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Automatically generates AI-friendly product descriptions by identifying causal relationships between product specifications and experiential value

Tokyo—October 13, 2026—Hakuhodo Inc., a leading integrated marketing and innovation company headquartered in Tokyo, and Hakuhodo DY ONE Inc. today announced the launch of Data Enrichment for Product Insight, a product data enrichment solution designed to help AI agents autonomously understand and select products. The solution joins Agentic Commerce ONE™, the Hakuhodo DY Group’s integrated suite of next-generation commerce solutions. Developed as an initiative of HCAI Professionals, the Group’s cross-Group collective of AI specialists, the service is available starting today.

Background: Product specifications alone are no longer enough to be selected by AI

Advances in generative AI and AI agents are driving the emergence of agentic commerce, in which users communicate broad intentions, needs or challenges to AI, and AI autonomously searches for, recommends and even purchases products on their behalf. Unlike traditional keyword-based search engines, AI agents interpret contextual information and identify products based on the user’s specific situation and objectives.

Consequently, traditional product master data held by companies, which relies heavily on functional specifications and technical attributes, often fails to provide AI agents with sufficient contextual information to accurately assess product relevance. This creates a growing risk that products may be excluded from recommendation candidates despite being well suited to a user’s needs.

Overview and key features of the solution

Data Enrichment for Product Insight is a data enrichment solution that enhances existing product master data with additional contextual information, enabling AI agents to interpret and match products with a higher level of accuracy.

At the core of the solution is a proprietary patent-pending technology that automatically identifies the experiential value sought by sei-katsu-sha (our term for the holistic person) and structures the objective causal relationships between product specifications and those benefits as a logic bridge.

For example, a washing machine’s specifications, such as “32 dB operating noise” and “heat pump drying system,” can be connected to experiential outcomes through a logic bridge that explains how the technology enables clothes to be dried gently and efficiently regardless of weather conditions or time of day, helping reduce the burden of household chores on busy nights. These structured relationships are stored within the product database and incorporated into product master data.

This enriched data structure enables AI agents to accurately interpret contextual requests. For example, when a user asks an AI assistant for a washing machine suitable for doing laundry late at night in a dual-income household, the AI can accurately identify the context and correctly recommend the company’s product.

Application areas for enriched product data

Product data generated and enriched through the solution can be utilized across a wide range of environments, from proprietary e-commerce platforms to external AI ecosystems.

• AIO (AI optimization) for owned e-commerce platforms and websites
  Enhances product catalogs as part of AIO initiatives for general-purpose large language models (LLMs) such as ChatGPT and Gemini.
• AIO for e-commerce marketplaces
  Supports catalog optimization for AI-powered shopping assistants and LLM-based recommendation environments within e-commerce platforms, including services such as Amazon Rufus (beta).
• Advanced integration with external data feeds
  Enables companies to provide not only product specifications but also contextual experiential value data through platforms such as Google Merchant Center and OpenAI Portal, enriching product feeds as part of broader AIO initiatives.
• Preparation for autonomous purchasing protocols
  Supports the development of product data infrastructure for a future in which AI agents autonomously handle purchasing processes, from inventory checks to order execution, through emerging autonomous purchasing protocols such as UCP, ACP and MCP. The enriched data helps external AI agents accurately understand user intent and identify the most relevant products.

About Agentic Commerce ONE™
Agentic Commerce ONE™ is an integrated suite of solutions for next-generation commerce provided by the Hakuhodo DY Group. The solutions anticipate an age in which AI autonomously acts on behalf of sei-katsu-sha, handling search, comparison and payment. Agentic Commerce ONE™ provides end-to-end support, from strategy development and brand experience design, to the development of data infrastructure compatible with the AI age, as well as implementation and operation.

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