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What context influences

Contextual information affects multiple aspects of the search experience: Relevance scoring: The platform adjusts relevance scores for products related to cart items or purchase history, surfacing complementary or similar items more prominently. Facet selection: Layers intelligently selects which facets (filters) to display based on the customer’s browsing context and previous interactions. Sort order optimization: Customer behavior patterns influence default sorting, showing more relevant products first. Geographic personalization: Layers applies location-aware merchandising rules and product availability based on the customer’s region. Intent understanding: Prior searches and click behavior inform how new queries are interpreted, improving semantic understanding over time. User affinities: When you pass contextual data along with an identity, Layers derives affinity signals from cart contents and purchase history — such as preferred brands, product types, or variant options. These signals include both promotions (boosting products that match detected preferences) and demotions (slightly suppressing non-matching products within the same attribute). Low-confidence signals are automatically filtered out so only meaningful affinities influence results. The computed affinities are returned in the _meta.affinities array of Search, Browse, and Blocks API responses. This lets you see which attributes influenced ranking for the current request. Customer segmentation: Customer profile data (order history, spending patterns, loyalty status) enables personalized experiences for different customer segments. Marketing attribution: UTM parameters and campaign information help track the effectiveness of marketing efforts and can influence product recommendations. Channel-specific behavior: Shopping channel information enables different merchandising rules, sort orders, and analytics segmentation for web vs mobile app visitors.

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Implementation notes

  • Contextual information is processed in real-time; derived affinities are persisted per session to improve personalization across subsequent requests
  • No personally identifiable information (PII) is required; all data is behavioral and anonymous
  • Sort orders and merchandising rules always take precedence over contextual adjustments
  • Missing or incomplete contextual data won’t break functionality; the platform gracefully degrades to non-personalized results
  • For headless implementations, validate your contextual data structure matches the expected format to ensure proper personalization

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Privacy considerations

The Layers platform is designed with privacy in mind:
  • Device IDs are anonymous browser identifiers, not tied to personal information
  • Contextual data is used only for search personalization and is not shared with third parties
  • Customer IDs are encrypted and handled according to Shopify’s privacy standards
  • Geographic data is limited to city-level granularity, never precise coordinates

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See also