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EKG Catalog
Social Connections
EKGF/ekg-catalog

Social Connections

Client 360 / Customer 360 Relationships & Connections Business Connections Family Connections Political Connections Social Connections
Client 360 / Customer 360 Relationships & Connections Business Connections Family Connections Political Connections Social Connections
New to this diagram? Learn about the method: Use Case Tree · Use Case · Outcome

Social connections model relationships between customers revealed through interactions, referrals, social media, and shared activities. This use case addresses discovering unstructured social relationships, managing privacy concerns, distinguishing meaningful relationships from casual connections, detecting fake or fraudulent networks, integrating cross-platform social data, and leveraging social networks for fraud detection, referral optimization, risk assessment, and customer acquisition.

The Challenge

Organizations need to understand social networks but face obstacles:

  • Unstructured data sources — Social relationships are revealed through interactions, not formal declarations
  • Privacy concerns — Collecting and using social relationship data requires careful privacy management
  • Scale and complexity — Social networks can be vast and change rapidly
  • Fake or fraudulent connections — Bot networks and fake accounts can distort understanding
  • Cross-platform fragmentation — Social connections exist across multiple platforms and channels
  • Weak vs. strong ties — Distinguishing meaningful relationships from casual acquaintances

Traditional CRM systems capture explicit referrals but miss the broader social context that influences customer behavior.

Why EKG is Required

Enterprise Knowledge Graphs excel at modeling and analyzing social networks:

  • Graph-native social analysis — Natural representation of "friend-of-friend" relationships and network effects
  • Multi-source integration — Combine social media data, referral patterns, event attendance, and interaction history
  • Community detection — Automatically identify social clusters and communities within customer base
  • Influence measurement — Calculate social influence scores based on network position and connectivity
  • Temporal evolution — Track how social connections form, strengthen, and dissolve over time
  • Privacy-preserving analysis — Aggregate social patterns while protecting individual privacy

Business Value

  • Fraud detection — Identify fraud rings through analysis of connected accounts and suspicious patterns
  • Referral optimization — Target highly connected customers for referral programs and word-of-mouth marketing
  • Risk assessment — Understand social risk factors and identify customers in distress through their network
  • Customer acquisition — Leverage social networks for targeted marketing and lookalike audience identification
  • Community building — Foster customer communities and peer-to-peer engagement
  • Churn prediction — Detect churn risk when connected customers leave or reduce engagement

See also Social Graph for social media-specific relationship analysis.