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Context-Aware Recommendations

Context-aware recommendations adapt to query context, category context, basket context, and user lifecycle to provide relevant recommendations.

Overview​

Context-aware recommendations use current context (query, category, basket, lifecycle) to provide more relevant and timely recommendations.

Context Types​

Query-Aware​

Recommendations based on search query:

{
  "context_type": "query_aware",
  "query": "running shoes",
  "recommendations": [
    "running_socks",
    "running_shorts",
    "running_accessories"
  ]
}

Category-Aware​

Recommendations based on category:

{
  "context_type": "category_aware",
  "category": "electronics",
  "recommendations": [
    "related_electronics",
    "compatible_accessories"
  ]
}

Basket-Aware​

Recommendations based on cart contents:

{
  "context_type": "basket_aware",
  "basket_items": ["prod_123", "prod_456"],
  "recommendations": [
    "frequently_bought_together",
    "complete_the_look"
  ]
}

Lifecycle-Aware​

Recommendations based on user lifecycle:

{
  "context_type": "lifecycle_aware",
  "user_stage": "new_customer",
  "recommendations": [
    "popular_products",
    "starter_kits",
    "best_sellers"
  ]
}

Best Practices​

  1. Use multiple contexts: Combine contexts for better relevance
  2. Prioritize context: Weight context appropriately
  3. Test performance: Measure context-aware vs generic recs
  4. Update contexts: Keep context data fresh