Global consumer brands are reworking how they track customers, measure campaigns, and connect online shopping with marketing data as AI reshapes digital commerce. Unilever’s recent five-year agreement with Google Cloud shows how large firms are beginning to construct those changes around artificial intelligence.
The partnership focuses on AI-driven marketing intelligence, shared data systems, and what each corporations describe as “agentic commerce,” where AI systems help guide shopping actions like discovery and purchase flows. The deal goals to support Unilever’s global portfolio of brands by improving how the corporate understands customer behaviour and manages marketing performance.
Unilever plans to use Google Cloud technology to enhance brand discovery, conversion tracking, and campaign measurement in markets. It’s working to attach more of its consumer data into unified platforms so teams can analyse performance and respond faster to shifts in demand.
Linking marketing data in systems
The effort reflects a wider move amongst consumer goods corporations to bring marketing data, commerce platforms, and analytics tools right into a single environment. Coverage from ITPro notes that the collaboration also supports Unilever’s broader push toward digital transformation, with AI tools expected to assist automate parts of marketing evaluation and improve how insights are shared in teams. By tying marketing intelligence to cloud-based systems, the corporate may find a way to check campaigns faster and refine targeting using real-time signals not delayed reports.
Moving toward agent-supported commerce
An essential a part of the initiative is the concept of agent-supported commerce. In practice, this involves looking into how AI systems can assist with product recommendations, search visibility, and online shopping experiences. Brands are exploring how AI might help connect consumers to products earlier in the choice process.
The change comes as marketers face growing pressure to point out measurable returns on digital spending. Industry research has highlighted how complex marketing stacks and fragmented data often limit the worth corporations get from analytics tools.
A Gartner study often cited in marketing technology coverage has found that organisations typically use only about half of the features available in their martech platforms, suggesting many systems remain underused or poorly integrated. That gap has pushed firms to rethink whether AI-based tools can simplify how insights are gathered and applied.
AI adoption spreads in global brands
Unilever’s move also reflects how large advertisers are adapting to changes in online discovery. Search engines, retail platforms, and social media are increasingly reliant on automated rating and suggestion systems. As these systems alter what consumers see first, brands are trying to grasp how AI affects visibility, pricing strategy, and promotional timing.
Google Cloud positions its AI services as infrastructure for this type of work. The company offers tools for data processing, predictive evaluation, and automated campaign insights, which businesses can plug into their very own systems. By working directly with Google Cloud, Unilever gains access to those abilities with Google’s broader ecosystem, including promoting and analytics platforms.
The partnership may help address the dimensions challenge that comes with operating in many markets without delay. Unilever sells products in greater than 190 countries, in keeping with its corporate publications, which implies marketing teams often have to balance global brand consistency with local campaign needs. Cloud-based AI systems might help central teams share insights while allowing regional teams to adapt campaigns for local audiences.
While the long-term impact of such partnerships relies on execution, the direction is that marketing technology is changing from isolated tools toward integrated platforms where data and shopping experiences connect more closely. Unilever’s collaboration with Google Cloud shows how major brands are testing that model as they appear for higher ways to grasp customers and manage digital sales channels.
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