Missed our webinar, The Present & Future of AI & Customer Data: Insights from Kaz Ohta, CEO of Treasure Data? Here are the key takeaways.
The challenge: Disjointed customer experiences
Every business interacts with customers across multiple channels—online, in-store, through customer support, and more. However, data from these interactions is often siloed across different departments, creating inconsistent experiences that negatively impact revenue and efficiency. Treasure Data's vision of connected customer experiences is simple: put customer data at the heart of the enterprise to drive smarter decisions, not just in marketing but across sales, customer support, compliance, and even supply chain management.
Today, Treasure Data powers customer experiences for 400 global brands, including AB InBev, AXA, Nestlé, Honda, and Sony. In fact, about 60% of the internet-connected population—approximately 3 billion people—have their data managed within our system. Among the more than 190 CDP vendors in the market, we are the only independent provider recognized as a leader by Gartner, Forrester, and IDC.
The future of AI and customer data
AI is rapidly transforming industries. Generative AI has already made significant strides in areas like IT security and software engineering, but when it comes to sales, marketing, and customer operations, AI works best with proprietary customer data. Unlike foundational models that have generalized knowledge, AI-powered customer experiences require deep integration with a company’s own data—and that’s where Treasure Data comes in.
Key AI challenges in customer experience
While AI presents massive opportunities, there are three major challenges brands must address:
- Lack of personalization – AI agents often lack the necessary context about a customer’s past interactions, leading to impersonal and frustrating experiences.
- Short-term memory – AI systems today struggle to retain long-term context, making every interaction feel like starting from scratch.
- Balancing automation with human oversight – While AI can accelerate tasks like content creation, human judgment is still critical for quality control and strategy.
At Treasure Data, we believe AI should act as a teammate, not just an assistant. It should handle repetitive, data-intensive tasks while humans focus on creativity, strategy, and customer relationships.
The evolution of CDPs in an AI-powered world
Over the past decade, the marketing technology landscape has exploded, with thousands of SaaS solutions creating feature overload. Companies are now shifting toward consolidation, looking for enterprise-wide solutions that break down silos and deliver real business impact.
Why does this matter for CDPs? Many martech vendors are now branding themselves as CDPs, but true enterprise-grade CDPs must:
- Unify real-time and batch data across the business
- Create a single, comprehensive customer profile
- Enable AI-powered decision-making across departments
AI + CDP: A new era of customer intelligence
CDPs can serve as the long-term memory for AI, allowing businesses to leverage historical customer data to enhance AI-generated insights. Imagine AI-powered marketing campaigns that instantly analyze years of behavioral data to deliver hyper-personalized experiences.
We’re already prototyping AI-driven solutions like Treasure Retail, which enables in-store AI assistants to help customers find products, check inventory, and provide personalized recommendations—all powered by real-time CDP data.
Looking ahead: AI as a teammate
In 2025, we anticipate AI evolving into a true teammate in areas like data analytics, marketing operations, copywriting and creative development, and customer support automation. CDPs will play a crucial role by ensuring AI agents have the context and memory needed to make intelligent decisions. Instead of AI-to-AI collaboration, the real unlock in enterprise AI will be human-to-AI collaboration.
We’re excited about the future of AI and CDP and actively working on innovations that will shape this space.
