The feature set of Demand Gen campaigns reflects Google's investment in AI-powered advertising. Advertisers can create multiple asset groups within a single campaign, each with its own set of videos, images, headlines, and descriptions. Google's AI then assembles these assets into various ad formats based on available inventory and predicted performance. This approach reduces the manual work required to create platform-specific creatives while ensuring ads are optimized for each placement.
Reach extends across three primary Google surfaces: YouTube, Discover, and Gmail. YouTube placements include in-stream ads, video discovery ads, and Shorts, while Discover surfaces appear in the personalized feed users see across Google properties. Gmail placements show ads within the promotional and social tabs of the email interface. This multi-surface approach provides advertisers with significantly more opportunities to engage potential customers throughout their daily digital routines.
The targeting capabilities in Demand Gen campaigns mirror those available in Performance Max, including demographic targeting, audience signals, geographic targeting, and content exclusions. Advertisers can also leverage in-market audiences and affinity audiences to reach users with specific interests or purchase intentions. This combination of broad reach and precise targeting creates opportunities to build brand awareness while still moving users toward conversion.
Multi-Surface Reach
Deliver ads across YouTube, Discover, and Gmail to reach users during discovery and consideration phases.
AI-Powered Optimization
Google's machine learning automatically tests asset combinations and optimizes delivery for each placement.
Diverse Ad Formats
Support for video ads, image ads, and carousel formats within a single campaign structure.
Expanded Targeting
Leverage demographic targeting, audience signals, in-market audiences, and affinity audiences.
The Video Action Campaign Migration
Understanding the Automatic Upgrade Process
Google announced that Video Action Campaigns would be automatically upgraded to Demand Gen campaigns, with the transition completing in Q2 2025. This automatic upgrade ensures that advertisers don't experience disruption in their video advertising efforts while providing access to the expanded capabilities of Demand Gen. Understanding this process helps advertisers prepare and optimize their campaigns for the transition, as outlined in Google's official upgrade documentation.
The upgrade process preserves most campaign settings, including targeting, bidding strategies, and budget allocations. However, creative assets require attention, as Demand Gen supports additional formats beyond traditional video ads. Advertisers who have been running Video Action Campaigns may need to add image assets to their campaigns to fully leverage Demand Gen's carousel and image ad formats. Without these additional assets, campaigns will continue functioning but won't take full advantage of the new formats available.
Google has provided an upgrade tool within Google Ads that allows advertisers to preview their campaigns before the automatic transition and make necessary adjustments. This tool shows which campaigns will be upgraded, highlights any creative assets that need to be added, and provides recommendations for optimizing the new campaign structure. Accessing this tool before the automatic upgrade gives advertisers time to prepare and avoid any potential performance dips during the transition, as noted by industry analysts at Search Engine Land.
Preparing Your Campaigns for Migration
Preparation for the Demand Gen migration should begin several weeks before the automatic upgrade date. Review your existing Video Action Campaigns and assess the creative assets currently in use. Ensure you have high-quality image assets available in the recommended sizes, including landscape, square, and portrait formats to maximize creative flexibility across different placements.
Examine your current audience targeting and consider whether the expanded reach of Demand Gen requires any adjustments. While core targeting options remain available, the ability to reach users on Discover and Gmail may require reviewing content exclusions and brand safety settings. Users on these surfaces may have different contextual signals than YouTube viewers, so refining your targeting approach can improve campaign performance.
Budget allocation deserves attention during migration planning. Some advertisers report that Demand Gen campaigns achieve lower cost-per-conversion than their predecessors due to the expanded reach and optimized creative delivery. However, this varies by industry and campaign objectives. Consider starting with a test budget to establish performance baselines before scaling投入, and use the insights from initial performance to inform broader budget decisions. Working with a digital advertising specialist can help you navigate these decisions effectively.
Campaign Setup and Structure
Creating Effective Asset Groups
The asset group structure in Demand Gen campaigns serves as the foundation for AI-optimized ad delivery. Each asset group functions as a container for related creative elements, including headlines, descriptions, images, videos, logos, and optional calls-to-action. Google's AI uses these assets to generate various ad combinations and tests them across different placements to identify high-performing variations.
Best practices for asset groups recommend creating multiple groups with distinct themes or product categories. This approach allows the AI to learn which combinations resonate with different audience segments and optimize delivery accordingly. For example, a retailer might create separate asset groups for different product lines, while a service business might differentiate by customer type or offering tier.
Headline and description assets should be written to work across multiple contexts, as they may appear in video ads, carousel cards, or image formats. Include a mix of benefit-focused and feature-focused messaging to provide the AI with options for different audience preferences. Google recommends providing at least five headlines and five descriptions per asset group, with clear differentiation between each asset to enable effective testing.
Video assets remain central to Demand Gen campaigns, even with the addition of image formats. Ensure your videos are optimized for the platforms where they'll appear, with the first few seconds designed to capture attention immediately. Videos should communicate key messages quickly, as users may not watch to completion before scrolling or clicking away. Consider creating shorter edits specifically for placements where user attention is limited.
Bidding Strategies and Budget Considerations
Demand Gen campaigns support the same bidding strategies available in other Google Ads campaign types, with options including Maximize Conversions, Target CPA, Maximize Clicks, and Manual CPC. The choice of bidding strategy should align with your primary campaign objective and the stage of the customer journey you're targeting.
For advertisers focused on conversions, Maximize Conversions provides the most automated approach, allowing Google's AI to optimize toward conversion events while managing spend across the expanded inventory. Target CPA allows for more explicit control over cost-per-acquisition goals but may limit reach if targets are set too aggressively relative to market conditions.
Budget management in Demand Gen campaigns should account for the expanded reach across multiple surfaces. Daily budgets may need adjustment from Video Action Campaign levels to capture the additional inventory available through Discover and Gmail placements. However, the AI optimization typically improves efficiency, so cost-per-results may decrease even as total spend increases. Monitor performance metrics closely during the initial scaling period to establish appropriate budget levels that align with your overall advertising strategy.
Targeting and Audience Strategy
Leveraging Audience Signals
Audience signals in Demand Gen campaigns function similarly to Performance Max, allowing advertisers to provide hints about their ideal customers without creating strict audience restrictions. The AI uses these signals to prioritize delivery to users who match the described characteristics while still reaching beyond those segments to expand reach.
Effective audience signals combine demographic information with interest-based signals. Consider which customer segments have historically performed well and translate those characteristics into signal inputs. Include information about customer behaviors, content consumption patterns, and purchase intentions to help the AI identify high-potential users across the expanded inventory.
In-market audiences remain valuable for Demand Gen campaigns, particularly for advertisers selling products or services with defined category interest. These audiences indicate recent purchase intent and can help focus delivery on users actively researching solutions in your category. Combining in-market signals with affinity audiences, which indicate long-term interests, creates a targeting approach that captures both immediate intent and sustained interest.
Remarketing audiences can be incorporated through customer match strategies, allowing you to reach previous customers or prospects who have engaged with your brand. This approach is particularly valuable for advertisers looking to increase frequency among warm audiences or promote complementary products to existing customers. The expanded reach of Demand Gen provides additional touchpoints for nurturing these relationships and driving them toward conversion through your website conversion funnels.
Expanding Reach Across Surfaces
The multi-surface nature of Demand Gen campaigns requires a thoughtful approach to reach strategy. Each surface--YouTube, Discover, and Gmail--attracts users in different contexts and mindsets, which influences how creative should be developed and how performance should be measured.
YouTube placements capture users in video consumption mode, making them ideal for storytelling and demonstration content. Users on YouTube often have higher engagement with video content, creating opportunities for deeper brand engagement. Performance metrics for YouTube placements should include video engagement signals alongside conversion metrics to understand full-funnel impact.
Discover placements appear within the personalized content feed that users see when browsing Google properties. These placements are interruption-based, appearing between content the user is actively consuming, which may require more attention-grabbing creative. Image-based formats often perform well on Discover due to the visual nature of the feed, and carousel formats can showcase multiple products or messages within a single ad unit.
Gmail placements show ads within the email interface, creating opportunities to reach users in a communication context. The format resembles email content, with ads appearing in the promotional and social tabs. Creative for Gmail should be designed to feel native within the email experience while still clearly identifying as advertising. This surface often provides strong performance for direct response objectives due to the user's task-oriented mindset when checking email.
Creative Best Practices
Developing Multi-Format Creative Assets
Successful Demand Gen campaigns require creative strategies that account for the variety of formats and placements where ads may appear. Rather than repurposing a single video across all placements, develop assets with format-specific considerations to maximize performance across each surface, as recommended by Smartly.io's migration guide.
Video assets should be produced in multiple aspect ratios to accommodate different placement requirements. Landscape formats (16:9) work well for YouTube in-stream placements, while vertical formats (9:16) maximize impact in Shorts and mobile Discover placements. Square formats (1:1) provide flexibility across placements and can be effective in both video and image contexts. Having multiple ratio options ensures your message is presented optimally regardless of where the ad appears.
Image assets have become essential with the introduction of carousel and image ad formats in Demand Gen. Develop a library of images in various sizes, including the recommended 1200x628 landscape format, 1200x1200 square format, and 1200x1500 portrait format for carousel cards. Each image should be compelling on its own while also working cohesively with other assets in the same asset group.
Carousel formats offer unique opportunities to tell sequential stories or showcase multiple products. Plan carousel content to create logical progression from one card to the next, whether highlighting different product features, presenting customer testimonials, or demonstrating a step-by-step process. The first carousel card should be particularly attention-grabbing, as it determines whether users engage with the remaining cards.
Testing and Optimization Approaches
Testing in Demand Gen campaigns operates at the asset combination level, with Google's AI automatically testing different permutations and learning which combinations perform best for each placement. Advertisers can support this testing by providing diverse assets that offer clear alternatives for the AI to evaluate.
A/B testing at the campaign level remains valuable for testing broader strategies, such as different bidding approaches, budget levels, or targeting variations. Run controlled experiments with isolated variables to understand the impact of specific changes before implementing them broadly. This approach provides actionable insights while minimizing risk to overall campaign performance.
Monitor performance data at the asset level to understand which creative elements drive results. Google Ads provides asset performance reports that show how individual headlines, images, and videos perform within your campaigns. Use these insights to inform future creative development, doubling down on approaches that demonstrate strong performance while iterating on underperforming elements.
Seasonal and promotional testing should be planned in advance, with creative assets developed for key dates and events relevant to your business. Demand Gen campaigns can respond quickly to seasonal opportunities when appropriate creative is available, so maintaining a library of adaptable assets enables rapid deployment of timely campaigns that align with your overall marketing calendar.
Performance Benchmarks and Integration
Understanding Performance Metrics
Performance measurement in Demand Gen campaigns requires attention to both conversion-focused metrics and engagement indicators that capture the awareness-building value of the format. Conversion metrics like cost-per-conversion and conversion rate remain important, but should be supplemented with video engagement metrics and reach data to understand full campaign impact.
Industry benchmarks suggest that advertisers integrating Demand Gen with existing Search and Performance Max campaigns see meaningful improvements in conversions compared to running those campaigns without Demand Gen support. This integration approach allows Demand Gen to serve its intended purpose as an upper-funnel tactic that feeds downstream conversion activity. Uplift varies by industry, with advertisers whose products have strong visual appeal often seeing stronger results due to the format's emphasis on engaging visual content.
Engagement metrics provide insight into how users interact with Demand Gen content before converting. Video view rates, click-through rates, and time spent with ad content indicate how effectively creative captures attention and communicates value propositions. These metrics are particularly important for understanding performance on awareness-focused objectives where conversion windows may be extended.
Attribution for Demand Gen campaigns requires consideration of the customer journey context. Users may encounter Demand Gen content during discovery, engage with the brand through other touchpoints, and eventually convert through a different channel. Using attribution models that account for upper-funnel touchpoints provides more accurate understanding of Demand Gen's contribution to overall performance.
Integration with Broader Campaign Strategies
Demand Gen campaigns work most effectively as part of a coordinated advertising strategy rather than as standalone initiatives. The format excels at creating awareness and consideration that feeds into conversion-focused campaigns running on Search and Performance Max.
Integration with Performance Max campaigns requires attention to audience overlap and budget allocation. Both campaign types may compete for similar inventory and audience attention, which can create inefficiencies if not managed thoughtfully. Consider using audience exclusions or campaign priority settings to coordinate delivery and prevent internal competition.
Search campaign integration benefits from Demand Gen's ability to build familiarity with your brand before users enter active search mode. Users who have seen Demand Gen content may be more likely to click on Search ads and convert at higher rates due to prior brand exposure. This synergy suggests that budgets allocated to Demand Gen may reduce effective costs in downstream Search campaigns.
Testing the incremental impact of Demand Gen requires controlled experiments that isolate its contribution. Some advertisers use geographic or time-based exclusions to create holdout groups that don't receive Demand Gen impressions, then compare conversion rates between exposed and unexposed segments. This approach provides concrete evidence of Demand Gen's value but requires sufficient scale to generate statistically significant results.
Cost Optimization Strategies
Maximizing Budget Efficiency
Budget efficiency in Demand Gen campaigns depends on aligning creative quality, targeting precision, and bidding strategy with campaign objectives. Small improvements in each area compound to create significant cost advantages over time.
Creative quality directly impacts cost efficiency through its effect on engagement and conversion rates. High-quality assets that capture attention and communicate value effectively lead to higher engagement, which improves the quality scores that influence ad serving and costs. Investing in professional creative development typically yields returns through improved performance metrics.
Audience refinement helps control costs by focusing delivery on users most likely to convert or engage meaningfully. Review performance data segmented by audience to identify segments with strong conversion rates and consider narrowing targeting to prioritize these groups. However, be careful not to over-narrow, as the expanded reach of Demand Gen is part of its value proposition for building awareness at scale.
Bidding strategy optimization requires ongoing attention as campaigns mature. The AI learns from performance data over time, but initial bidding settings may need adjustment as you gather more information about realistic cost-per-conversion levels. Regular review of bidding performance helps identify opportunities to improve efficiency while maintaining scale. Partnering with a performance marketing agency can help you navigate these optimizations effectively.
Managing Costs During Scale
Scaling Demand Gen campaigns while maintaining cost efficiency requires a deliberate approach that balances reach expansion with performance maintenance. As budgets increase, inventory constraints and audience exhaustion may drive costs upward if not managed carefully.
Gradual budget increases allow the AI to find new opportunities without sudden disruptions to performance. Large budget jumps can temporarily degrade performance as the algorithm explores new inventory and audience segments. Incremental increases, with performance stabilization between steps, tend to produce more consistent results over time.
Creative refreshes provide opportunities to maintain performance during scale phases. Users who have seen the same creative repeatedly may develop banner blindness, reducing engagement and conversion rates. Introducing new creative assets keeps campaigns fresh and provides the AI with new combinations to test. Plan regular creative refreshes as part of ongoing campaign management to maintain momentum.
Inventory expansion through relaxed exclusions can provide additional scale, but requires monitoring to ensure performance doesn't degrade significantly. Consider expanding content exclusions or geographic targeting gradually, evaluating impact on cost-per-result before making further adjustments. This approach expands reach while maintaining control over performance and ensuring your advertising investment delivers measurable returns.
Common Migration Challenges and Solutions
Creative Asset Gaps
The most common challenge during Demand Gen migration involves insufficient creative assets to fully leverage the new formats. Advertisers transitioning from Video Action Campaigns often have strong video libraries but lack the image assets required for carousel and image ad formats.
Resolution requires developing a systematic approach to image asset creation. Work with design resources to produce high-quality images in the recommended sizes and formats. Consider adapting existing video content by extracting key frames or creating still versions that maintain visual consistency with video creative. The investment in image assets typically produces returns through improved performance across image-based placements.
Asset quantity is also important, as Google's AI requires sufficient variety to test and optimize. Aim to provide at least the recommended minimum number of assets while exceeding these thresholds when possible. Quality should remain the priority, but quantity supports the testing and learning process that drives performance improvements over time.
Performance Drops During Transition
Some advertisers experience temporary performance declines during the transition from Video Action Campaigns to Demand Gen. This can occur due to the AI learning new optimization patterns, changes in inventory, or mismatched creative for the expanded format.
Monitoring performance closely during the transition period helps identify issues early. Compare performance against historical baselines while accounting for the expected adjustment period as the AI adapts to the new campaign structure. If performance doesn't stabilize within a reasonable timeframe, investigate specific factors such as placement distribution, creative performance by format, or audience composition.
Adjusting targeting or bidding strategies may help stabilize performance during transition. If costs have increased significantly, consider tightening audience focus or adjusting bidding targets. If volume has declined, review any targeting changes that may have inadvertently limited reach. The goal is to find the balance between maintaining performance and taking advantage of Demand Gen's expanded capabilities.
When challenges persist, seeking additional optimization support from Google Ads specialists can help diagnose issues and implement solutions more quickly. The learning curve for Demand Gen optimization is similar to other AI-powered campaign types, and experienced practitioners can often identify fixes that aren't immediately apparent.