Treasure Hunt: 'No Compute' Model from Treasure Data Promises More Predictable Pricing with Hybrid CDP

I’ve written about CDPs quite a bit. The category is rapidly evolving, particularly as data and context become more critical to the CMS and broader DXP ecosystem. 

There's also been the periodic acquisition of a CDP by an enterprise digital experience platform – think Optimizely buying Zaius, Sitecore absorbing Boxever, and Contentstack adding Lytics to its menu. These purchases were separated by time, but they speak to the critical need for data within their integrated offerings, especially when powering the “Holy Grail” of personalization. 

And as we know, that last piece is taking on a whole new urgency in the age of AI.

On a more architectural level, I’ve personally been crawling through the underbelly of CDPs for years now, connecting all kinds of apps and sources, inspecting JSON packages, and worrying incessantly about MTUs – those monthly tracked users that we care so much about. 

Most recently, when I was working on a big cloud-based SaaS product, it was breathtaking to watch the real-time events passing into our customer data platform. But it was also alarming as you considered the scale of users and the associated price tag. Ouch.

In every stack, there are multiple cost dimensions to consider, and CDPs bring their own unique challenges to the mix. Some platforms are focusing less on MTUs and zeroing in on active users, while others are embracing event-based pricing. There are also the processing resources that come in the form of compute. This is where overruns are a persistent and pesky concern. 

But Treasure Data is trying to change that. The intelligent customer data platform, which is built for enterprise scale and super-charged by AI, just unveiled a groundbreaking “No Compute” pricing model that completely decouples cost from processing resources. This could be the unearthing of buried treasure for users in a hunt for more efficient data solutions. 

This “No Compute” model is made possible by Treasure Data’s Hybrid CDP architecture. It primarily charges for the number of unified customer profiles stored and the behavioral events associated with them. This enables brands to run unlimited queries, segmentations, and activations – all without fear of runaway bills.

I caught up with Treasure Data’s co-founder and CEO, Kaz Ohta, who provided a bit more context. In his mind, predictable costs in a CDP should be a right, not a luxury.

“Our ‘No Compute’ pricing removes the biggest barrier to full CDP adoption – cost anxiety – so every team can activate data and AI agents with confidence.”

Here’s some of Ohta’s vision from 2023, which is worth a listen. He lays out the challenge surrounding loyalty during periods of economic uncertainty (which takes on a more pressing urgency today), and where a CDP can unlock potential around personalization and customer experience:

A lot has changed in two years, but it provides a foundation for how Ohta is steering Treasure Data towards success in an increasingly competitive market. He’s a compelling figure in the customer data landscape, and this disruptive new approach to pricing could be another element that elevates the company’s preference.

Solving the CDP industry’s cost dilemma

When it comes to selecting a CDP, it’s fair to say that enterprises have been in a pricing pickle. On one side, DXPs have been consuming CDP players into their pre-ordained stacks with integrated capabilities. Meanwhile, pure play solutions have been energizing their feature sets to enhance their independent relevance. 

Composed solutions with built-in customer data layers have some obvious advantages. But do they deliver as intended? I asked Ohta about the nuances between the DXP strategy and pure-play solutions like Treasure Data and where his company might have the upper hand. 

“DXPs such as Adobe, Acquia, and Optimizely take a different approach,” Ohta said. “They want to provide the complete stack. They bundle CDPs in their stack. However, we see many failed implementations of their CDP, just because leading DXPs mostly acquired their CDPs as a bolt-on solution. They are not really integrated. While I see the vision of DXPs, the execution of DXPs are poor: they, in reality, are Frankenstein stacks and a collection of different businesses – and that’s why buyers are not happy with them.”

Within these shifting business dynamics, pricing is a key consideration and fraught with challenges. Buyers are faced with a choice between packaged CDPs that focus on metering the number of profiles and compute, or composable-only CDPs that primarily meter the number of profiles and shift the processing burden to a cloud data warehouse, creating potentially unpredictable query charges.

Treasure Data’s new pricing model attempts to end this trade-off by separating economics from compute location. Customers get transparent pricing based primarily on the number of real-time, resolved customer profiles managed and the volume of associated behavioral events – think website visits, mobile app usage, email activities, and the like. 

“The true value is no longer just in data storage and movement, but in the intelligence you apply to it,” said Ohta. “Treasure Data is infused with AI everywhere, and now our customers pay for the value they get from AI-driven outcomes like better personalization, predictive insights, and campaign optimization – not for the underlying compute cycles.”

In an age where CDPs and data warehouses need to align in all the right ways, Treasure Data is providing an optimal solution. Whether workloads are running in its high-performance database engine or inside a customer’s CDW environments, enterprise teams get the same consistent experience without having to consider infrastructure or cost complexities. In this way, it’s a bit of a godsend.

I asked Ohta how this new approach to Treasure Data’s pricing model came about and how users are receiving it thus far. 

“Our largest customers have trillions of records and hundreds of millions of profiles managed with Treasure Data,” he said. “We pioneered this pricing model with them in the last few years and renewed their contracts under these terms. It’s worked well and now we’re rolling it out to other customers.”

Powered by Hybrid CDP architecture

Flexibility is a keystone attribute for any software solution. Composability can deliver on this promise, but there are instances where customers might want a hybrid approach over purely composable architectures based on specific use cases. 

Treasure Data conducted some research around the preference for a hybrid CDP architecture, where IT teams can choose the optimal processing environment to meet their needs. Based on its global survey of CDP buyers, 65% wanted a hybrid approach (edging up to 69% in the US). In the same report, a much smaller portion opted for packaged or composable architectures.

I asked Ohta how this reinforces Treasure Data’s position.

“While people talk a lot about the composable stack, the majority of buyers want choice and flexibility,” he said. “An enterprise has multiple brands, businesses, regions, and departments where they have different levels of martech and data maturity. Customers are asking to have choice over their architecture, anchored in a CDP or in a data warehouse, per brand, region, etc. Composability on its own requires the right engineering resources around, but hybrid lets you have the best of both worlds.”

How does Treasure Data’s unique Hybrid CDP architecture empower IT teams with choice? In two ways: First, they can leverage its Complete Mode, where Treasure Data provides the complete CDP solution – journey orchestration, segmentation and activation, ID unification, batch and real-time connectors, storage and compute – so you can implement it as a single source of truth.

There’s also a Composable Mode. Designed for more mature data engineering organizations, where a cloud data warehouse already exists as a single source of truth, Treasure Data builds a real-time cache of the customer 360 view from the CDW for instant customer data activations.

One of Treasure Data's key advantages is implementing the optimal processing environment based on preferences and use case suitability. This dual-mode approach helps preserve governance, maximize CDW ROI, and guarantee sub-second performance for time-sensitive engagement. All solid benefits.

Availability and pricing

According to Treasure Data, the new “No Compute” pricing model is generally available today for new customers and existing ones who want to make the move. It’s worth noting that there are multiple options for deploying Treasure Data, including through the AWS Marketplace. 

How do the pricing benefits translate in the real world? That’s the real question. The mechanics of the model make sense, and as Ohta said, they’ve seen success with existing users. Those metrics could be part of an upcoming webinar on The Power of a Hybrid CDP: Connected Experiences with Predictable Costs, which is being held on September 8th.

Obviously, a CDP’s total cost is a product of its usage, and this new model presents a big shift in how that functions. As far as assessing just how impactful this might be in your own stack, you’ll need to contact Treasure Data for a personalized cost analysis. There are different features composed into various packages across the CDP product landscape, so be sure to specify your goals when engaging with their pricing team – and do your homework on available integrations and warehouse options.

From a security and compliance perspective, Treasure Data has a trust and security center that includes all of its artifacts. It’s robust, but it’s always worth a look to ensure that you’re meeting the proper data privacy and regulatory requirements. There’s also an option to conduct a security review.

Why it matters

The CDP space is heating up as the market evolves and data warehouses take on an elevated role. Organizations are struggling to turn these resources into action, and leverage CDPs to power their personalization and customer 360 efforts. Despite the consolidation within the DXP category, pure play solutions are finding value with new features – and now, new pricing models that are strengthening their posture within the composable stack.  

With Treasure Data’s new “No Compute” pricing, customers are more empowered to utilize their CDP. It allows them to explore and assemble multiple segments, run various queries, and leverage its on-board AI agents – all without compute costs weighing them down. That means they’re free to align around outcomes that really matter to them, like the number of unified profiles and the behavioral events resulting from their marketing efforts.

On that topic, marketers using Treasure Data will also have more latitude to keep their existing CMS or DXP and their data warehouse – and still get real-time, AI-powered engagement at a predictable cost with a CDP that integrates with all these tools. This core flexibility is a key competitive advantage for Treasure Data within the pantheon of customer data platforms. 

As Ohta said, AI is a big part of the feature set for marketers and enterprises. But cost anxiety is a major pain point – and they’re helping to overcome that challenge.

“Our hybrid architecture blends historical depth with live behavioral data for sub-second personalization, all in a no-code, self-service environment for marketing teams,” he explained. “It’s about giving marketers the speed, insight, and freedom to act on every moment of opportunity without budget surprises.”

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