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The Inspired by Your Browsing History algorithm refines recommendations by mining a shopper’s past interactions—both within the current session and across previous visits. By blending session-based signals with content-based analysis of viewed items, IBYBH delivers highly personalized suggestions that resonate with each user’s unique interests.

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How It Works

  1. Session-Based Modeling
    Examines the sequence of pages visited, dwell times, and in-session interactions to surface products aligned with the user’s immediate browsing context.
  2. Content-Based Analysis
    Analyzes attributes (e.g., category, brand, features) of items the user engaged with, building a profile of their long-term preferences.
  3. Hybrid Scoring
    Combines session and content signals into a unified relevance score, ranking products that best match both recent and historical behaviors.

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Supported Rule Types

  • Global
  • Home Page
  • Product
  • Category
  • Search

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Behavior

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Non-Logged-In Users

  • With Session Data: IBYBH populates recommendations based on items viewed in the current session.
  • Cold-Start (No Views):
    • Fallback Disabled: Widget remains hidden.
    • Fallback Enabled: Displays a fallback algorithm (e.g., “Popular Products”) to avoid empty slots.

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Logged-In Users

  • With Past & Current Sessions: Leverages full browsing history across sessions for deeper personalization.
  • New Accounts (No History):
    • Fallback Disabled: Widget remains hidden until interaction data is collected.
    • Fallback Enabled: Shows fallback recommendations to guide first-time visitors.

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When to Use

  • Personalized Engagement: Deliver tailored suggestions that adapt to both immediate interests and established affinities.
  • Feed-Based Discovery: Enhance “infinite scroll” or content-feed experiences where users expect a continuous flow of relevant items.
  • Multi-Session Continuity: For returning shoppers, maintain personalized continuity across visits without manual curation.

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Example

  1. A shopper browses several bohemian dresses across multiple sessions.
  2. IBYBH analyzes both their recent clicks and overall browsing patterns.
  3. On the Homepage, the widget surfaces new boho-style dresses and complementary accessories.
  4. On a Product Page, it highlights the exact dress previously viewed plus similar items in matching colors or prints.
By weaving together session context and content attributes, IBYBH keeps recommendations fresh, relevant, and deeply personalized—turning every visit into a bespoke shopping journey.