Why graph discovery? - Aster Execution Engine

Teradata Aster® Developer Guide

Product
Aster Execution Engine
Release Number
7.00.02
Published
July 2017
Language
English (United States)
Last Update
2018-04-13
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lifecycle
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Product Category
Software
Graph discovery augments content with context:
  • Content-based decision models consider an individual entity as a discrete unit of analysis. Entities have attributes such as age, income, and sex.
  • Context-based decision models analyzing interdependencies between entities as in a social network, fraud network, or online community.
For example, graph discovery helps you:
  • Target key customers for special offers by identifying influencer, bridge, and other social roles.
  • Target high sentiment influencer for viral marketing campaigns.
  • Target low sentiment bridge to prevent churn and community disconnection.
  • Improve products by identifying clusters of users (sub-graphs) that have difficulty using the product due to localization issues.
  • Increase product adoption or decrease churn by targeting more central members of social networks for special offers.
  • Decrease revenue loss by identifying fraudulent actors in a network based on their patterns of interaction.
  • Harness community effects to improve product recommendations, thereby increasing the likelihood of selling.