LiveRamp Expands OpenAI Deal to Bring First-Party Data Targeting to ChatGPT Ads

Advertisers using LiveRamp's RampID can now activate customer audiences directly within ChatGPT Ads following an expanded partnership between LiveRamp and OpenAI announced in late September 2026.

The expansion marks a significant step in OpenAI's push to mature its advertising platform. As ChatGPT evolves from a conversational tool into a full-scale media channel, the ability to deploy first-party data for precise audience targeting brings it closer to the established playbooks advertisers have long relied on with Google and Meta. For marketers managing complex data ecosystems, this development could reshape how they think about budget allocation and audience strategy across AI-powered platforms.

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What the LiveRamp and OpenAI Integration Actually Does

The new integration allows marketers to use LiveRamp's RampID — its cross-platform customer identity tool — to activate audiences from CRM systems, loyalty programs, websites and apps directly within ChatGPT Ads. Advertisers can use those audiences to reach specific customer segments or suppress others, such as excluding existing subscribers from an introductory offer campaign.

This expansion builds on a partnership that began in June 2026, when LiveRamp became a measurement partner for ChatGPT Ads. That initial deal focused on connecting ad exposure to downstream conversions. The latest update moves the relationship into audience activation territory.

What Markets Are Covered

The integration launched across 11 markets, with LiveRamp confirming plans to expand availability as ChatGPT Ads rolls out in additional regions. For brands already running RampID across multiple platforms, adding ChatGPT as another activation destination requires minimal additional setup.

It is worth noting that LiveRamp is not the only path to first-party targeting in ChatGPT. OpenAI's Ads Manager already allows advertisers to upload Custom Audiences directly using CSV or TXT files containing email addresses, phone numbers, hashed identifiers or Google Advertising IDs. LiveRamp simply offers existing customers a more streamlined route.

Why Identity Resolution Matters Here

The underlying mechanism — identity resolution — is what makes this integration meaningful. RampID works by pseudonymously linking customer identifiers across platforms, allowing a brand's offline and online data to be matched against addressable audiences without exposing raw personal data. For marketers already investing in building a unified single customer view, this integration represents a logical extension of that infrastructure into an emerging channel.

Understanding how data flows through platforms like this is increasingly important. Marketers operating across multiple jurisdictions should also be aware of how first-party data activation intersects with privacy obligations — the core GDPR data protection principles governing personal data use apply to audience activation workflows regardless of the platform involved.

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How This Compares to Google and Meta Audience Targeting

For performance marketers, the feature set will feel familiar. The ability to include or exclude specific audiences at the campaign level and apply bid multipliers at the ad group level mirrors controls that have existed on Google and Meta for years. OpenAI allows bid multipliers ranging from 0.1x to 10x, giving advertisers granular control over how aggressively they pursue known customers or prospects.

Where ChatGPT Ads Still Has Ground to Cover

However, surface-level similarities should not be mistaken for equivalent performance potential. Google and Meta carry years of advertiser data, conversion signals and machine learning refinement behind their targeting systems. ChatGPT Ads remains a relatively young platform with limited public performance benchmarks.

Allegiance Group & Pursuant (AGP), a firm working with nonprofit clients, is already implementing the integration. Megan Morris, Director of Integrated Media Solutions at AGP, explained the rationale: "We're continually optimising the channels we use to reach our customers, and with ChatGPT Ads becoming an increasingly popular engagement surface for donors, it's important for us to view the omnichannel impact of our ads across all of our investments."

That use case highlights where early adoption may make the most sense — brands already using LiveRamp across several channels who can add ChatGPT without building a separate data workflow. Conversation context also plays a role in determining which ads users see within ChatGPT, adding a layer of targeting complexity that does not exist in traditional search or social platforms.

A Channel Shift Worth Watching

The rise of conversational AI as an ad-supported medium is part of a broader transformation in how businesses deploy technology to reach audiences. Marketers who have followed real-world examples of artificial intelligence in business will recognise this pattern: capability arrives before consensus on best practice, and early movers absorb the learning curve that later adopters avoid.

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What Advertisers Still Don't Know — and What It Could Cost Them

Despite the expanded toolset, significant unknowns remain. OpenAI has not published comparative performance data showing how Custom Audiences perform against its other targeting options. There are no public benchmarks for click-through rates, conversion rates or cost efficiency specific to first-party audiences within ChatGPT Ads.

The Pricing and Performance Gap

On pricing, OpenAI's documentation does not identify separate rates for Custom Audience campaigns. ChatGPT Ads supports both CPM and CPC buying models, along with conversion-optimised campaigns. Bid multipliers give advertisers indirect control over spend levels, but without baseline performance data, determining a fair bid premium for a known audience segment remains largely speculative.

If Custom Audiences carry higher CPCs or CPMs in practice, cost alone will not tell advertisers whether they are overpaying. Conversion rates, customer lifetime value and incremental lift compared to existing channels will all need to factor into any honest assessment.

What Early Case Studies Could Reveal

LiveRamp has indicated it plans to share results from early adopters using the integration. Those case studies could provide the first meaningful signal on how first-party audiences perform in a conversational AI ad environment — something the industry does not yet have.

For now, advertisers face a familiar tension in emerging channel adoption: easy access to the tools does not guarantee clarity on whether the tools are working. The absence of standardised reporting metrics within ChatGPT Ads means that marketers will need to apply their own measurement frameworks rigorously, rather than relying on platform-reported figures alone.

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The LiveRamp-OpenAI expansion reflects a broader pattern in digital advertising — first-party data infrastructure becoming table stakes across every major platform. Here is how advertisers can apply this information:

• Start with suppression before expansion. Using first-party data to exclude recent purchasers or existing subscribers is a lower-risk first test that protects budget while generating early platform data.
• Audit your LiveRamp activation list. If you are already running RampID across Google, Meta or other destinations, confirm whether adding ChatGPT requires any incremental effort or cost before committing to a test.
• Set clear measurement criteria before launching. Given the absence of public benchmarks, define in advance what success looks like — whether that is CPA, ROAS or incremental reach — so early results can be evaluated objectively rather than anecdotally.

For further context on the evolving standards around identity resolution and cross-platform data use, the IAB Tech Lab's resources on data transparency offer a useful reference point for marketers building compliant, durable audience strategies.