102. Introduction of AI chat linked to product database
If you want to make AI chat a "substitute for sales," linking it to a product database is essential. By referencing the database for specifications, compatibility, and selection criteria, we can improve the accuracy of responses.
The main reason why AI chat fails to meet expectations is that product information is scattered in "text." Questions in the B2B manufacturing industry cannot be answered accurately unless they are structured data, such as applications, conditions, specifications, dimensions, materials, compatibility, and delivery times. Referring only to the text on the page leads to ambiguous answers and increases the risk of incorrect responses. This service will implement an AI chat that is linked to a product database (product master/specification database/compatibility tables/stock and delivery information, etc.). The chat will listen to the user's conditions, present relevant candidates from the database, and provide the basis (specification values and compatibility conditions), smoothly connecting to quotes, document downloads, and inquiries. ■ Provided Content (3 Points) 1. Product DB design/maintenance (items that can withstand AI reference/normalization) 2. AI chat implementation (database reference answers, candidate presentation, basis display) 3. Sales flow integration (quote condition collection, form/CRM integration, operational design) *First, please tell us the "number of products" and the "frequently asked questions from users (compatibility/selection/quotes)." We will design based on the optimal DB items.
- 企業：アンドワン 本社、東京支社、川崎営業所
- 価格：Other
