Enterprise marketing has changed faster in the last few years than most pricing models have in the last decade.
Marketing teams are expected to move in real time, operate across channels, and increasingly rely on AI to surface insights, recommend actions, and automate execution. Yet many enterprise platforms are still priced as if usage were static, predictable, and linear.
That mismatch is no longer tolerable.
At Treasure Data, we rethought pricing with a single question in mind: what should pricing look like when marketing is dynamic, AI-driven, and value compounds over time?
The hidden cost of legacy CDP pricing
Most traditional CDP pricing models were designed around infrastructure, not outcomes.
They tend to charge for:
- Compute consumption
- Processing volume
- System activity that marketers never directly see
This creates an unhealthy dynamic. The more successful teams are, the more unpredictable their costs become. Instead of encouraging experimentation and scale, pricing quietly discourages it.
When every new campaign, audience, or AI-powered workflow carries financial uncertainty, teams hesitate. Innovation slows. Ambition shrinks.
That is not a technology problem. It is an economic one.
Why AI breaks old pricing models
AI fundamentally changes how value is created in marketing software.
In a traditional SaaS world:
- Users initiate most actions
- Workflows are predefined
- Value is limited by manual effort
In an AI-native world:
- Systems analyze continuously
- Recommendations surface automatically
- Actions scale without linear increases in effort
That shift means successful platforms are used more, not less. If pricing increases simply because the system is doing what it is designed to do, the model is misaligned.
Pricing must enable AI-driven scale, not penalize it.
Pay for value, not compute
Enterprises have long been forced to choose between two imperfect options for CDPs:
- Packaged CDPs that primarily meter the number of profiles and compute.
- Composable-only CDPs that primarily meter the number of profiles and shift all processing to a cloud data warehouse (CDW), creating unpredictable query charges.
This is why Treasure Data decoupled pricing from compute.Customers enjoy transparent pricing based primarily on the number of real-time, resolved customer profiles managed and the volume of associated behavioral events (e.g., website visits, mobile app usage, email activities, etc.). Whether workloads run in Treasure Data’s high-performance database engine or inside the customer’s cloud data warehouse environment, your teams enjoy the same consistent experience.
Our Hybrid CDP architecture supports fully managed deployments, composable data warehouses, or a combination of both. But unlike many modern stacks, customers are not exposed to unpredictable infrastructure costs as they activate more data or use more advanced capabilities.
To recap, no-compute pricing means you pay for profiles and behaviors instead of processing in the CDP. That translates to:
- Predictable economics, even as usage grows
- Freedom to experiment without financial anxiety
- Flexibility without sacrificing control
Teams can focus on creating value instead of managing cost risk.
Treasure Data pricing: How it works
We often hear that enterprise pricing has to be complex to support complex use cases.
We disagree.
Complexity in pricing rarely benefits customers. More often, it obscures tradeoffs and slows decisions. Our approach prioritizes clarity without sacrificing power.
Treasure Data pricing works like this:
At the foundation is an annual Intelligent CDP subscription, structured around customer profiles and behavioral scale rather than opaque system metrics. This provides a stable base for unifying data, managing identity, orchestrating audiences, and powering AI-driven workflows.
From there, AI-powered marketing capabilities within the AI Marketing Cloud extend through a clear and flexible model:
The result is pricing that scales in ways teams can actually understand and delivers a tremendous amount of value. The price tag for most enterprise CDPs gets you just that — a CDP. With Treasure Data, the CDP is the foundation, but for a similar or even lower total cost of ownership it bundles in an omnichannel marketing suite and the Marketing Super Agent to help your team embrace AI-native marketing. The savings pile up further with the Trade-Up program.
Trade-Up program: Built for how value really emerges
Enterprise software rarely delivers its full value on day one.
Most teams start with a few high-impact use cases, prove ROI, and expand from there. Yet traditional pricing forces customers to commit to future scale before that value is realized.
Treasure Data’s Trade-Up program was designed to reflect reality.
With Trade-Up, teams can:
- Start with what they need today and implement Treasure Data quickly to drive immediate time to value
- Replace legacy platforms with incentive pricing:
- Switch your CDP and only pay Treasure Data in full after your incumbent CDP contract ends.
- Replace your email service provider (ESP) and/or customer engagement platforms (CEP) for up to 24 months free
- Expand capabilities as adoption grows
- Avoid over-committing before outcomes are proven
This is especially important in an AI-native environment, where early wins often unlock entirely new workflows teams did not anticipate. It’s also a way to reduce your total cost of ownership by breaking up with pricier platforms. One multi-billion retailer switched from Amperity to Treasure Data and projects to save over $3 million over multiple years.
Predictability enables speed
There is a persistent myth that predictable pricing limits flexibility.
In practice, the opposite is true.
When marketing leaders trust the economics of their platform:
- They activate more use cases
- They allow AI to operate more freely
- They scale what works instead of throttling it
- They move faster with less internal friction
Unpredictable pricing creates hesitation. Predictable pricing creates momentum.
Reframing the “expensive” conversation
Price is easy to label. Value is harder to measure.
When platforms are evaluated purely on sticker price, context disappears. Total cost of ownership, operational overhead, and opportunity cost are rarely part of the discussion. Smart buyers know to take this holistic view, however, and Treasure Data often comes out on top. Six Flags Entertainment implemented Treasure Data and saved over $1 million from tech consolidation.
A platform that looks cheaper upfront but takes years to implement or discourages experimentation with sync-based pricing often costs far more over time.
Treasure Data’s pricing is designed to reduce long-term friction, platform sprawl, and hidden costs. In that light, the question is not whether pricing is higher or lower than alternatives. The question is whether it is aligned with outcomes.
Built for how buyers decide today
Modern buyers are not optimizing for the most features per tier.
They are optimizing for confidence:
- Confidence they can start quickly
- Confidence they can scale safely
- Confidence pricing will not become a blocker as success grows
- Confidence the platform can evolve alongside their strategy
Our pricing is designed to support that mindset.
What comes next
We are continuing to invest in even greater transparency, including tools that help teams model usage, estimate cost based on real scenarios, and understand how value and pricing scale together.
Because when pricing is clear, teams move faster.
Simple pricing.
Predictable economics.
Built to trade up as value grows.
