LiveRamp Powers Agentic Pilots for Commerce Media - From Insights to Optimization

Advertiser expectations are rising, and many commerce media networks (CMNs) are being asked to deliver with increased speed, ease, and optimization that marketers have come to expect from major platforms. Social platforms and DSPs have spent years making it easier to set a budget, define a goal, and now let AI handle the optimization. Advertisers have grown comfortable with that model and they’re increasingly asking CMNs to offer something similar. 

CMNs have the data, but are challenged with an operational gap. CMNs want to turn their data into outcomes, for multiple advertisers simultaneously, through workflows that are governed, repeatable, and fast. And agentic AI offers them the opportunity to achieve this at a scale not previously possible.

That is the thesis behind LiveRamp’s new agentic pilots for commerce media. We believe that the friction CMNs face today - fragmented workflows, one-off analysis, and slow time to value - is exactly the kind of problem well-governed, outcome-oriented AI can help solve.

How LiveRamp is helping CMNs turn insight into outcomes

CMNs have differentiated assets: first-party transaction data, direct consumer relationships, and media inventory close to the point of purchase. Whether it’s a grocery chain, a food delivery platform, an airline, or a financial institution, the underlying value proposition is the same. The network knows things about its consumers that no one else can replicate. The challenge isn’t access to that data. The challenge is operationalizing it into repeatable, scalable outcomes for the advertisers. 

LiveRamp is helping solve that problem by building more connected, outcome-first workflows from insights to optimization. Our approach builds on the collaboration infrastructure CMNs and advertisers already use today, securely layering agentic orchestration on top of existing clean room environments, APIs, and interfaces rather than asking teams to start from scratch. The LiveRamp platform is fundamentally designed for neutrality and interoperability, enabling customers to build their own agents, leverage their partners’ agents, or tap into the LiveRamp Agentic Builder program. 

Recognizing that this transition is too significant to develop in the abstract, we are working through it in practice with customers and partners across the ecosystem. That work is now taking shape through three early pilot patterns, each tied to clear business goals:

• Food delivery: CMNs built on transaction and behavioral data from food delivery services are creating a clearer path to growth; driving net-new customer acquisition, higher purchase frequency, and customer reactivation.
• Big box & specialty retail: Retailers with broad product assortments are turning their first-party intelligence into action; supporting product launches, expanding basket size, and deepening customer loyalty through more targeted, timely engagement.
• Grocery retail: Grocery CMNs are gaining stronger performance visibility and smarter cross-channel optimization, with clearer insight into reach, frequency, conversions, incrementality, and ROAS.

These pilots are designed to show what happens when CMNs can move faster from insight to action, with more structure, more automation, and stronger measurement built in.

What we’re still building in agentic marketing for commerce media

We’re confident in the problem we’re solving and the direction we’re heading. But this is a complex shift for the industry, and some of the hardest questions are still being worked through. We think that transparency matters, especially for the builders, partners, and practitioners helping shape what comes next.

A few areas are still taking shape:

• Governance and permissions: Trusted collaboration only works when every participant has assurance, control, and clarity over how data is used. While the industry is still working through developing standards for those controls, LiveRamp already provides the platform controls to make governance possible, allowing retailers and brands to define what is permitted, who can access data, and which workflows are allowed, with those rules enforced in the system itself. That foundation is what makes more advanced agentic workflows possible while respecting each party’s privacy requirements.
• The user experience: We believe the future is a workflow-native planning experience, not another chatbot. But the design patterns for outcome-first agent experiences in media are still emerging, and practitioner feedback will play an important role in getting that right.
• Activation handoffs: We know the transition from insight to activation needs to feel seamless, not stitched together. The exact shape of that handoff, including what the APIs return, how projected match rates are shown, and how alternative options are presented, is still being refined with customers and partners.
• Measurement and optimization: An outcome-first agent needs to do more than plan and activate. It also needs to learn from measurement results and utilize those insights to inform future decisions. That closed-loop system is a work-in-progress and remains an active area of development.

Why this matters for CMNs right now

The CMNs that standardize and accelerate the path from consumer insight to campaign to measured outcome will be the ones that win advertiser investment. Agentic AI will not replace the teams doing this work. But, built on governed collaboration infrastructure, it can reduce the manual steps that slow those teams down and help them spend more time on the strategic work that truly differentiates a network.

That’s why we’re building this with a select group of customers, and why we’re looking for more CMNs and ecosystem participants ready to help shape what comes next. If you’re working on navigating these paradigm shifts, we’d love to hear from you at LiveRampAgenticPilots@liveramp.com  

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