{"id":10989,"date":"2026-04-27T18:38:58","date_gmt":"2026-04-28T00:38:58","guid":{"rendered":"https:\/\/attentionmedia.io\/?p=10989"},"modified":"2026-04-27T18:38:58","modified_gmt":"2026-04-28T00:38:58","slug":"what-marketers-need-to-know-from-google-cloud-next-26","status":"publish","type":"post","link":"https:\/\/attentionmedia.io\/?p=10989","title":{"rendered":"What marketers need to know from Google Cloud Next \u201926"},"content":{"rendered":"
\"Google<\/div>\n

Google Cloud\u2019s annual conference featured dozens of announcements aimed at enterprise marketers. Some represent genuinely new capabilities. Others are early-stage partnerships with vague timelines, or existing products repackaged under the conference spotlight.<\/p>\n

Sorting out which is which matters if you are trying to make real technology decisions \u2014 so here is a look at the nine most significant announcements, what they mean, and how much you can actually use today.<\/p>\n

One thing worth noting upfront: Most of the marketing-focused announcements from Cloud Next \u201926 are customer and partner stories, not Google product launches. Google is not building a marketing cloud. It is embedding Gemini AI models into tools marketers already use \u2014 Salesforce, SAP, Slack, WPP\u2019s agency platform \u2014 and betting that owning the AI layer is more valuable than owning the workflow.<\/p>\n

\u201cThis isn\u2019t about offering individual services that can be cobbled together; it is about providing a comprehensive backbone for innovation,\u201d Thomas Kurian, CEO of Google Cloud, said in his keynote remarks.<\/p>\n

Whether that strategy pays off for marketers depends heavily on how well those integrations actually work in practice, which takes time to figure out.<\/p>\n

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1: Gemini Enterprise for CX powers most of this<\/h2>\n

Most of the customer-facing AI announced runs on Gemini Enterprise for Customer Experience, Google Cloud\u2019s platform for building AI agents \u2014 shopping assistants, voice agents, and similar tools. Most of it is currently available through Google Cloud, so enterprises with Google Cloud contracts can use it today.<\/p>\n

What the announcements do not tell you: what it costs, how long typical implementations take beyond the headline cases, or how deployments perform outside of controlled pilots. Keep that in mind as you read the case studies below.<\/p>\n

2: Is UCP a new standard or a Google dependency?<\/h2>\n

Google introduced the Universal Commerce Protocol (UCP), an open standard that lets retailers plug their product catalogs and checkout flows directly into Google\u2019s AI surfaces \u2014 AI Mode in Search and the Gemini app. In theory, this means shoppers can ask Gemini for product recommendations and complete a purchase without ever leaving the conversation. Ulta Beauty is among the first retailers to use it, with a rollout expected within the next month.<\/p>\n

The word \u201copen standard\u201d deserves scrutiny. Google is proposing UCP as an open protocol, but the primary beneficiary of broad retailer adoption is Google \u2014 it becomes the default commerce layer inside its own AI products. Retailers who integrate get visibility in Gemini and AI Mode in Search. Those who do not risk being invisible in those, just as they once risked invisibility without a Google Shopping feed.<\/p>\n

Separately, Ulta launched Ulta AI, an on-site shopping assistant built on Gemini Enterprise for Customer Experience, and drawing on data from its 46 million-plus loyalty members. That part is live now on Ulta.com, with an app rollout coming.<\/p>\n

What it means for marketers:<\/strong> The UCP question is not really about whether you should integrate \u2014 if Google\u2019s AI surfaces become a significant commerce channel, you will need to. The question is when, and at what cost. Right now, this is very early, with limited retailer participation and no clear data on how much commerce is actually flowing through AI Mode in Search. Watch the adoption curve before committing significant resources.<\/p>\n

Availability:<\/strong> Ulta\u2019s UCP integration goes live within the month. Broader program details \u2014 including how other retailers enroll, technical requirements, and any revenue-sharing terms \u2014 have not been fully disclosed.<\/p>\n

3: What Macy\u2019s \u2018four weeks\u2019 claim actually means<\/h2>\n

Macy\u2019s announced \u201cAsk Macy\u2019s,\u201d a conversational shopping assistant built on Gemini Enterprise for Customer Experience that helps shoppers navigate a catalog of more than 2.5 million stock-keeping units. The headline claim: it was built and deployed in four weeks.<\/p>\n

That figure is doing a lot of work. Four weeks to a functional demo is very different from four weeks to a production system serving millions of customers at scale. The press release does not specify what \u201cbuilt\u201d includes \u2014 whether it covers data preparation, integration with existing commerce systems, quality assurance, or the legal and compliance review that large retailers typically require before customer-facing AI launches. Macy\u2019s is also a longstanding Google Cloud customer, which means the underlying infrastructure was already in place.<\/p>\n

None of that means the deployment is not real or impressive. Cart abandonment rates running around 70% for ecommerce are a genuine problem, and conversational AI that replicates an expert store associate\u2019s guidance is a legitimate solution. But \u201cfour weeks\u201d as a benchmark for your own organization should be treated with caution.<\/p>\n

What it means for marketers:<\/strong> Conversational shopping agents are becoming table stakes for large retailers. That is the real takeaway \u2014 not the speed claim, but the fact that Macy\u2019s, Ulta, and others are deploying these now, which will raise customer expectations across the category.<\/p>\n

Availability:<\/strong> Ask Macy\u2019s is live on Macy\u2019s digital properties. The platform it runs on is generally available to Google Cloud customers.<\/p>\n

4: Home Depot\u2019s AI voice agents<\/h2>\n

The Home Depot announced AI voice agents for customer phone calls to its U.S. stores. Rather than navigating a phone menu, customers describe what they need, and the system routes or resolves the inquiry in natural language. A 50-store pilot showed the system understanding customer intent in fewer than 10 seconds \u2014 four times faster than traditional menus.<\/p>\n

This is one of the more credible announcements because it comes with a real pilot, a specific metric, and a defined rollout plan. The agents can check order status, build shopping carts from verbal project descriptions, and handle calls in multiple languages. Home Depot also noted that store associates in the pilot reported higher job satisfaction \u2014 more time for in-store customers, less time fielding routine phone calls.<\/p>\n

The caveat: <\/strong>\u201cExpanding to all U.S. stores over the coming year\u201d is a plan, not a shipped product. Home Depot has thousands of stores. A 50-store pilot is roughly 1% of that footprint.<\/p>\n

What it means for marketers:<\/strong> AI voice agents at this scale create a new stream of structured customer intent data \u2014 what people are actually calling about, in their own words \u2014 that marketing teams have not had access to. How that data gets used for campaign planning and personalization is a question worth asking if your organization is considering similar deployments.<\/p>\n

Availability:<\/strong> Pilot live at 50 stores now. Full U.S. rollout planned over the coming year.<\/p>\n

5: WPP and Google Earth AI<\/h2>\n

WPP announced it integrated Google Earth AI \u2014 Google\u2019s planetary-scale geospatial intelligence, including population movement, weather modeling, and real-time traffic \u2014 into WPP Open, its proprietary agentic marketing platform. <\/p>\n

The integration allows WPP agency clients to factor physical-world signals into digital campaign planning: trigger a campaign when weather shifts in a target market, pre-validate media reach against real foot traffic rather than modeled estimates, or build location-specific audience indexes like WPP\u2019s cited example of an \u201cElectric Vehicle Readiness Index\u201d mapping charger availability to potential EV buyers by locality.<\/p>\n

\u201cPeople don\u2019t just live in the digital world \u2014 they live in the physical world,\u201d said Stephan Pretorius, chief technology officer at WPP, in a press release. That is a fair point, and the capability being described is genuinely novel. More than 80% of retail sales still happen offline, and connecting physical-world signals to digital marketing decisions has been a longstanding gap.<\/p>\n

But here is the important context: This is not a Google Cloud product you can buy. It is a WPP Open capability, meaning it is available only to brands working with WPP agencies \u2014 GroupM, Ogilvy, Grey, and others in the WPP network. If you are not a WPP client, this announcement tells you where the industry is heading, not what you can do today.<\/p>\n

It is also worth noting that WPP is under significant financial and competitive pressure, losing major accounts to rivals. This partnership is partly a WPP differentiation play \u2014 a way to offer something its competitors cannot easily replicate quickly.<\/p>\n

What it means for marketers:<\/strong> If you work with WPP agencies, ask about access to these capabilities now. If you do not, watch for similar geospatial-augmented planning tools to emerge from other platforms and agency networks over the next 12 to 18 months.<\/p>\n

Availability:<\/strong> Available to WPP Open clients now. Not a self-serve product.<\/p>\n

6: SAP and Google\u2019s marketing automation integration<\/h2>\n

SAP and Google Cloud announced an integration that brings SAP\u2019s Joule AI agents into SAP Customer Experience (SAP CX) solutions, with Gemini Enterprise acting as the coordination hub. The promised capability: a marketer sets a plain-language objective \u2014 \u201cIncrease repeat purchases from the last 30 days\u201d \u2014 and a Joule agent handles end-to-end audience segmentation, content personalization, and campaign execution.<\/p>\n

This is one of the most substantive marketing technology announcements to come out of the conference because it addresses a real and documented problem. According to SAP\u2019s research, more than half of marketers say fragmented, outdated data prevents them from acting in the moment. The zero-copy data sharing between SAP Business Data Cloud and Google BigQuery is a meaningful architectural choice \u2014 agents can draw on both data ecosystems without moving data between platforms, which simplifies governance.<\/p>\n

The significant catch: this is not available yet. Marketing is described as \u201cthe first use case\u201d and will be available to customers \u201cin the second half of 2026.\u201d That means at least six months from now, and \u201cH2 2026\u201d is a conference announcement, not a shipping date. Enterprise software integrations between two large platforms routinely slip.<\/p>\n

What it means for marketers:<\/strong> If your organization is already on SAP for commerce and customer data, this is worth tracking closely and raising with your SAP account team. If you are not an SAP customer, this is a roadmap item for a different ecosystem.<\/p>\n

Availability:<\/strong> Not yet available. Planned for the second half of 2026.<\/p>\n

7: Salesforce and Google partnership<\/h2>\n

Google Cloud and Salesforce announced an expanded integration connecting Salesforce Agentforce with Gemini Enterprise. The headline: AI agents can now work across Slack, Google Workspace, and Salesforce CRM simultaneously, sharing context and taking action without users switching tools. Specific features include Agentforce Sales agents accessible inside Gemini Enterprise, Gemini accessible inside Slack, and zero-copy data sharing between Salesforce Data Cloud and Google BigQuery.<\/p>\n

The competitive subtext here is significant and worth stating plainly: Salesforce competes directly with Microsoft in the CRM market. Microsoft\u2019s Copilot, embedded across Microsoft 365, Teams, and Dynamics, is arguably the most aggressively marketed enterprise AI product right now.<\/p>\n

The fact that Salesforce is deepening its AI partnership with Google \u2014 rather than doubling down on Microsoft \u2014 is a meaningful signal about where enterprise confidence in Gemini is heading, and about the limits of the Microsoft-OpenAI relationship in the eyes of at least one major platform vendor.<\/p>\n

The less exciting reality: The press release is short on specifics about what is actually available today versus what is coming. \u201cIntegrations are rolling out now,\u201d and \u201cthe two companies will develop new features\u201d appear in the same document, indicating some of this is live, and some is a roadmap. The companies have not provided a consolidated GA date for the full feature set.<\/p>\n

What it means for marketers:<\/strong> If your stack is Salesforce + Google Workspace + Slack, ask your Salesforce rep which features are live today. Do not assume everything in the announcement is available.<\/p>\n

Availability:<\/strong> Some integrations are rolling out now. Full feature set GA dates not specified.<\/p>\n

8: ServiceNow and Google partnership <\/h2>\n

ServiceNow and Google Cloud announced that AI agents across Gemini Enterprise and the ServiceNow AI Platform can work together in a single automated chain, with use cases cited in retail, 5G networking, and IT operations. For retail marketers, the implication is that promotional changes could automatically trigger coordinated marketing and supply chain responses.<\/p>\n

This is the thinnest announcement when it comes to concrete, usable facts. The press release is high on vision and short on specifics about what is actually built, what is available, and what it costs.<\/p>\n

Availability:<\/strong> Partnership announced. Product availability, pricing, and integration specifics are still being disclosed.<\/p>\n

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9: The $750 million partner fund<\/h2>\n

Google Cloud announced a $750 million fund to support the development, adoption, and education of agentic AI across its partner ecosystem \u2014 agencies, system integrators, software vendors, and consulting firms.<\/p>\n

To be clear, this is not $750 million in grants to marketers, and it is not a product. It is Google Cloud investing in the ecosystem of companies that build on its platform \u2014 the same strategy Microsoft has used for decades to grow Azure adoption by funding partner development. The money goes to vendors and agencies building Google AI-powered tools, not to the marketing organizations using them.<\/p>\n

The practical implication is that you will likely see more Google-Cloud-powered capabilities from the agencies and software vendors you already work with over the next 12 to 18 months. But that is an indirect benefit, and the timeline is uncertain.<\/p>\n

Availability:<\/strong> Fund announced. Partner program details to follow.<\/p>\n

The bigger picture of what Google is really doing here<\/h2>\n

Overall, Cloud Next \u201926 revealed a fairly coherent Google Cloud strategy for the martech market \u2014 one that is driven as much by competitive pressure as by product innovation.<\/p>\n

Google Cloud is third in the overall cloud infrastructure market, trailing Amazon Web Services and Microsoft Azure by significant margins. Microsoft\u2019s particular advantage in enterprise marketing technology is its deep integration with the tools organizations already use \u2014 Office 365, Teams, Outlook, and, increasingly, Copilot, which is woven into all of them. Alphabet committed $75 billion in capital expenditures for 2026, primarily for AI infrastructure, to help close that gap.<\/p>\n

Google\u2019s response isn\u2019t a Microsoft-style suite that owns the full workflow. It is making Gemini the AI engine inside the tools that already own those workflows \u2014 Salesforce for CRM, SAP for commerce, WPP for agency services, and Slack for team communication. That is a sensible strategy, but it also means Google\u2019s success in marketing technology depends on partners executing well, on integrations working as promised, and on enterprises choosing Google\u2019s AI layer over the alternatives \u2014 primarily Microsoft\u2019s OpenAI-backed models \u2014 within those same platforms.<\/p>\n

The announcements are mostly signals of intent and early deployment rather than mature, widely available products. The retail AI stories \u2014 Macy\u2019s, Ulta, and Home Depot \u2014 are the most credible because they come with deployed products and real metrics, even if those metrics are selective. The platform integrations \u2014 SAP, Salesforce, and ServiceNow \u2014 are largely dressed-up roadmap items. And the WPP partnership, while genuinely interesting, is only accessible through one agency network.<\/p>\n

All in all, some of what Google announced is worth watching, a little of it is worth acting on now, and most of it will be clearer in six to 12 months once the partner integrations ship and the real-world deployments accumulate enough data to evaluate.<\/p>\n

The post What marketers need to know from Google Cloud Next \u201926<\/a> appeared first on MarTech<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"

Google Cloud\u2019s annual conference featured dozens of announcements aimed at enterprise marketers. Some represent genuinely new capabilities. Others are early-stage partnerships with vague timelines, or existing products repackaged under the conference spotlight. Sorting out which is which matters if you are trying to make real technology decisions \u2014 so here is a look at the … <\/p>\n

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