AI Decisioning with Real-Time Personalization

Kickstart or enhance your personalization strategy with autonomous AI agents. Embrace AI decisioning that leverages real-time data and memory to learn, decide, and personalize every customer interaction in the moment.
AI Decisioning with Real-Time Personalization

The keys to agentic personalization

Experience the difference of AI decisioning and real-time personalization powered by Treasure Data:

  • Real time: The system adapts messaging, recommendations, and support instantly based on live data and customer behavior.
  • Autonomous AI Agents: These agents act independently, learning and making decisions without constant human input.
  • Personalization: Hyper-personalization is central to every use case, from onboarding to product recommendations. Messaging, offers, and timing are customized per user.
  • Continuous learning / AI signals: The agents learn each customer’s motivations, preferences, and behaviors.
The keys to agentic personalization

We couldn’t afford to hire and retain a lot of data scientists. So we focused on making it very easy for the marketers to use predictive modeling capabilities coming out of our CDP, Treasure Data. We’ve been able to deploy LTV and RFM models very easily to the business.”

Anushil Kumar

Anushil Kumar

VP, Enterprise Architecture and Innovation

Constellation Brands

How to drive value from AI Decisioning with Real-Time Personalization

Drive adoption

Onboard new customers

Learn each new user’s behavior and preferences, automatically adjusting messaging to guide them through the most relevant onboarding steps.

Boost revenue

Recover abandoned carts

Trigger personalized messages at the right time with behavior-based incentives or reminders to encourage customers to return and complete their purchase.

Reduce churn

Retain and reactivate customers

Identify at-risk customers and adjust their messaging, timing, and offers to encourage re-engagement.

Increase CLTV

Personalize recommendations

Continuously adapt recommendations based on real-time data, ensuring customers receive the most relevant, timely, and personalized suggestions.

Improve loyalty

Provide proactive customer support

Create a supportive experience by monitoring cross-channel behavior and proactively suggest solutions or offer help at critical moments.

Video: How to use AI to break away from the competition

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Treasure Data vs the competition

Capability

Other solutions

Treasure Data

Personalization

Static segments, pre-defined journeys, or batch processing

Memory-rich AI agents continuously learn, adapt, and personalize in real time

Decisioning

Manual configuration of rules and workflows, or slow A/B tests

Fully autonomous AI agents make decisions and take action without human intervention

Segmentation

Complex segmentation strategies and rule-based workflows

Adapts in real-time to each customer's behavior and context

Memory

Lacks deep, contextual understanding of customer histories and behavior

Access to a customer's full data history, preferences, and behaviors

Engagement

Limited to specific touchpoints or campaign windows

Adapts to the customer journey and real-time data

AI is really powerful for leveraging the consumer data we have. Having a unified consumer view … can be overwhelming, so we use AI to manage this more efficiently.”

Natália Spada Ribeiro

Natália Spada Ribeiro

Group Data Product Manager

Nestlé

Drive smarter, more efficient engagement with AI