Contextual Embeds: How They Work and How to Configure Them

Overview: When and Why to Use Contextual Embeds

Use Contextual Embeds when you want to display highly relevant, adaptive video feeds inside your website or app, based on what a user is viewing, searching for, or interested in at that moment.

Unlike static or generic embeds, Contextual Embeds dynamically adjust content using real-time signals such as page context, search intent, user attributes, and location. This ensures users see videos that feel timely, personalized, and directly aligned with their current journey - driving deeper engagement, longer sessions, and higher content relevance.

This matters because modern audiences expect content to respond to context, not just identity.

What Are Contextual Feeds?

A Contextual Feed is a dynamically generated video stream powered by Genuin Adaptive Intelligence, using real-time signals from a user’s environment and behavior.

These signals may include:

Page context (what content or category the user is viewing)
Search keywords entered on your site or app
User attributes such as interests or profile data
Geographic signals like latitude and longitude

Genuin processes these inputs together to determine intent and relevance, then surfaces videos most likely to resonate in that specific moment.

The result: a feed that adapts continuously as user context changes.

How Contextual Feeds Work

Contextual Feeds operate on a multi-signal recommendation model, where different types of context are evaluated independently and combined intelligently.

At any given time, the system prioritizes the strongest available signal, ensuring high-quality recommendations even when some data points are missing (for example, anonymous or first-time users).

Supported Context Inputs

Page Context

The page or screen a user is currently viewing, such as:

“SUV Listings”
“Car Loan Guides”
“Winter Fashion Collection”

This helps align video content with the surrounding editorial or commerce experience.

Search Query Context

Keywords or phrases entered by the user within your site or app.These signals indicate explicit intent and are given high relevance in feed generation.

User Profile Context

Includes available user attributes such as:

Age range
Interests
Bio or stated preferences

When present, these signals help personalize feeds across sessions.

Geographic Context

Latitude and longitude, typically derived from IP or device data, are used to:

Localize recommendations
Surface regionally relevant or nearby content

Video Selection and Ranking Logic

Contextual Feeds use a multi-stage selection and ranking process to balance relevance, freshness, and engagement.

1. User Profile–Based Selection

Videos are first matched against known user interests and attributes.
If no strong matches exist (cold-start scenarios), the system automatically falls back to contextual or location-based signals.

Engagement weighting within this stage:

Shares (highest influence)
Sparks/Reactions (medium)
Views (baseline)

2. Context-Based Selection

Text-based inputs (page context, search terms, bios) are analyzed to extract:
- Keywords
- Topics
- Implied intent
Location signals are applied where relevant.
These signals are converted into structured queries and executed via OpenSearch to retrieve matching videos.

3. Final Ranking and Feed Output

Each candidate video is assigned a final score using a balanced weighting model:

index.html

Final_score = 0.34 × Context_score
              + 0.33 × Recency_score
              + 0.33 × Popularity_score

Videos are then sorted in descending order of this score and delivered as a ranked feed.

This ensures users see content that is:

Contextually relevant
Recently published
Proven to engage other users

Contextual Feed Configuration Parameters

To enable contextual recommendations, your embed or SDK implementation passes a structured payload including:

Brand and community scope
Optional user identifiers and interests
Contextual feed flag
Ranking weights
Page and location context

These parameters allow fine-grained control over how feeds behave, without hardcoding content decisions.

index.html

{ 
  "brand_id": int, 
  "communities": [ 
   { 
     "community_uuid": "string", 
     "groups": ["string", "string", "string"] 
   }, 
   { 
     "community_uuid": "string", 
     "groups": ["string", "string", "string"] 
   } 
  ], 
  "user_uuid": "string", 
  "user_interest": ["string", "string", "string"], 
  "page_session": "string", 
  "genuin_user": true, 
  "limit": int, 
  "contextual_feed": true, 
  "user_weight": float, 
  "recency_weight": float,   
  "popularity_weight": float, 
  "page_context": { 
    "page_context": "string", 
    "compare_with": "video/community/brand/group/location",
    "location": [lat, long], 
    "location_radius": int 
  } 
}

How the compare_with Parameter Works

The compare_with field determines how contextual similarity is evaluated:

Value	Behaviour
community	Matches videos from communities with similar descriptions
brand	Surfaces videos linked to related brands
video	Finds videos with similar contextual signals
location	Filters content within a defined geographic radius

If contextual_feed is set to false, Genuin defaults to standard (non-contextual) feed logic.

Contextual Embed Activation Flow

Once enabled, the system follows this sequence:

Contextual feed flag is validated
Videos are filtered by brand_id and scope
A context vector is generated from available inputs
Videos receive contextual relevance scores
Final ranking is applied
A personalized feed is returned to the embed

This flow allows every embed to respond dynamically to user behavior without manual intervention.

How to Configure Contextual Feeds Across Platforms

Contextual Feeds can be implemented using Genuin’s SDKs across platforms:

Each SDK provides:

Step-by-step integration guidance
Configuration examples
Platform-specific best practices

Refer to the respective SDK documentation for implementation details.

Summary: Why Contextual Embeds Matter

Contextual Embeds enable media and commerce brands to move beyond static content blocks and deliver real-time, intent-aware video experiences.

By combining page signals, user behavior, and location data - within a governed, configurable framework - Contextual Feeds help you:

Increase relevance and engagement
Improve content discovery
Personalize experiences without sacrificing control
Scale intelligent video across all owned digital surfaces

This ensures every embed feels purposeful, timely, and aligned with the user’s journey - while remaining fully brand-safe and auditable.