Today, I discovered some exciting news about Google’s expansion of Demand Gen with fresh YouTube creator tools. It’s all about enhancing performance advertising and was recently highlighted at Google Marketing Live 2026.
Here’s the scoop. Google has unveiled new updates for Demand Gen with a focus on partnerships with creators, innovative product discovery methods, and improved cross-platform campaign optimization.
As an advertiser, I soon will be able to:
Create engaging videos using the multimodal capabilities of Asset Studio.
Seamlessly integrate creator partnership videos during campaign setup.
Dynamically share Merchant Center product videos directly from campaign structures.
Include Demand Gen campaigns in Google Maps for increased outreach.
Google’s also pushing checkout links into more markets and expanding product feed support to new verticals, such as automotive. They mentioned that advertisers with vast product options tend to experience a 33% boost in conversions with product feeds.
Additional improvements in measurement include:
Campaign Type Attribution to understand source impact.
Uplift Experiments for deeper insights.
Enhanced third-party integrations with partners like TransUnion.
I also learned about Google introducing AI-assisted Demand Gen campaign creation, which uses existing campaign settings, like those from Performance Max, to simplify setup processes.
Understanding the mechanism. Demand Gen harnesses AI signals across YouTube, Discover, Maps, and Shopping to smartly allocate creative and product feeds amidst Google’s platforms. Advertisers, like myself, can leverage creator videos and Merchant Center product assets for more tailored campaigns responsive to user interest and engagement techniques.
The reason it’s noteworthy. Google’s tactic to pitch YouTube and Demand Gen as comprehensive performance channels shows a shift from just creating awareness. The merge of creator content, Maps inventory, and dynamic product experiences epitomizes the evolving intersection of discovery and commerce within Google’s ecosystem.
For us, the advertisers, these updates are a golden opportunity to marry creator-driven content with tangible conversion metrics.
What’s ahead. Google’s ongoing focus on creator tools and Demand Gen sets the stage for YouTube’s larger involvement in performance advertising plans. It’s essential to keep tabs on how Maps inventory and creator-led commerce campaigns may influence conversion performances.
When can we expect it? Many of these Demand Gen updates are globally expanding in open beta.
Want more insights? Check out more from Google Marketing Live 2026:
I’ve recently experienced frustrations with Google Ads as there’s a known issue causing Demand Gen ads to face review delays of over a week. Google acknowledges this problem and assures us that they’re working on a solution.
Some of us advertising on Google have noticed our ads are lingering in review, taking more than seven days—something that deviates from normal review timelines.
What’s happening. Matthew Skelton, a senior PPC specialist I follow, has pointed out a trending issue: Demand Gen campaigns stuck in review for an unexpectedly long time. This delay is noticeable across various accounts and industries, seemingly without any policy breaches causing it.
Interestingly, other campaign types, like Search and Performance Max, aren’t affected and continue processing as usual, which suggests the problem is isolated to Demand Gen ads.
Why we care. For those of us using Demand Gen to test creatives and drive top-of-funnel results, speed is crucial. Long review times hinder our ability to iterate swiftly, delay launches, and make it challenging to respond to seasonal trends or time-sensitive opportunities.
A delay lasting a week can disrupt our pacing and diminish the effectiveness of campaigns relying on rapid optimization.
The response. Ginny Marvin, a Google Ads Liaison, acknowledged this issue specifically impacting Demand Gen image ads, admitting reviews are taking longer than anticipated. She assured us that Google’s team is actively seeking a solution, but no clear timeline has been provided yet.
Bottom line. If you’re experiencing delays with your Demand Gen ads, know that it’s a widespread issue acknowledged by Google rather than something you can directly address.
First seen. This situation was first reported by Matthew Skelton, who shared his insights on LinkedIn.
I’ve been following the latest updates from Google, and it’s exciting to see how they’re enhancing Demand Gen tools. These updates are designed to help advertisers like me convert quicker and reach more new customers on platforms like YouTube.
What’s happening. Google has integrated Demand Gen into their Commerce Media Suite. This means I can now leverage retailers’ first-party catalog and conversion data to connect with high-intent shoppers across YouTube, Discover, and Gmail.
The introduction of view-through conversion (VTC) optimization is another great addition. It allows my campaigns to focus on conversions that occur after an ad is viewed—speeding up performance significantly.
Why we care. These updates enhance the effectiveness of Demand Gen by turning views into tangible conversions. By utilizing retailer data and optimizing for view-through activities, I’m able to engage high-intent users, even if they don’t immediately click. This results in faster outcomes and increased customer acquisition.
Between the lines. Google is now focusing beyond clicks, using richer commerce data and view-based attribution to generate results in more passive, discovery-rich environments like YouTube.
What to watch. I expect more exciting announcements about Demand Gen at upcoming events like Google Marketing Live. As YouTube evolves, it’s becoming a comprehensive performance channel.
Bottom line. With these updates, Google has transformed Demand Gen into a robust, data-driven machine for converting high-intent audiences—especially on YouTube.
I often find that platform reporting can lead me astray when trying to gauge the real impact of Demand Gen creative. To get a clear picture, conducting controlled experiments can validate if my creative work genuinely boosts conversions.
Demand Gen campaigns shine across YouTube, Discover, and Gmail, but they also bring a challenge—what I call the “attribution illusion.” It’s frequent for me to question whether reported conversions are truly incremental or if users would have converted through search regardless.
Google introduced asset uplift experiments in November, allowing me to measure the impact of my Demand Gen creative using an A/B split test. This feature helps replace assumptions with clearer insights into what’s truly driving results.
Relying heavily on creative instinct or standard reporting can misdirect efforts and waste valuable resources on underperforming assets. Google’s A/B testing capabilities empower me to isolate the impact of individual assets, preventing such outcomes.
Why attribution doesn’t equal incrementality
For example, if someone views a Demand Gen ad on YouTube but doesn’t click, only to search for my brand later and convert, Google might still credit the Demand Gen campaign. This attribution reflects correlation more than causation.
To measure accurately, I need to understand the scenario without showing the creative. Withholding test assets from a portion of the target audience helps establish a baseline.
The difference in conversion rates, or any key KPI between groups exposed to the ad and those not, reveals the actual incremental lift the creative drives.
Launching experiments without enough data for statistical significance is a common misstep. Before testing, I ensure campaigns meet necessary prerequisites to avoid inconclusive or invalid results.
Conversion volume
Google suggests having at least 50 conversions across test groups during the experiment for accurate lift measurement. If primary conversions fall short, I consider optimizing the test around micro-conversions like “Add to Cart.”
Budget minimums
Experiments require continuous, uninterrupted spending. A limited budget stopping my campaign early skews data for the control group.
The campaign budget must be sufficient to run for at least four weeks or until statistically significant results are achieved.
Creative isolation
I test one new variable at a time to determine if a specific asset drives uplift, keeping all other campaign elements unchanged.
Running a creative uplift test in Google Ads is now more streamlined. Here’s how I set up a valid experiment.
1. Define a clear hypothesis
Each scientific test starts with a clear hypothesis. I avoid tests without defined objectives. For example:
Bad hypothesis: “Let’s see if our new video works.”
Good hypothesis: “Adding user-generated content (UGC) to our Demand Gen asset group will drive a 10% incremental lift in ‘purchase’ conversions compared to standard static image carousels.”
Navigate to the Experiments interface
In my Google Ads account, I navigate to Campaigns > Experiments. I create a new experiment, selecting Asset tests provided by you for a Demand Gen campaign.
Configure a 50/50 split
I define a 50/50 cookie-based split to ensure both groups have equal historical data and algorithm weighting, preventing users from being in both test arms.
My existing campaign becomes the control, and the new asset campaign serves as the treatment.
Lock your variables
Once started, I practice extreme discipline by not altering audiences, targeting, or making drastic bid and budget changes.
Any changes during the test can introduce noise, affecting the statistical significance of results.
Set the duration
I run experiments for at least four weeks. Week 1 is a learning period, and Weeks 2 to 4 provide actionable data.
Longer conversion cycles in B2B SaaS might require six to eight weeks.
A positive lift with 95% confidence means my creative asset adds real value. I calculate incremental cost per acquisition (iCPA) by dividing the treatment group’s ad spend by incremental conversions over the control.
This iCPA becomes my benchmark for further scaling.
Outcome 2: Negative lift
Creatives may underperform, perhaps being too disruptive or skipped in ads. Pausing these assets is crucial to let data direct budget choices over personal preference.
Outcome 3: Inconclusive result
If results are negligible and don’t confidently attribute conversions after four weeks, I might extend the test for more data. If still inconclusive, trying a drastically different creative asset is my next step.
Prove creative impact with incrementality testing
Creative remains a powerful differentiator for performance. Creating high-quality video or UGC is one thing, but proving its impact with scientific rigor strengthens my creative decisions.
Asset uplift experiments provide evidence of Demand Gen’s budget worthiness to stakeholders. When I start with a holdout test, establish a baseline, and let data guide my creative roadmap, the results speak for themselves.
I just discovered that Google Ads has given the Asset Optimization layout for Demand Gen a sleek makeover. The updated panel enables advertisers like me to easily streamline creative formatting and placement through a few toggles.
Why we care. If you’re managing a large volume of creative, this central panel makes life much easier. It reduces manual labor by allowing us to enable or disable automation features quickly.
What’s new. This layout refresh organizes three main automation features into a more user-friendly interface:
Auto-generated shorter videos let AI trim existing videos for broader placements.
Automatic video resizing ensures our videos fit multiple aspect ratios, optimizing for wider coverage.
How it works. The new panel displays simple toggles like Resized videos and Image assets, making it straightforward for us to activate or deactivate each feature without sifting through several submenus.
Bottom line. If you’re running Demand Gen campaigns like me, it’s time to dive into the Asset Optimization panel and review which automations are turned on. Don’t miss out on features like video resizing and landing page image pulls as they can expand your reach effortlessly.
And, ensure your landing pages are visually appealing; Google will draw directly from them. As more AI tools roll out, I’m shifting my workflow to focus on high-quality source assets and letting Google handle the optimization of formats and placements.
I’ve discovered that shifting toward Demand Gen in Google Ads transforms the focus from simple keyword targeting to more visually-driven advertising. Relying on outdated methods not only wastes money but also limits the potential of what Demand Gen can achieve. To thrive, I need to see things like a social advertiser rather than just a search advertiser.
At SMX Next, Jack Hepp from Industrious Marketing shared valuable insights on why many businesses, particularly in the B2B sector and lead generation, find demand gen campaigns challenging, while also providing strategies that are applicable to ecommerce.
In transitioning to Demand Gen, I see Google’s move from intent-driven to discovery-focused campaigns. This involves reaching users casually browsing on platforms like YouTube, Gmail, or Discovery feeds rather than those actively searching for my offerings. This approach means that visual assets now play the role that keywords once did.
Aligning campaign strategies to fit this model requires abandoning old tactics. Here’s what I need to avoid:
Expecting bottom-of-funnel CPAs from mid-funnel traffic.
Employing imprecise, broad targeting.
Running dull, uninspired creative.
Lack of optimization know-how without negative keywords.
Seeing success demands that I adopt a mindset similar to social advertising.
Demand Gen structure consists of campaigns governed by broad parameters (like bidding strategies and conversion goals) and ad groups that dictate audience specifics. Each ad group learns independently, which allows for finely tuned audience segmentation.
When crafting interruption-based creative, my goal is to catch attention in the first 3-4 seconds. It’s about highlighting a specific pain point and offering a solution in a way that turns casual browsers into engaged prospects.
Ensuring my visual content aligns with the customer journey is crucial:
Cold audiences benefit from educational material.
Warm audiences engage with case studies and webinars.
Hot audiences are ready for demos or purchase offers.
When my creative addresses specific problems with bold visuals and compelling headlines, the engagement naturally increases. For instance, targeting specific challenges like cybersecurity for small businesses makes my ads stand out.
Bidding in Demand Gen focuses on campaign-specific goals. To gather the necessary data, I aim for significant monthly conversions and budget accordingly to enable optimal performance.
Even small budgets can work if strategically planned. By directing efforts at mid-funnel activities, I can achieve the necessary conversions for meaningful insights.
In building the right audiences, it’s about balance. I avoid extremes of too broad or too narrow segments and focus on custom segments complemented by lookalike data, optimizing as success dictates.
Aligning the messaging of my creative with the buyer’s stage ensures Google effectively targets potential customers. This strategy steering focuses more on creative, audience, and the offer itself.
Using targeted exclusions efficiently helps me concentrate effort on engaging users without overly restricting potential reach. It’s a strategic rather than blanket approach.
Optimization in Demand Gen focuses on creatively testing different formats and refining audience targeting. I continually test offers to match audience readiness and optimize post-click experiences to enhance campaign effectiveness.
In a real-world application, a telecommunications company achieved impressive outcomes by clearly defining its offer, targeting, and creative messages. The results highlighted the critical importance of aligning these elements for Demand Gen success.
Here are the key takeaways for any campaign I plan next:
Align creative content with my target customer’s stage in their journey.
Identify and target audiences at appropriate points in their journey.
Continuously test and refine both creative elements and offers to amplify impact.
I’ve noticed some exciting changes coming to Google Demand Gen campaigns. Starting in March 2026, Lookalike audiences will no longer be the rigid framework we’re used to. Instead, they’ll serve as optimization signals, ushering in a new era of AI-driven campaign enhancements.
Google is updating its Help documentation to reflect this transformation where Lookalike segments shift from strict targeting to a more flexible, AI-enhanced recommendation model.
Understanding the Transition. Previously, I would choose a specific similarity tier (narrow, balanced, or broad) to dictate exactly who my campaigns targeted. That’s changing.
Now, Google will use these tiers as signals. The system will intelligently expand its reach beyond my chosen Lookalike lists to engage users predicted to convert.
Behind the Change. This transition turns Lookalikes from a barrier into an enabling tool. It allows Google’s automation to use intent signals to explore audience performance well beyond predefined limits.
Interaction with Optimized Targeting. The new Lookalike-as-signal approach resembles Optimized Targeting but doesn’t replace it. When they’re layered, Google mentions it could further expand my reach.
In practice, this means multiple automation signals will be at play, providing the algorithm more freedom to either reduce CPA or boost conversion rates.
Opting Out. If I prefer the traditional Lookalike approach, I can opt out via a dedicated form, preserving the old targeting behavior. Absent that, campaigns automatically switch to the new format.
Why This Matters. This update affects the control I have over ad targeting in Google Demand Gen campaigns. Lookalike audiences will now guide rather than confine targeting, significantly influencing scale, CPA, and performance.
Additionally, it indicates an industry-wide move toward automation, similar to shifts driven by Meta Platforms. I’ll need to test thoroughly, rethink strategies, and decide whether to embrace the added reach or opt out for tighter targeting.
Industry Context. Google’s strategy echoes a broader trend toward AI-first audience expansion, aligned with similar adaptations from Meta in recent years. The advertising landscape is increasingly prioritizing machine-led optimization over detailed manual control.
The Reasoning. According to digital marketer Dario Zannoni, there are two main reasons for Google’s shift:
Stringent Lookalike targeting can limit scale and hinder performance in conversion-focused campaigns.
The complexity of maintaining high-quality similarity models makes automation a more viable option.
The Bottom Line. For performance marketers like me, this marks another step towards automation-centric strategies. Reduced control might be daunting, but similar platform changes have historically yielded performance gains. A fresh testing cycle is on the horizon as I examine the impact of expanded Lookalike signals on CPA, reach, and conversions.
Observed and Shared. Dario Zannoni initially highlighted this update on LinkedIn.
I’m excited to share that Google’s Demand Gen updates are making video ads even more shoppable and measurable across platforms like YouTube and Google. With these enhancements, I can now explore new ways to engage with audiences and increase conversions.
Google is pushing more Demand Gen features into mainstream use, particularly boosting shoppable and travel ads. It’s clear to me that Google is committed to creating a comprehensive performance channel, merging discovery, video, and commerce on both YouTube and Google surfaces.
What’s new:
Shoppable CTV is now available through Demand Gen, giving viewers the option to browse and purchase products directly from YouTube ads on connected TVs. It’s a game-changer for anyone looking to enhance their advertising strategy.
Attributed Branded Searches provide advertisers, like me, with insights into how campaigns influence brand search activity on Google and YouTube. Activation requires a Google rep, and it’s a feature that promises to add tremendous value.
Travel Feeds let advertisers like me connect Hotel Center feeds to create dynamic video ads featuring real-time pricing, ratings, and availability.
By the numbers:
According to Google, Demand Gen campaigns featuring TV screens result in 7% more conversions at the same ROI. That’s a significant increase in performance for anyone leveraging these tools.
For example, LG Electronics reported a 24% higher conversion rate compared to paid social media, while reaching high-value customers at a 91% lower CPA.
Why we care. With these updates, Demand Gen becomes more competitive with paid social channels, offering actionable and measurable solutions. Shoppable CTV transforms TV impressions into direct sales opportunities, while attributed branded search proves Demand Gen’s effectiveness beyond a simple last-click model. Travel feeds, on the other hand, streamline the process from browsing to booking.
All these features offer advertisers like me the chance to drive incremental conversions, engage high-value audiences at a lower CPA, and better justify upper-funnel investments with clearer performance metrics — all within Google’s integrated ecosystem.
Between the lines. It’s evident that Google is positioning Demand Gen as a formidable alternative to paid social by utilizing premium video resources, first-party data, and enhanced measurement. This move is particularly strategic as advertisers seek scalable performance beyond traditional social media platforms.
Bottom line. With advancements like shoppable CTV, reinforced brand attribution, and travel-focused automation, Demand Gen is evolving into a versatile performance tool — a significant aspect of Google’s strategy to secure larger budgets higher up the advertising funnel.
When Google introduced Demand Gen campaigns in 2023, I saw them as a promising way to boost engagement across platforms like YouTube, Discover, and Gmail.
Initially, they felt experimental, straddling the line between awareness and performance, but they’ve come a long way since.
Now, the creative flexibility and enhanced audience control make Demand Gen a go-to campaign type for my ecommerce clients.
This strategy allows me to scale revenue in a controlled manner, maintaining brand consistency while testing creative approaches to drive conversions.
I’ve found that Demand Gen delivers the best results when strategically paired with Performance Max and Search campaigns.
Advertising with Demand Gen is ideal if you crave more control.
One major drawback of Performance Max is its lack of transparency and manual control.
If precise targeting, placement, or creative control is essential, Demand Gen stands out as the better option.
Performance Max auto-generates ads from your uploads, relying on Google’s AI to mix and match for the best performance.
This makes it crucial to provide top-notch creative assets.
For example, a fitness brand might create separate asset groups for products like leggings, shorts, and vests.
While this helps target relevant audiences, the control isn’t exhaustive.
However, Demand Gen offers far superior flexibility.
It allows me to upload, preview, and tweak ad combinations before launch, adapting each creative to its unique placement.
For instance, I can customize YouTube ads for in-feed, in-stream, and Shorts placements.
This control is perfect for ecommerce brands focusing on creative precision, message testing, and maintaining a strong visual identity.
Using Demand Gen alongside Performance Max can be incredibly effective if you leverage their roles within the customer journey. They enhance each other rather than compete.
Demand Gen builds awareness and sparks interest by reaching higher-funnel audiences before they actively start product searching.
Conversely, Performance Max focuses on converting lower-funnel users who are primed to purchase.
For example, a fitness retailer might utilize Demand Gen for lifestyle videos and discovery ads promoting their latest activewear.
When a potential customer begins to research or exhibit purchase intent, Performance Max engages with tailored Shopping and Search ads to finalize the sale.
I’ve set up feed-only Performance Max campaigns, providing only a product feed within the asset group.
This restricts Performance Max activities to Shopping placements, focusing it sharply on direct conversions.
Meanwhile, Demand Gen operates across platforms like YouTube, Gmail, Discover, and Shorts, covering the upper and mid-funnel with more visual, creative content focused on awareness.
This configuration minimizes overlap between campaign types while ensuring user engagement throughout the funnel, from brand discovery to purchase.
For larger accounts with flexible budgets, this dual structure drives holistic performance and clearer attribution.
In contrast, smaller accounts seeking efficiency should prioritize mastering high-intent campaigns before layering in Demand Gen once the core conversions are stable.
The diverse campaign types now offer advertisers more flexibility than ever, yet it requires understanding Google’s restructuring of video and discovery products.
It streamlines Google’s visual placements into one campaign type, including YouTube in-stream, Shorts, in-feed, Gmail, and Discover.
This change is significant. VAC was successful for ecommerce, particularly for conversion-centric video. Its removal underscores Google’s encouragement to embrace Demand Gen.
The advantage is that Demand Gen provides stronger creative control and diverse testing options across YouTube placements.
If you previously ran VAC campaigns, they are now under Demand Gen. Ensure your top-performing assets and audiences have migrated correctly, then use the new controls to optimize performance.
Audience control is a significant benefit of Demand Gen, and it’s a reason why I consistently use it for ecommerce.
Demand Gen allows precise audience creation, letting me decide who sees the ads.
I can select placements, merge audience types, and allocate the budget strategically.
It’s the only Google Ads campaign type supporting lookalike audiences, valuable for brands focused on acquiring quality leads.
While Performance Max utilizes audience signals over fixed targeting, Demand Gen excels for control, testing, and segmentation strategies.
In mid-2025, Google rolled out an open beta for advertisers to opt out of specific Demand Gen channels manually.
This means I can now control ad display, excluding Discover or YouTube Shorts if they don’t align with my objectives or creative format.
This small but significant update offers more control, a feature often lacking in many of Google’s automated campaign types.
In early 2025, Google introduced product feed integration for Demand Gen campaigns. This change allows me to link the Google Merchant Center feed, incorporating live product data directly into visual ads.
This development bridges performance and branding for ecommerce, enabling storytelling through creative visuals while displaying actual products.
For instance, a fashion retailer can showcase a new collection in a video advert while featuring shoppable product cards below.
This update positions Demand Gen as a hybrid between Shopping and Display, a much-anticipated capability among ecommerce advertisers.
Demand Gen typically demands a larger budget than other campaign types.
Google recommends starting at about £100 per day per campaign or 20 times your target CPA/tROAS, whichever is higher.
Practically, the £100-per-day baseline is a viable starting point for effective data collection and optimization. Lower budgets restrict data flow and slow progress.
Demand Gen complements your broader Google Ads strategy, rather than replacing Search or Performance Max.
It’s a premium, visually led campaign type that boosts awareness leading to conversions, particularly effective when you have accurate measurement, a clean product feed, and clearly defined audiences.
The table compares Demand Gen and Performance Max on key aspects that matter to advertisers.
