> ## Documentation Index
> Fetch the complete documentation index at: https://docs.uselayers.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Usage & privacy

> How contextual data influences search ranking and personalization in Layers, plus privacy guidelines, data retention rules, and PII handling considerations.

## 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](/api-reference/search), [Browse](/api-reference/browse), and [Blocks](/api-reference/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.

## 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

## 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

## See also

* [Contextual Information Overview](/engine/contextual-information) - How contextual information works and user identity
* [Context Data Structure](/engine/contextual-information/data-structure) - Complete reference for the context parameter
* [Storefront Pixel](/shopify-integration/storefront-pixel) - Automatic context collection
* [Query Understanding](/engine/user-intent-processing) - How context influences query interpretation
* [Search API](/api-reference/search) - Passing context in search requests
* [Browse API](/api-reference/browse) - Passing context in browse requests