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Google’s Display Ads are dead – here is what replaces them in 2026

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By Luis Rijo

Google is phasing out standalone Display Ads campaigns and folding the Google Display Network into Demand Gen, with a migration tool launching in June 2026.

Google last month confirmed that standalone Display Ads campaigns are being retired, with the Google Display Network folded into Demand Gen as the new unified home for visual advertising across more than 2 million sites, videos and apps. A phased migration tool is now rolling out, and the full transition is expected to complete by 2027.

What is actually changing

The announcement, published on May 26, 2026 on the Google Ads and Commerce Blog, marks the end of Google Display Ads as a standalone campaign type. According to Google, advertisers can now manage their Google Display Network (GDN) presence directly through Demand Gen campaigns. The campaign creation workflow changes, but the underlying network remains unchanged – the same inventory of more than 2 million sites, videos and apps remains accessible.

The move is significant in scale and in what it signals. Display Ads have been part of Google’s advertising infrastructure for well over a decade. Folding them into Demand Gen is not a minor interface update. It is a structural consolidation that changes how advertisers set up, manage, and report on their display activity going forward.

What remains available? Advertisers who want to serve ads exclusively on GDN can still do so. According to Google’s Help Center documentation, customers looking for Display-only campaigns can continue purchasing them within Demand Gen using channel controls – a feature that lets advertisers isolate specific placements. The difference is that the campaign shell itself is now Demand Gen, not a standalone Display campaign.

The migration tool and how it works

Google is launching a phased rollout of its migration tool in June 2026. Eligible advertisers can begin moving existing Google Display Ads campaigns to Google Display Network on Demand Gen using the tool directly inside their Google Ads account.

The tool is the recommended path. According to Google’s Help Center, it allows advertisers to update live campaigns with performance history going back 42 days ported over to the new campaign. That historical data transfer reduces learning time to approximately 1 to 2 days and avoids a “cold start” – the period during which Google’s bidding models lack sufficient data and can underperform. The alternative is a manual budget transition, where advertisers gradually shift spend from existing Display campaigns to Demand Gen by decreasing budgets on the former while proportionally increasing them on the latter.

The step-by-step process inside Google Ads involves navigating to the Campaigns menu, filtering by campaign type for “Display,” selecting the campaigns to migrate, then choosing “Upgrade to Demand Gen” from the Edit dropdown. The migration can handle multiple campaigns simultaneously, though Google does not recommend batches of more than 100 campaigns at a time.

A few technical details matter here. Migrated campaigns will be renamed following the convention “[Original campaign name] #2.” The original Google Display Ads campaigns are not deleted – they are set to “Removed” status and remain in the account for reporting purposes for up to five years under Google Ads’ standard retention policy. Advertisers running lift measurement studies – such as Conversion Lift – are advised not to use the migration tool while a study is active, because the converted campaign will not be automatically associated with the ongoing study.

Budget handling on migration day carries a specific wrinkle. According to Google’s documentation, any budget spent earlier in the day on the Google Display Ads campaign will not be recognised by the new Demand Gen campaign. If a campaign has spent $10 of a $50 daily budget before migration, the new Demand Gen campaign resets and starts with the full $50 for the remainder of the day. Temporary underdelivery or overdelivery is possible within the first 24 hours.

Performance claims and real-world data

Google is citing two sets of numbers to support the migration. On average, according to the announcement, advertisers adding GDN in Demand Gen campaigns see a 9.5% increase in return on investment (ROI). The company also pointed to GoFood, a food delivery platform, as a case study. According to Google, GoFood saw a 24% decrease in cost per acquisition (CPA) and a 19% higher conversion volume after adding GDN to its Demand Gen campaigns.

These figures come from Google’s own data and should be read in that context. The 9.5% ROI improvement and GoFood case study reflect conditions that may not transfer uniformly across industries, account sizes, or competitive environments. Advertisers who have relied on standalone Display campaigns for years will need to test and monitor performance independently after migration, particularly during the first several days when fluctuations are expected.

Feature changes: what is gained and what is lost

The move from Google Display Ads to GDN in Demand Gen involves a meaningful shift in feature availability. Not everything carries over directly, and some capabilities available in Display Ads are not available in Demand Gen.

On the inventory side, Demand Gen expands reach beyond what Google Display Ads offered. Where Display Ads ran across GDN, YouTube, and Gmail, Demand Gen adds Discover and Maps (Maps currently in beta). The ad surfaces available expand from three to five, giving advertisers who opt into them a broader footprint.

Creative formats also expand. Google Display Ads supported Responsive Display Ads, uploaded Display Ads (image ads, HTML5, GIF), and product feeds from Google Merchant Center and Business Data Feeds. Demand Gen adds carousel ads, generative image tools, a wider range of video ad formats, and HTML5 (described in the documentation as “coming soon” for GDN in Demand Gen). GIF support, however, is not listed among the available formats in Demand Gen.

On the audience targeting side, the transition introduces Lookalike segments as a replacement for Similar Audiences. Lookalike segments allow advertisers to reach new users who share characteristics with existing customers. The core targeting options – optimised targeting, remarketing lists, custom segments, first-party data, interest, demographics, and contextual targeting – remain available in both formats.

Bidding changes in specific ways. Manual CPC, Viewable Impressions, and Pay for Conversions are not available in Demand Gen. What replaces them are Max conversions, Max conversion value, tCPA, tROAS, Max clicks, and a new option called tCPC (target cost per click). Demand Gen also introduces Flighted Campaign Total Budgets, which are not available in Google Display Ads.

Pay for Conversions campaigns specifically are handled by the migration tool automatically. According to the documentation, these campaigns will be switched to pay for clicks, while continuing to use target CPA to optimise for conversions at the advertiser’s stated target.

Reporting gains one notable capability in Demand Gen: format segmentation reporting. This breaks down performance data at the format level, including In-Feed, Skippable In-Stream, and Shorts, giving advertisers visibility they did not have within standalone Display campaigns.

Logos and business names are pre-populated from existing Google Display Ads campaigns during migration. If a Display Ads campaign lacks a logo, the migration tool creates a placeholder image to ensure continuity. Advertisers can edit this after migration completes.

Key dates and what comes next

The timeline for this migration has three stages, according to Google’s Help Center documentation.

June 2026: The phased rollout of the migration tool begins. Eligible advertisers can start moving existing Google Display Ads campaigns to GDN on Demand Gen using the tool in their Google Ads accounts.

Coming later (no specific date provided): New Google Display Ads campaigns can only be created within Demand Gen. Advertisers can still access and edit existing Display Ads campaigns until they are migrated.

Coming later (no specific date provided): Remaining eligible Google Display Ads campaigns will be automatically migrated to GDN on Demand Gen without any advertiser action required.

The full migration is expected to complete by 2027. Google has said it will provide account notifications in Google Ads as key dates approach.

Where the money goes – and does not go

There is a dimension to this migration that sits outside the migration checklist: the question of who ultimately benefits from ad spend flowing into Demand Gen rather than standalone Display, and how the balance between Google-owned and publisher inventory shifts in the process.

Google Display Ads – the format being retired – ran by default across the Google Display Network, a third-party publisher ecosystem spanning more than 2 million sites and apps. When an advertiser ran a Display campaign and ads served on an external publisher’s website, a portion of that revenue was shared with the publisher via AdSense or Google Ad Manager. That revenue-sharing model has underpinned publisher monetisation across the open web for over a decade.

Demand Gen has a more layered inventory structure, and understanding it requires separating the surfaces available within the campaign type. The primary surfaces in Demand Gen – YouTube, Discover, Gmail, and Maps – are all Google-owned properties. Discover is Google’s personalised content feed. Gmail is Google’s email service. Maps is Google’s navigation product. According to PPC Land’s analysis of Demand Gen placements, unlike traditional YouTube ads where Google must split revenue with video creators, Demand Gen placements on surfaces like Discover and Gmail allow Google to retain a larger portion of advertising revenue. Those surfaces carry no revenue share obligation to external publishers.

GDN is also available within Demand Gen – but the mechanics are different from how standalone Display Ads worked. In a standard Display campaign, GDN was the entire network, and every impression served on a third-party publisher site generated revenue for that publisher. In Demand Gen, GDN is one channel among several, accessed via explicit channel controls at the ad group level. The default campaign configuration points spend toward YouTube, Discover, Gmail, and Maps. Advertisers who want GDN inventory must actively opt into it. That shift from default to opt-in is consequential at scale.

In Display & Video 360, the distinction is encoded directly into the reporting infrastructure. According to PPC Land’s coverage of DV360’s granular inventory controls, the standard Inventory Source reporting dimension labels YouTube, Discover, and Gmail traffic as “Google Owned Properties,” while GDN traffic appears separately as “Google Display Network.” Google itself maintains that boundary in its own systems – a clear delineation between inventory where revenue stays with Google and inventory where a share flows to external publishers.

The financial trajectory of Google’s Network advertising segment – the one that pays out to publishers – makes the stakes concrete. Google’s advertising revenue distribution reached a point in mid-2025 where 90% of revenues were flowing to its own properties rather than through publisher partnerships, according to PPC Land’s analysis following Alphabet’s Q2 2025 earnings. Network advertising revenue – covering AdSense, AdMob, and Google Ad Manager – declined 1% year-on-year to $7.4 billion in Q2 2025. By Q1 2026, that figure had fallen further to $6.97 billion, a 4% year-on-year drop of approximately $285 million in a single quarter, according to PPC Land’s coverage of Alphabet’s earnings release.

The Display Ads migration adds structural momentum to that decline. In standalone Display campaigns, GDN publisher inventory was the default and the entire point of the campaign type. In Demand Gen, GDN is an optional channel that requires a deliberate activation step. Every advertiser who migrates without explicitly enabling GDN via channel controls will, by default, direct their visual advertising spend toward Google-owned surfaces where no publisher revenue share applies. Budget that previously flowed to external websites through AdSense now flows to YouTube, Discover, Gmail, and Maps instead.

Google’s Network ad revenue decline has also been attributed in part to AI Overviews reducing click-through rates from search results, which reduces traffic to publisher sites and therefore ad impressions served through AdSense and Ad Manager. The Display migration applies pressure from a different direction: it reduces the share of advertiser display budgets that flow to external publishers, independent of what happens to search traffic volumes.

GDN inventory remains technically available inside Demand Gen, and publishers on the network can still earn revenue from advertisers who opt in. That is the honest limit of the claim. But the structural change is real: the campaign type that made GDN the default has been retired, and the one replacing it treats GDN as an elective channel within a portfolio that tilts heavily toward Google’s own properties.

Why this matters for the marketing community

This consolidation is one of several structural moves Google has made to reduce the number of distinct campaign types in its advertising platform. The retirement of YouTube Video Action campaigns in favour of Demand Gen completed by April 2025, and Demand Gen was expanded to Display & Video 360 in October 2024. The pattern is consistent: Google is reducing campaign-type fragmentation and concentrating activity inside a smaller set of formats built around its AI-driven bidding and creative tools.

Google quietly removed Display and Video campaign support from Performance Planner on March 9, 2026, eliminating the ability to model those campaigns in its forecasting tool. Taken together with the Display migration announcement, the signals from Google have been clear for months. Standalone Display infrastructure is being wound down.

The Google Marketing Live 2026 announcements in May included Demand Gen’s expansion to Google Maps with Promoted Pins, and further AI-assisted campaign creation tools – all pointing toward Demand Gen as the primary canvas for visual advertising across Google’s owned-and-operated surfaces.

For advertisers, the operational consequences are real. Campaigns that have accumulated years of performance history inside Google Display Ads will need to be migrated. The migration tool attempts to transfer 42 days of historical data to ease the transition, but the learning reset is not zero – performance fluctuations within the first several days are explicitly flagged by Google’s own documentation. Advertisers running lift studies or time-sensitive campaigns will need to plan the migration window carefully.

The removal of Manual CPC and Pay for Conversions bidding in Demand Gen will also require workflow changes for teams that have built their optimisation processes around those options. February 2026 changes to how Lookalike segments function in Demand Gen – converting them from hard targeting constraints to audience suggestions – had already altered the audience control model. The Display migration adds another layer to the adjustment.

Advertisers who re-approve migrated ads should expect them to go through the standard approval process. According to Google, migrated ads are treated as newly created ads regardless of how they are transitioned, which means they must be submitted for approval before they can serve. This is particularly relevant for advertisers planning to migrate close to a campaign’s scheduled start date.

What best practices say

Google’s Help Center outlines recommended steps for advertisers using the migration tool. On channels, the guidance is to keep GDN-only selected in channel controls during migration to ensure a proper campaign setting transfer – additional channels like YouTube and Gmail can be added after the migration is complete.

On audiences, Google recommends replicating the audience approach from comparable Display campaigns and testing Lookalike segments. On bidding, the advice is to try similar bid levels to existing Display campaigns, set the conversion attribution window to more than 28 days, and limit bid changes to no more than plus or minus 15% – waiting at least a week between adjustments.

On creative, Google recommends expanding the number of assets, including a business logo and video assets. According to the documentation, this allows ads to scale across the widest possible range of inventory slots, which typically leads to stronger overall performance.

Campaign consolidation is also advised: combining similar audience themes across ad groups, and considering merging ad groups with fewer than approximately 30 conversions in 30 days. A consolidated campaign structure allows Google’s AI to learn more efficiently.

Timeline

Summary

Who: Google, affecting all advertisers currently running Google Display Ads campaigns globally, announced via the Google Ads and Commerce Blog.

What: Google Display Ads campaigns are being retired as a standalone campaign type. The Google Display Network is being folded into Demand Gen as the unified home for visual advertising, expanding the available ad surfaces from GDN plus YouTube and Gmail to also include Discover and Maps. A migration tool is launching in June 2026 to help advertisers transfer existing campaigns, with 42 days of performance history ported over. The full migration is expected to complete by 2027.

When: The announcement was published on May 26, 2026. The migration tool rollout begins in June 2026. A future date – not yet specified – will prevent the creation of new standalone Display Ads campaigns. A second future date will trigger automatic migration of all remaining Display campaigns.

Where: The change applies to Google Ads globally. Advertisers manage the migration from within their Google Ads accounts. Google Display Network inventory – more than 2 million sites, videos and apps – remains available via Demand Gen campaigns after migration.

Why: Google frames the migration as a response to shifting consumer behaviour and a push toward more unified campaign management. The consolidation aligns with a multi-year pattern of reducing standalone campaign types: Video Action Campaigns were absorbed into Demand Gen by April 2025, Display was removed from Performance Planner in March 2026, and Google Marketing Live 2026 confirmed Demand Gen as the primary vehicle for visual advertising across Google’s owned-and-operated surfaces. Advertisers adding GDN in Demand Gen campaigns see on average a 9.5% ROI increase, according to Google’s own data.

By Luis Rijo

Luís Rijo is a seasoned marketing professional with over 10 years of experience in Digital Marketing,  Search, Social, Display, Video, and DOOH. Based in Europe. Also writing in the spend. Reach out via [email protected]

Sourced from PPC Land

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The AI-Driven Marketing Playbook Reshaping Modern Retail

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By Al Sefati

Retail marketing has changed drastically in recent years. Consumers no longer discover brands only through search ads, visiting stores or browsing social media. Today’s shoppers move from Google, TikTok, marketplaces, AI assistants, review platforms and influencer content before buying anything.

This change has created both a challenge and opportunity for retailers.

Many times, the most successful brands don’t carry the biggest advertising budgets. They are the ones connecting digital ecosystems including SEO, AI visibility, paid media, AI automation, reputation management and customer retention into one strategy.​

The Customer Journey Is No Longer Linear

The traditional retail funnel is no more. Customers no longer move from awareness to consideration to purchase. Instead, they jump between devices, apps, AI assistants, marketplaces, reviews and social channels in a fragmented buying journey.

Someone shopping for sneakers might find a product on TikTok, search Google for reviews, ask ChatGPT for alternatives, compare prices on Amazon and then finally make a purchase after seeing a retargeting ad days later.

This behaviour applies to all retail segments. Visibility alone is no longer enough. Retailers must have consistency across every digital touchpoint.

SEO Has Expanded Into AI Visibility

SEO still matters, but retail brands are now competing for visibility inside AI-generated answers, not traditional rankings. Platforms like ChatGPT, Gemini, Perplexity and Google AI Overviews are changing how consumers research products.

Instead, customers are asking conversational questions like, “What are the best sustainable clothing brands?” or “Which standing desk is best for small apartments?”

This is where answer engine optimization (AEO) and generative engine optimization (GEO) enter the picture. To capture the visibility retailers need, AI-generated responses need fast websites, strong product data, new content, authentic reviews and FAQ-driven pages.

Brands relying only on traditional SEO tactics are becoming invisible in AI-driven searches.

AI Automation Is Becoming Essential

AI is rapidly becoming one of the biggest competitive advantages in retail.

Retailers are using AI to automate customer support, product recommendations, CRM automation, email and SMS workflows and lead qualification, among other things. From what I’ve seen, this doesn’t just reduce manual work; using AI improves speed, personalization and scalability across the business.

In my experience, companies are moving beyond experimentation and focusing on operational AI systems that directly improve efficiency, customer experience and revenue growth.

AI automation is a differentiator for businesses in a crowded market.

Product Pages Have Become Conversion Hubs

One of the biggest mistakes retailers still make is treating product pages like static catalogues.

Modern product pages must function as full conversion environments, meaning they include customer reviews, FAQ sections, rich media, shipping transparency and user-generated content. AI systems are pulling directly from these pages when generating recommendations. Pages with thin or repetitive content lose visibility and trust.

Retailers I’ve worked with who invest in detailed, conversion-focused product pages tend to see stronger organic traffic and higher conversion rates simultaneously.

Reviews And Reputation Influence Discovery

Reviews no longer only influence conversions. They now influence visibility. Search engines and AI evaluate trust signals across Google Reviews, Trustpilot, Reddit, YouTube, TikTok and other marketplace ratings.

Peer validation always beats polished advertising. That is why modern retail brands are investing heavily in review acquisition, social proof and real customer experiences.

From what I’ve seen, brands generating authentic customer conversations online tend to perform better in both search visibility and conversion rates.

Retail Marketing Is No Longer Just About Driving Traffic

Retail marketing in 2026 is not about simply driving traffic. The focus is now on visibility across search engines, AI platforms, marketplaces and social ecosystems. ​

Growing brands are the ones creating connected systems that combine modern SEO, AI visibility, paid media, AI automation, customer trust and operational speed into a unified strategy. Retailers that are still relying on disconnected tools and outdated marketing playbooks risk becoming increasingly invisible in the modern digital buying journey.​

Feature image credit: Getty

By Al Sefati

COUNCIL POST | Membership (fee-based)

Al Sefati is an enterprise SEO, AEO\GEO, and digital marketing expert, and CEO of Clarity Digital with over two decades of experience. Read Al Sefati’s full executive profile here. Find Al Sefati on LinkedIn and X. Visit Al’s website.

Sourced from Forbes

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Google Rewrote The Rules Of Search, And Many Marketers Haven’t Noticed

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By John Readman

Google announced a shift in how search works after more than 25 years of relative stability. It confirms what agencies like us have been telling clients for months: that Google is now an AI engine. From a familiar search box to AI Mode, the way online searches happen has changed.

​What Exactly Has Changed?

AI Mode and AI Overviews have been rolled further into Google Search, shifting the experience from a list of links to a synthesized response layer built on top of traditional search results.

The most visible change is, of course, the search box. Relatively unchanged for decades, Google now prompts users directly into new AI-led features. Instead of just autocomplete suggestions, users are now offered routes into Gemini models, image and document uploads, and conversational prompts in a way that mirrors ChatGPT. Not only that, but Google now actively encourages long-form conversational queries rather than short keyword-based searches. The search engine is adapting to user behaviour in a way it never has before.

Other Shifts You May Have Missed

Alongside the update to search, Google also shared insights into how people in the U.S. are using AI Mode. Voice and image searches now account for more than one in six searches overall, with image searches growing over 40% month over month. The shift to more conversational search also has become evident, with the average AI Mode search being three times as long as a traditional search query. Perhaps most interesting is the reported 80% increase in “queries related to planning” over the last six months.

​In other words, many people aren’t using AI Mode to answer a question; they’re using it to achieve an outcome. They’re asking real questions that they might have asked a person before. These are queries that may have multiple stages and multiple constraints requiring consideration. Instead of asking questions about a holiday destination (e.g., “best time to visit Paris,” “best hotels in Paris,” “best restaurants near Pigalle”), people are using AI Mode to plan entire trips, with queries that look something like this: “I have a $2,000 budget, I’m free in July or August, I love art, plan me a week visiting Paris.”

​What Do These Changes Mean For Brands?

The entire user journey can now take place within a search engine. A 2024 study by SparkToro found that zero-click searches accounted for 58.5% of all U.S. Google searches. Google’s search revolution means that number is probably going to get much, much higher.

The shift is designed to make users’ lives more convenient, but it could make yours a lot harder. As AI agents bring more interactions away from your site and centralize them within search engines, the typical ways we track and analyze user data have to change. We no longer can rely on website sessions, UTM codes or clean user click journeys, making your current attribution model largely obsolete.

​What Should You Do About It?

While Google’ overhaul represents a new phase in how we view user journeys, build our brand presence online and measure success, the fundamentals of search are still the same. Google still values good quality brands that understand their customers, and are trusted by others—it has simply developed more sophisticated signals that can meet the needs of evolving user expectations and behaviours.

Here are some ways to start adapting:​

Unify Organic, Paid And AI Search Strategies

Stop treating organic, paid and AI search as separate channel conversations. Visibility is shifting from channel silos to a unified system. AI synthesizes information from multiple sources, so public relations, SEO, paid media and content all feed the same underlying entity signal.

Stop Focusing On Rankings, And Optimize Your Brand Entity

Visibility is shifting from pages to entities, so your brand, products, leaders and locations need consistent signals across the web. AI doesn’t just pick one ranking URL; it pulls and synthesizes information from across sources to fully understand your brand.

Stop Separating AI And GEO; Embed Them

There is no separate strategy for AI search. Answer engine optimization (AEO) and generative engine optimization (GEO) are essentially just SEO applied to an AI surface. Google still rewards helpful, structured and authoritative content, but now puts more emphasis on clarity and extractability.

Start Measuring Causal Outcomes, Not Clicks

AI search and zero-click environments mean users can be influenced without ever visiting your site. Click-through rates and sessions alone don’t show the full picture anymore. Instead, focus on things like brand lift, incremental conversions, geo experiments and assisted conversions.

Ensure You’re Present Throughout The Conversation

Search is becoming a planning and decision-making interface. Users are no longer just asking questions; they are trying to solve entire problems inside search. So you can’t just answer isolated queries with blog content. You need to support decisions by making sure your brand appears in comparison, constraint-based and recommendation-driven queries.

​As Google has adapted to keep users within its platform, you can no longer rely on a single page or ranking. You need to optimize your online footprint so your brand is present throughout complex planning journeys—not just answering one question, but being consistently surfaced across follow-up prompts, comparisons and refinement stages.

This update goes way beyond technical changes; it’s behavioural. Search is moving from a system that helps users find information to one that helps them make decisions. The question is no longer just “How do I rank?” It’s “How do I stay present while decisions are being made?” It’s time we all started taking a lot more notice.​

Feature image credit: Getty

By John Readman

Find John Readman on LinkedIn. Visit John’s websit

COUNCIL POST | Membership (fee-based)

John Readman is the CEO of ASK BOSCO, an AI-powered marketing platform that brings all your marketing and e-commerce data into one place. Read John Readman’s full executive profile here.

Sourced from Forbes

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Zoom and Google Already Had This Product. But He Built It Anyway and Hit $1.5 Billion: ‘Care More About Your Particular Problem’

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By Jonathan Small, edited by Dan Bova

Can you build a $1.5 billion company in a market that Zoom and Google already dominate? Chris Pedregal proved you can. The Granola founder sat down with the Silicon Valley Girl podcast to talk about his popular AI notepad, which records meetings, transcribes them and lets users chat with their entire meeting history.

Taking on tech giants requires patience. Rather than launching publicly, Pedregal spent a full year sitting next to 150 users, watching them install and use the product, going home to fix what was broken and doing it again the next day. He resisted a public launch until the product was “meaningfully better than the competition.” The result was 500 installs on day one with zero advertising, followed by viral organic growth that eventually attracted major enterprise clients. This kind of intense focus is harder for Big Tech companies that have to spread their attention across dozens of products and hundreds of millions of users.

The mistake most founders make, he says, is letting the noise of social media and FOMO win. “Do not let it mess with your head,” he told host Marina Mogilko. “Care more about your particular problem.” The underlying problem you’re solving probably hasn’t changed in two years. Neither has the only thing that beats Big Tech.

By Jonathan Small,

Founder, Strike Fire Productions. Entrepreneur Staff. Jonathan Small is a bestselling author, journalist, producer, and podcast host. For 25 years, he… Read more

Edited by Dan Bova

Sourced from Entrepreneur

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Google’s latest Search ad updates signal growing shift away from keywords

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By Asa Hiken

AI Max advertisers can now instruct the system in natural language instead of having to rely on previously selected keywords. (Google)

New Search advertising updates from Google show how the tech giant is continuing to shift away from keywords and toward capturing intent through deploying the reasoning skills of AI. Advertisers using AI Max, its automated platform for optimizing search ad campaigns, can now instruct the system in natural language instead of having to rely on previously selected keywords, Google announced today.

The new feature, dubbed AI Brief, is meant to give advertisers better control over how AI Max optimizes their Search campaigns, in much the same way that conversational AI helps consumers express more specific search queries.

AI Brief is just the latest example of Google deprioritizing a keyword-centric approach to search advertising in favour of AI automation. Earlier this month, the tech giant announced that it was retiring Dynamic Search Ads (DSA), which are meant to extend keyword-based strategies, and moving all DSA-powered campaigns to AI Max. More broadly, Google operates Performance Max (PMax), a platform that uses Gemini to effectively run a campaign across all Google channels based on goals outlined by the advertiser.

The rise of AI search platforms has changed how consumers use the internet, namely, opting for longer, more complex search queries over relying on a few impactful keywords. In turn, this behaviour has spurred tech companies such as Google and Meta to create new ways for advertisers to target ads on their platforms. The solution has largely focused on using AI to sniff out the intent behind consumers’ queries.

This shift is why Google launched AI Max roughly one year ago. AI Max offers PMax-like automation, but for advertisers who only want to run Search ads. Using its skills in reasoning, AI Max is able to extend the performance of Search ads by matching advertisers’ desired keywords to a broader range of search queries. Even though these queries might not have contained a targeted keyword, AI Max can understand the intent behind the query, and if it matches that of the keyword, then it will show an ad. The system can also slightly adjust the ad copy based on the perceived intent.

AI Brief enables advertisers to seek the same results without having to use a list of rigid pre-selected keywords to direct AI Max. They can simply explain, in natural language, the search queries they want to capture and avoid, and their guidelines around ad copy. The hope is that doing so makes it easier for advertisers to express their goals.

As part of today’s updates, Google is also expanding AI Max to Shopping ads. The system will seek to match retailers’ ads to shoppers merely showing intent, without the need for them to provide specific product details. Google is making AI Max available for Search campaigns for Travel, too.

By Asa Hiken

Sourced from Ad Age

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Meta and Google fund kids’ brands with millions as critics highlight social media risk

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By Reuters

WASHINGTON — Meta and Google enlisted trusted children’s brands such as Sesame Street, Girl Scouts and Highlights magazine to teach kids to use technology in moderation — even as the companies designed apps that made it difficult for those same young users to unplug, public statements and internal documents show.

Backed by tens of millions of dollars from the tech giants, these ​organizations delivered lessons about personal responsibility to hundreds of thousands of children and parents, using colourful magazines, popular characters and catchy songs, according to public statements.

Alphabet’s Google and Meta’s sponsorships of those lessons are fuelling criticism that the companies are ‌finding new ways to encourage kids to become dependent on social media, particularly by partnering with brands aimed at children younger than 12, an age paediatricians say is often too young for smartphone ownership.

Student texting on a smartphone under a desk during a lesson.
The tech giants designed apps that made it difficult for those same young users to unplug, public statements and internal documents show.Syda Productions – stock.adobe.com

The partnerships also weaken trust in decades-old institutions families have relied on for advice on raising kids, parent advocates said, at a time when the tech giants are facing down multiple lawsuits accusing them of designing addictive products that harmed youth mental health.

The first case to reach trial ended with a $6 million judgment against the two companies.

“It’s like Sesame Street teaming up with Philip Morris to teach kids how to smoke cigarettes safely,” said Rose Bronstein, whose 15-year-old son died ​by suicide after he was bullied online. “How is it any different?”

Meta and Google’s properties generate billions of dollars in advertising revenue from businesses marketing to minors. That economic incentive, critics say, makes it difficult for the companies to offer unbiased guidance on screen use.

“Their ​very business model relies on maximum time on device,” said Emily Boddy, co-lead of US Smartphone Free Childhood, a parent group that advocates against phones in schools. “Their guidance or advice can’t be neutral, and we ⁠see that it’s not.”

Corporations, ranging from soda companies to the tobacco industry, have long made donations to “trusted institutions” to improve their reputations, said Nora Kenworthy, a public health researcher at the University of Washington Bothell.

“It’s very much a reputation management strategy,” Kenworthy said.

Sponsorships extend across several brands

Reuters reviewed ​thousands of pages of company documents made public through lawsuits, along with company-sponsored educational videos and lessons.

The documents reveal that Meta’s strategy to partner with outside groups to promote positive messages about technology began several years ago as criticism of the apps started to proliferate.

In a 2018 draft document, ​internal user experience researchers deliberated how to respond to accusations that social media companies were “designing addictive products that can harm well‑being.”

Researchers proposed asking external experts to identify Facebook features that could have a negative effect on users over time.

A low-angle view of six young people looking down at their cell phones in a circle.
In a 2018 draft document, ​internal user experience researchers deliberated how to respond to accusations that social media companies were “designing addictive products that can harm well‑being.”Davide Angelini – stock.adobe.com

Among their list of ideas, they wrote: “Form an alliance where the third party can vouch for the thoroughness and relevance of our approach for targeting the ‘addiction’ claims.” In a statement to Reuters, Meta said it did not act on that idea.

The companies did establish relationships with numerous brands. Google sponsored Sesame Street, Highlights and Girl Scouts. Meta also sponsored Girl Scouts.

Some of the materials promoted by Meta and Google do include digital safety ​instructions, children’s media researchers said, including reminders to set strong passwords and avoid scams.

The companies declined to say what they paid these organizations. But in a 2024 statement, Google pledged to spend at least $20 million supporting groups that promote “digital well-being,” including Highlights Magazine and Sesame Workshop.

“We prioritize the ​well-being of our youngest users by building industry-leading safeguards and putting families in charge of their digital experiences — any suggestion otherwise is simply wrong,” a Google spokesperson told Reuters.

Sesame Workshop said Google had no control over its digital well-being educational materials, adding in a statement that Google executives gave advice “prior to the start ‌of content development.” ⁠Child development researchers, parents and caregivers weighed in on the materials themselves, Sesame said.

Meta said in a statement it had a limited role in designing the Girl Scout materials, but said it was proud of its work with experts in online safety. The company often works with academics to study negative use of the platform, a spokesperson said.

Highlights Magazine declined to answer specific questions about its Google partnership. Spokesperson Melanie Bay said the magazine designs products to help kids “make thoughtful choices.”

Merit badges for using tech

The Girl Scouts’ digital safety curriculum, sponsored by Meta’s Instagram, requires that girls complete age-specific lessons to earn a “digital leadership” badge.

One part of the curriculum aimed at middle-school-aged scouts instructs girls to track their screen time. Girls are then challenged to “create digital content to support a topic” they care about.

Illustration of the Girl Scouts of the USA logo, featuring two white female profiles on a green clover-like shape.
The Girl Scouts’ digital safety curriculum, sponsored by Meta’s Instagram, requires that girls complete age-specific lessons to earn a “digital leadership” badge.

Last year, Google began sponsoring its own Girl Scouts patch, called the “Be Internet Awesome Fun Patch,” ​tied to the company’s digital literacy curriculum. Girls learn about being kind ​online, using strong passwords, and keeping personal information private.

The ⁠patch, available on the Girl Scouts website, features its logo, as well as Google’s.

“It’s almost priming them to desire to get on social media once they reach the minimum age,” said Brendesha Tynes, a children’s media researcher at the University of Southern California.

Girl Scouts did not respond to multiple requests for comment.

Smartphone sleeping bags

Google also paid Highlights magazine at least $5 million. A 2024 special edition sponsored by Google includes instructions on how to make ​a “sleeping bag” to store devices overnight.

“Before you shut down for the night, put your device to bed,” the magazine says.

The activity makes it appear normal for Highlights readers — who range in age from six ​to 12 — to have smartphones at that ⁠age, seven parents who advocate for tech restrictions told Reuters after reviewing the magazine.

Google logo on the exterior of a building at night.
Google paid Highlights magazine at least $5 million.Christopher Sadowski

Google provided an extra 250,000 copies of the special Highlights edition to organizations such as Save the Children and Reading is Fundamental.

In a statement, a Google spokesperson said the company’s internet safety curriculum is “accredited and reputable,” adding that Google worked with safety organizations to design it.

One of those organizations is the Family Online Safety Institute, a non-profit that receives the majority of its revenue from tech companies, including Google. Meta is not a member.

The institute said in a statement that they reviewed the curriculum before launch.

Some consequences addressed

The lessons sponsored ⁠by Google and ​Meta addressed some of the apps’ effects on kids, four children’s media researchers and paediatricians told Reuters.

Meta’s sponsored Girl Scouts curriculum for middle schoolers addresses how companies take user ​data to sell products or “influence you online.”

A Scholastic worksheet sponsored by Google asks kids to practice what to do if they get a pop-up message that says, “You’ve won a free smartphone! Click here to get it!”

Feature image credit: creativeneko – stock.adobe.com

By Reuters

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Gemini’s upcoming daily assistant feature could get a logical new name

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By Aamir Siddiqui, Contributor AssembleDebug
TL;DR
  • Google has reportedly renamed its upcoming proactive Gemini feature from “Your day” to “Daily brief.”
  • The tool could pull data from searches, emails, and chats to surface relevant information, such as “Active goals.”
  • Despite this rebranding, the name isn’t final until Google officially launches the feature.

 

We’ve previously spotted Google working on a Golle Now-esque feature within Gemini called “Your Day.” The tool would seemingly pull content from searches, email, and Gemini chats to proactively surface useful information for your day, similar in spirit to Samsung’s Now Bar and Now Brief. “Your Day” sounds a bit flimsy as a marketing name, and it seems Google is gunning for a rename of the feature to a more logical “Daily brief.”

As per information shared by a Telegram user (who wishes to remain anonymous) with us, Google has seemingly renamed Gemini’s upcoming “Your day” feature to “Daily brief,” as seen in the screenshot below:

Gemini Your day renamed to Daily brief

While Daily Brief sounds better than Your Day, it’s still not a finalized name. Google could change the name in the run-up to the feature’s launch. We’ll have to wait for the company to officially launch the feature to learn the finalized name.

Here are previous screenshots for reference, showing the “Top of mind” and “Active goals” parts of the feature in action:

Google I/O 2026 is just a few weeks away, and it would be the perfect platform to announce this proactive feature. Hopefully, we can spot some more clues along the way.

Feature image credit: Ryan Haines/Android Authority

By Aamir Siddiqui, 

News Editor

Aamir is a lawyer-turned-tech journalist who has been writing about phones since 2015. He is an Android expert who previously served as the editor-in-chief of XDA Developers.

Contributor AssembleDebug

AssembleDebug (Shiv) is an expert in finding changes and new features in Google apps before they are official. When not diving into code, he’s busy with his studies.

Sourced from ANDROID AUTHORITY

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A consumer watchdog issued a warning about Google’s AI agent shopping protocol — Google says she’s wrong

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By Julie Bort

Shortly after Google announced its new Universal Commerce Protocol for AI-powered shopping agents, a consumer economics watchdog sounded the alarm.

In a now viral post on X viewed nearly 400,000 times, Lindsay Owens on Sunday wrote, “Big/bad news for consumers. Google is out today with an announcement of how they plan to integrate shopping into their AI offerings including search and Gemini. The plan includes ‘personalized upselling.’ i.e. Analysing your chat data and using it to overcharge you.”

Owens is executive director of the consumer economics think tank Groundwork Collaborative. Her concern stems from looking at Google’s roadmap, as well as delving into some of its detailed specification docs. The roadmap includes a feature that will support “upselling,” which could help merchants promote more expensive items to AI shopping agents.

She also called out Google’s plans to adjust prices for programs like new-member discounts or loyalty-based pricing, which Google CEO Sundar Pichai described when he announced the new protocol at the National Retail Federation conference.

After TechCrunch inquired about Owens’ allegations, Google both publicly responded on X and spoke with TechCrunch directly to reject the validity of her concerns.

In a post on X, Google responded that, “These claims around pricing are inaccurate. We strictly prohibit merchants from showing prices on Google that are higher than what is reflected on their site, period. 1/ The term “upselling” is not about overcharging. It’s a standard way for retailers to show additional premium product options that people might be interested in. The choice is always with the user on what to buy. 2/ “Direct Offers” is a pilot that enables merchants to offer a *lower* priced deal or add extra services like free shipping — it cannot be used to raise prices.”

In a separate conversation with TechCrunch, a Google spokesperson said that Google’s Business Agent does not have functionality that would allow it to change a retailer’s pricing based on individual data.

Owens also pointed out that Google’s technical documents on handling a shopper’s identity say that: “The scope complexity should be hidden in the consent screen shown to the user.”

The Google spokesperson told TechCrunch that this is not about hiding what the user is agreeing to, but consolidating actions (get, create, update, delete, cancel, complete) instead making a user agree to each one separately.

Even if Owens’ concerns about this particular protocol are a nothingburger as Google asserts, her general premise is still worth some thought.

She is warning that shopping agents built by Big Tech could one day allow merchants to customize pricing based on what they think you are willing to pay after analysing your AI chats and shopping patterns. This is instead of charging the same price to everyone. She calls it “surveillance pricing.”

Although Google says its agents can’t do such a thing now, it’s also true that Google is, at its heart, an advertising company serving brands and merchants. Last year, a federal court ordered Google to change a number of search business practices after ruling the company was engaged in anticompetitive behaviour.

While many of us are excited to welcome a world where we’d have a team of AI agents handling pesky tasks for us (rescheduling doctor’s appointments, researching replacement mini-blinds), it doesn’t take a clairvoyant to see the kinds of abuse that will be possible.

The problem is that the big tech companies that are in the best position to build agentic shopping tools also have the most mixed incentives. Their business rests on serving the sellers and harvesting data on consumers.

That means AI-powered shopping could be a big opportunity for startups building independent tech. We’re seeing the first few sprinkles of AI-powered possibilities. Startups like Dupe, which uses natural language queries to help people find affordable furniture, and Beni, which uses images and text for thrifting fashion, are early entrants in this space.

Until then, the old adage probably holds true: buyer beware.

Feature image credit: Getty Images

By Julie Bort

Julie Bort is the Startups/Venture Desk editor for TechCrunch.

Sourced from TechCrunch

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Google Adds AI-Powered Comparisons To Trends

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Google has announced an update to Google Trends, its comparative search volume tool, which will now include AI suggestions to help contextualize searches, and give you more insight into relative Search interest and engagement.

The big functional change is that Google’s added a suggested terms for comparison option in the right-hand side bar within Trends. These suggestions are powered by Gemini, and will give you more options for your comparative analysis.

As per Google:

“For example, if you’re researching trending dog breeds, up to eight search terms like ‘golden retriever’ or ‘beagle,’ will automatically populate the graph so you can easily compare them. The side panel will also show related ideas like ‘hypoallergenic dog breeds’ or ‘large dog breeds’ to help you dive deeper. Hover over a search term to edit it, or use the country, time and property filters to adjust the Trends timeline.”

Google Trends

So now, rather than having to come up with the right comparisons on your own, you can prompt Gemini for inspiration, which could give you more relevant context for your Trends reports.

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Google’s update for Veo 3.1 lets users create vertical videos through reference images

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By Ivan Mehta

Google updated its Veo 3.1 AI video-generation model with the ability to create native vertical videos for social platforms using reference images. The changes will also make the videos generated from reference images more expressive and dynamic.

When producing AI-generated videos for YouTube Shorts or other platforms like Instagram or TikTok, Veo users can now natively choose the 9:16 vertical format to avoid any cropping. Google is also adding the feature directly to the YouTube Shorts and the YouTube Create app.

Google first released Veo 3.1 in October 2025 with improved audio output and more granular editing controls compared to previous versions.

When you provide reference images, Veo 3.1 now generates videos with better character expressions and movements, even if your prompts are shorter. Google said the update also improves character, object, and background consistency. What’s more, users can blend various characters, backgrounds, objects, and textures to create a cohesive output.

Users can access these features directly in the Gemini app. Professional users can access them through Google’s video editor Flow, the Gemini API, Vertex AI, and Google Vids.

The new update also brings an improved upscaling feature to 1080p and 4K resolutions, which is available on Flow, Gemini API, and Vertex AI in Google Cloud.

Apps, Gemini app, Google,In Brief,Veo,YouTube

Feature image credit: Google

By Ivan Mehta

Sourced from TechCrunch

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