Today, Oracle was named a Leader for Oracle Fusion Unity Data Platform in the Gartner® Magic Quadrant™ for Customer Data Platforms.
We’re proud of the recognition — but the dot itself isn’t the story. We set out to solve a problem we kept hearing again and again from enterprise customers:
“We have the data. We have the tools. Why is growth still so hard?” The answer, increasingly, is context.
The Market Has Changed — and So Has the Job to Be Done
AI has fundamentally changed expectations for how go-to-market teams should operate. Decisions that once took weeks are now expected in moments. Insights that once lived in dashboards are expected to surface directly in workflows.
And yet, most organizations are stuck.
Not because AI models don’t exist — but because the data and context those models depend on are fragmented, stale, or incomplete.
AI has created a secular shift in both technology and behavior — and in doing so, it has exposed a hard truth many organizations are now confronting: AI adoption is real, but AI value is blocked by data and context.
Go-to-market and customer experience teams don’t struggle because they lack models or tools. They struggle because:
- Customer and account data is fragmented
- Buying signals live across too many systems
- Context is assembled manually, if at all
- Marketing and sales optimize volume, not value
In short: AI is ready. Enterprise data is not.
From Campaign Creation to Context Engineering
Many vendors have responded to this moment by positioning CDPs alongside AI to scale what already exists:
- More campaigns
- More journeys
- More content
- More messages
But scaling volume in a world of limited attention doesn’t create advantage. It creates noise. The real opportunity isn’t to help teams do more of the same work — it’s to remove the work that shouldn’t exist at all.
- Manual segmentation.
- Disconnected decision logic.
- Meetings to reconcile data across systems.
These are symptoms of systems that were never built for enterprise context. What we’re seeing instead is a shift in the center of gravity for go-to-market teams:
- From campaigns → opportunities
- From segments → buying groups
- From dashboards → decisions
- From volume → value
This shift requires something fundamentally different from a traditional CDP. It requires a platform that can unify customer, account, and operational data — and make that context immediately usable by humans and AI.
Not as an overlay. Not as a bolt-on. But as a core system of record and action.
Our Perspective on the Report
In our opinion, the Gartner Magic Quadrant reflects this same inflection point. Customer Data Platforms are no longer evaluated solely on how well they support marketing activation. They’re increasingly judged on how effectively they:
- Unify front- and back-office data
- Surface revenue and expansion opportunities
- Support cross-functional teams
- Provide a foundation for AI-driven decisioning
We believe this recognition highlights our strengths in handling complex data requirements specific for large enterprises. Being named a Leader highlights our direction — not because of any single feature, but because of a sustained commitment to building a data platform that serves the entire go-to-market motion, not just one team.
Looking Forward
We’re grateful to the customers, internal marketing teams and partners who have challenged us, shared candid feedback, and pushed us to build a platform that reflects how modern enterprises actually operate. Their input continues to shape not only what we build, but how we think about the future of customer data and go-to-market strategy.
We believe that the next frontier of customer data will be defined by systems that:
- Create a unified intelligence layer from all critical enterprise data sources
- Collapse dozens of decisions into a single, informed outcome
- Surface buying groups instead of guessing at them
- Generate opportunities, not just audiences
- Help teams move faster with confidence, not complexity
That’s the direction we’re building toward — and the standard we believe the market will increasingly expect. If you’re rethinking your customer data strategy in an AI-first world, the Gartner Magic Quadrant is a useful place to start. And we’d love to continue the conversation about where it all goes next.
Gartner, Magic Quadrant for Customer Data Platforms, Lizzy Foo Kune, Rachel Dooley, Suzanne White, Benjamin Bloom, Audrey Brosnan, 26 January 2026. Gartner and Magic Quadrant are trademarks of Gartner, Inc. and/or its affiliates.
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