Treasure AI Launches Personalization Studio
The new marketer-facing user interface lets teams build, launch, and manage real-time website personalisation, powered by Treasure AI’s unified customer data and real-time decisioning.
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Treasure AI has announced Personalisation Studio, now available to all Treasure AI customers. The new marketer-facing user interface lets teams build, launch, and manage real-time website personalisation, powered by Treasure AI’s unified customer data and real-time decisioning.
The company also unveiled Engagement-Based Pricing, a new pricing approach tied directly to campaign performance.
Personalization Studio is part of Treasure AI’s Personalization AI Suite, within the company’s Agentic Experience Platform (AEP).
“Personalisation works when a brand can respond to what it knows about a customer in the moment,” said Rafa Flores, Chief Product and Growth Officer, Treasure AI.
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“Personalization Studio helps marketers move from customer insight to a relevant website experience using the context Treasure AI already has, while keeping the team in control of what goes live.”
From customer context to real-time experience
Brands’ customer data often already knows what a website visitor wants, but the website doesn’t. Standalone personalisation tools require separate integrations, data pipelines, and profile stores of their own, leaving marketers dependent on data and web teams every time they want to launch or change a campaign. This process leaves website experiences reliant on shallow, delayed, or session-only data.
Personalization Studio is built directly on top of Treasure AI’s customer data foundation, combining batch profile data — audiences, loyalty status, purchase history — with real-time behavoural signals to deliver sub-second personalised experiences on the website, without a separate profile store, export-and-sync process, or data pipeline to maintain.
Marketers work from one visual workspace: pick a page, select a content spot, choose an audience, and let AI propose the creative. They review, tweak, and launch.
With Personalization Studio, marketers can:
- Use existing audiences. Import segments already built in Treasure AI, along with profiles, loyalty data, and behavioural context, with no export, no sync, and no second profile store.
- Build campaigns visually. Select content spots, configure creative, preview, schedule, and launch with far less ongoing dependence on technical teams once initial setup is complete.
- Personalise in real time. Deliver experiences based on live behaviour, not a session-only snapshot, using full customer context through Treasure AI’s Real-Time 2.0 decision engine.
Because Personalization Studio runs on the same platform as the customer data that powers it, teams no longer need a standalone testing tool, a separate profile store, a data pipeline to keep them in sync, and a developer to hold it all together.
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Marketers move from audience insight to a live web experience without leaving the platform or the team, that already knows the customer.
“Most platforms were built to store data. We were built to activate it on behalf of a human being, in the right moment, in a way that feels like the brand actually knows you,” Flores said.
A pricing model built around results
Treasure AI also introduced a new engagement-based pricing model that ties email costs to customer actions, such as clicks, rather than the number of messages sent. It reflects a bold bet: if our intelligence doesn’t help you drive engagement and conversions, why should you pay for send volume alone?
“As the industry talks about outcome-based pricing, the real test is whether a platform’s economics align with the value it helps create. Treasure AI ties email pricing to customer engagement, such as clicks, rather than send volume. It’s a more accountable model, and we hope it encourages the industry to rethink what it charges for,” Flores said.
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Built for brands, agencies, and transformation partners
Personalization Studio helps enterprise brands and the partners they work with turn customer data into relevant, real-time website experiences.
Brand teams can build and manage personalisation programs using existing audiences and customer context, while agencies, consultancies, and systems integrators can help clients move from personalisation strategy to execution with less dependence on disconnected tools and technical handoffs.
