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E-commerce Manager

Natural Language Product Search

This agentic AI task optimises e-commerce search functionality - essential for product search agents. The task configuration outlines how to:

  • Process natural language queries and user intent signals

  • Match search terms with relevant product attributes

  • Generate contextually appropriate search results

  • Provide alternative suggestions for unclear queries

  • Score and rank results by relevance factors


As a modular task, it integrates with catalogue and inventory systems, enabling AI agents to execute intelligent search processing within existing e-commerce workflows. The task specification includes outputs for query interpretation, result optimization, and suggestion generation, adaptable across various retail platforms and product categories.

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Example outputs:

{
  "interpreted_query": "Lightweight, waterproof hiking boots for women",
  "identified_intent": "Find comfortable, weather-resistant footwear for outdoor activities",
  "key_product_attributes": [
    "lightweight",
    "waterproof",
    "hiking boots",
    "women's"
  ],
  "suggested_categories": [
    "Outdoor Footwear",
    "Women's Hiking Boots",
    "Waterproof Shoes"
  ],
  "related_keywords": [
    "trail running shoes",
    "women's trekking boots",
    "gore-tex hiking shoes",
    "lightweight outdoor footwear"
  ],
  "query_specificity": "Moderately Specific",
  "suggested_filters": [
    "Gender:Women",
    "Activity:Hiking",
    "Feature:Waterproof",
    "Weight:Lightweight"
  ],
  "requires_clarification": false,
  "clarification_questions": [
    "What type of terrain will you be hiking on?",
    "Do you have a preference for low-cut or high-cut boots?",
    "Is there a specific brand you prefer for hiking boots?"

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Lead Scoring

Lead Scoring