Google Enhances Demand Gen Campaigns with Gemini AI, Automated Video Resizing, and Advanced App Attribution

Google has announced a major suite of updates to its Demand Gen campaigns, designed to help digital marketers optimize creative performance, streamline asset production, and more accurately measure cross-channel return on ad spend (ROAS).

As visual-first platforms continue to dominate consumer attention, these updates aim to lower the technical barriers to high-quality video advertising while solving persistent attribution challenges across web and mobile application ecosystems.

Executive Summary: Google’s Next Step in Visual Commerce

The latest updates to Google’s Demand Gen campaigns focus on three core pillars of modern digital advertising: creative agility, artificial intelligence integration, and holistic attribution.

By introducing automated video resizing capabilities, embedding Gemini-powered asset recommendations directly into the campaign workflow, and launching Web-to-App Acquisition Measurement, Google is positioning Demand Gen as a comprehensive solution for mid-to-upper-funnel customer acquisition.

These enhancements arrive at a critical juncture. Advertisers are increasingly tasked with doing more with less, managing fragmented creative assets across multiple aspect ratios, and navigating a privacy-first landscape that has complicated conversion tracking.

According to Google, these updates are specifically engineered to reduce "creative friction"—the time, budget, and labor required to adapt ad creatives for different placements—while giving marketers deeper insights into how their media spend translates into tangible business outcomes, particularly on YouTube.

Main Facts: Deciphering the New Demand Gen Features

To understand the impact of Google’s announcement, it is necessary to examine the technical and operational mechanics of the three primary features being rolled out.

                    ┌────────────────────────────────────────┐
                    │      Google Demand Gen Updates         │
                    └───────────────────┬────────────────────┘
                                        │
         ┌──────────────────────────────┼──────────────────────────────┐
         ▼                              ▼                              ▼
┌──────────────────┐          ┌──────────────────┐          ┌──────────────────┐
│  Video Resizing  │          │    Gemini AI     │          │    Web-to-App    │
│  Auto-transform  │          │  Asset-level suggestions │  Cross-channel   │
│  aspect ratios   │          │  pre-launch optimization │  install tracking│
└──────────────────┘          └──────────────────┘          └──────────────────┘

Expanded Video Resizing: Eliminating Creative Bottlenecks

One of the most labor-intensive aspects of running multi-placement video campaigns is formatting. A video optimized for YouTube’s standard desktop player (16:9 landscape) rarely performs well on YouTube Shorts (9:16 vertical) or the Google Discover feed (1:1 square). Historically, creative teams had to manually re-edit, crop, and export multiple versions of a single video asset to ensure optimal delivery across all surfaces.

Google’s updated Demand Gen campaigns address this by expanding automated video resizing capabilities. Advertisers can now automatically transform existing creative assets between additional aspect ratios, including:

• Vertical-to-Square (9:16 to 1:1)
• Vertical-to-Landscape (9:16 to 16:9)
• Square-to-Landscape (1:1 to 16:9)

This machine-learning-driven reframing technology analyzes the visual composition of the original video to keep the primary subject centered and in-frame during the conversion process, significantly reducing the manual production burden for design teams.

Gemini Integration: The AI Creative Co-Pilot

Google is integrating its flagship generative AI model, Gemini, directly into the Demand Gen campaign creation workflow. This integration moves beyond simple text generation to assist with visual and structural asset optimization.

When advertisers upload their image and video assets, Gemini analyzes the selection and provides automated, real-time recommendations on how to improve the creative before the campaign goes live. These recommendations may include suggestions on visual contrast, framing, call-to-action placement, and alignment with YouTube’s best practices. By acting as a pre-launch optimization engine, Gemini helps marketers maximize their initial budget deployment by weeding out underperforming assets before they serve impressions.

Web-to-App Acquisition Measurement: Bridging the Attribution Gap

For brands that operate both web e-commerce platforms and native mobile applications, tracking the consumer journey has historically been disjointed. A user might click a Demand Gen ad on their desktop or mobile browser, navigate the mobile website, and eventually decide to download the brand’s app to complete a purchase.

The new Web to App Acquisition Measurement feature in Demand Gen addresses this gap. It allows advertisers to seamlessly attribute mobile app installs and subsequent in-app actions back to the initial web-based Demand Gen campaigns. By providing a unified view of the consumer journey across web and app environments, marketers can calculate a more accurate return on ad spend (ROAS) and optimize their bidding strategies for higher-lifetime-value customers.

Chronology: From Discovery Ads to the AI-Powered Era

To understand why Google is prioritizing these specific updates, it is helpful to look at the chronological evolution of Google’s visual ad offerings.

  2019                       Late 2023                 2024 - Present
  ┌─────────────────────────┐ ┌───────────────────────┐ ┌──────────────────────┐
  │ Discovery Ads Launched  ├─► Demand Gen Rollout    ├─► Gemini & Web-to-App  │
  │ Static visual feeds     │ │ Video integration,    │ │ AI optimization,     │
  │ (Discover, Gmail, YT)   │ │ Shorts focus, AI tech │ │ cross-channel track  │
  └─────────────────────────┘ └───────────────────────┘ └──────────────────────┘

• 2019 – The Launch of Discovery Ads: Google introduced Discovery campaigns, allowing advertisers to reach users on highly visual personalized feeds, including the Google Discover feed, Gmail promotions tabs, and the YouTube Home feed. These ads were primarily static images and carousel formats designed to capture intent-free browsing.
• June 2023 – The Announcement of Demand Gen: At its annual Google Marketing Live (GML) event, Google announced Demand Gen as the AI-powered successor to Discovery campaigns. The new format was built specifically to integrate video assets, particularly targeting YouTube Shorts and YouTube In-Stream placements alongside traditional Discover and Gmail feeds.
• October 2023 – Global Rollout of Demand Gen: Google officially migrated all Discovery campaigns to Demand Gen. The platform introduced lookalike segments, unique creative combinations, and localized bidding strategies, signaling a major shift toward automated, asset-based programmatic advertising.
• Early 2024 – Generative Image Tools: Google integrated text-to-image generative AI tools into Demand Gen, allowing advertisers to generate high-quality lifestyle imagery using simple text prompts directly within the Google Ads interface.
• Mid-2024 to Present – The Creative and Measurement Expansion: The current rollout represents the latest phase in this evolution, shifting focus from pure asset generation to asset adaptation (via resizing), intelligent curation (via Gemini recommendations), and omnichannel measurement (via Web-to-App tracking).

Supporting Data: The Strategic Value of YouTube and Visual Surfaces

Google’s decision to double down on Demand Gen features is backed by significant shift in consumer behavior and independent market research.

The New Customer Acquisition Engine

A key driver behind these updates is YouTube’s growing role as a performance marketing engine rather than just a brand awareness platform. Google cited research conducted by independent marketing measurement firm Measured, which revealed a compelling statistic for acquisition-focused marketers:

72% of incremental conversions generated on YouTube come from entirely new customers.

This data challenges the traditional view that video advertising primarily captures existing demand or assists in retargeting. Instead, it highlights YouTube’s capability to generate net-new demand, making it an essential channel for brands looking to expand their market share.

The Rise of Multi-Format Consumption

The necessity of automated video resizing is underscored by the explosion of YouTube Shorts. According to Google’s internal data, YouTube Shorts now averages over 70 billion daily views.

However, users do not consume vertical Shorts in isolation; they frequently transition between long-form horizontal videos on their connected TVs (CTVs) or desktops, and vertical videos on their mobile devices. Advertisers who restrict their campaigns to a single aspect ratio miss out on a massive portion of this cross-device user journey.

Official Positioning and Industry Responses

Google’s Perspective

In their official communications regarding the product drop, Google emphasized that the goal of these updates is to democratize high-performing creative workflows. By automating the technical aspects of video production and leveraging generative AI for pre-flight checks, Google aims to level the playing field for mid-market advertisers who may not have the massive creative agencies of enterprise brands.

Google noted that the updates are designed to:

"Combine AI-powered creative guidance, more flexible video optimization, and expanded measurement capabilities to help advertisers improve campaign performance while gaining clearer visibility into customer acquisition."

Industry Analyst and Practitioner Perspectives

Within the digital marketing community, response to the updates has been cautiously optimistic, with search engine marketing (SEM) and paid media specialists highlighting both the opportunities and the potential pitfalls of increased automation.

• On Video Resizing: Paid media editors and agency directors note that while automated resizing is a massive time-saver, creative teams must still monitor the output. Machine learning cropping can occasionally obscure text overlays or crop out subtle branding elements. Experts recommend using the auto-resized videos as a baseline but conducting manual QA checks before launching high-budget campaigns.
• On Gemini Integration: Industry practitioners view Gemini’s integration as a helpful guardrail. For years, Google Ads’ "Optimization Score" has been criticized for prioritizing spend over strategy. By focusing Gemini’s recommendations on creative asset quality and formatting alignment rather than just bidding increases, Google is offering a more practical, utility-driven application of AI.
• On Web-to-App Tracking: App marketing specialists have highly anticipated this update. In a post-App Tracking Transparency (ATT) world, tracking users across web-to-app pipelines has been incredibly difficult. Giving Demand Gen native capabilities to tie these journeys together helps mobile-first brands justify larger investments in Google’s web-facing inventory.

Strategic Implications for Advertisers and Agencies

The rollout of these Demand Gen features has broad implications for how marketing departments and advertising agencies allocate resources, structure their teams, and design their creative strategies.

                    ┌────────────────────────────────────────┐
                    │      Strategic Shift in Advertising    │
                    └───────────────────┬────────────────────┘
                                        │
         ┌──────────────────────────────┴──────────────────────────────┐
         ▼                                                             ▼
┌─────────────────────────────────┐           ┌─────────────────────────────────┐
│     From Technical Execution    │           │    From Fragmented Tracking     │
│  Manual resizing, cropping, and ├──────────►│  Unified attribution modeling,  │
│  formatting of video assets     │           │  web-to-app conversion pathways │
└─────────────────────────────────┘           └─────────────────────────────────┘

The Transition from Production to Strategy

As Google continues to automate asset adaptation (through resizing) and asset optimization (through Gemini), the role of the creative department is shifting. Instead of spending hours resizing, cropping, and exporting dozens of variations of a single ad, design teams can focus on core storytelling, high-quality production, and conceptual variation.

The value of a creative team will increasingly be measured by their ability to produce unique visual hooks and compelling narratives, leaving the mechanical formatting to Google’s automated systems.

Navigating Privacy-First Attribution

The introduction of Web-to-App Acquisition Measurement highlights Google’s commitment to first-party data and advanced modeling. As third-party cookies phase out and privacy regulations restrict cross-site tracking, advertisers must rely on platforms that can securely model user behavior across different environments.

By keeping the tracking within Google’s ecosystem (from Google search/display to Google Play or iOS App Store via Google-supported SDKs), Demand Gen provides a compliant way to preserve attribution accuracy without compromising user privacy.

Maximizing the Efficiency of Ad Spend

With the Measured data proving that nearly three-quarters of YouTube conversions represent new customers, brands can confidently use Demand Gen as an offensive growth tool.

Instead of treating YouTube purely as a top-of-funnel brand awareness expense, marketers can set concrete performance KPIs, confident that the combination of Gemini’s creative guidance and automated resizing will maximize the click-through and conversion rates of their video assets.

Conclusion: The Future of Programmatic Demand Generation

Google’s latest updates to Demand Gen demonstrate that the future of digital advertising lies at the intersection of generative AI, creative flexibility, and cross-channel measurement. By reducing the friction required to launch multi-format video campaigns and providing the attribution tools necessary to prove their worth, Google is making it easier for brands of all sizes to leverage the power of YouTube and its broader visual ecosystem.

For advertisers, the path forward is clear: those who embrace these automated creative workflows and unified measurement frameworks will be well-positioned to capture the next wave of consumer attention and drive meaningful, incremental business growth.