Intermediate

Search Personalization

Deliver personalized search results using user context, behavioral signals, role-based boosting, and adaptive ranking strategies.

Personalization Signals

👤

User Profile

Role, department, team, location, seniority, and expertise areas from the identity provider.

📊

Behavioral History

Past searches, clicked results, bookmarked documents, and time spent reading content.

🕑

Session Context

Current task context, recent queries in the session, and active project or ticket.

👥

Social Signals

What colleagues in similar roles find useful, trending documents in the department.

Personalized Ranking

Python — Personalized Score Boosting
def personalize_results(results, user_context):
    """Apply personalization boosts to search results."""
    for result in results:
        boost = 1.0

        # Department affinity boost
        if result["metadata"].get("department") == user_context["department"]:
            boost *= 1.3

        # Recency boost for user's team
        if result["metadata"].get("team") == user_context["team"]:
            boost *= 1.2

        # Previously accessed content boost
        if result["id"] in user_context.get("viewed_docs", set()):
            boost *= 0.8  # Slight penalty - they've already seen it

        # Role-based relevance
        if user_context["role"] in result["metadata"].get("target_roles", []):
            boost *= 1.4

        result["personalized_score"] = result["base_score"] * boost

    return sorted(results, key=lambda x: x["personalized_score"], reverse=True)

Privacy Considerations

  • Transparency: Users should understand why results are personalized and be able to opt out.
  • Data minimization: Collect only the signals needed for personalization, not comprehensive tracking.
  • Retention limits: Set TTLs on behavioral data. Recent behavior is more predictive than old data.
  • Filter bubbles: Ensure personalization doesn't hide important content. Show a "non-personalized" toggle.
  • Access control: Never use personalization to surface documents the user doesn't have permission to view.
✅
Start simple: Role-based and department-based boosting delivers 80% of personalization value with minimal complexity. Add behavioral signals only after you have sufficient usage data and proper privacy controls in place.