KSN identifies the otherwise hidden links – call records or bank transfers for instance – between friends, families, co-workers and other communities and extracts significant social metrics, pinpointing who are the best connected and who plays the most important role in any group. In this way it reveals valuable new customer intelligence that – when added to existing customer information – can strengthen significantly user organisations’ customer acquisition, retention, cross-sell and up-sell campaigns.
LogoUsing KSN, companies can increase the accuracy and precision of their campaigns by leveraging the many more customer attributes that the module reveals, allowing them to better predict when customers may be about to churn to another provider, close an account, or buy a new product. A feature unique to KXEN allows the analysis of multiple networks and their evolution over time, exposing specific patterns of behaviors like rotational churn, fraud and identity theft.
“Traditional marketing relies on models based solely on customer-vendor interaction and assumes customers act independently of each other,” says KXEN’s founder and CEO Roger Haddad. “But the new social network technology in KSN recognises that customers do indeed interact with each other, and exploits that knowledge to drive up the effectiveness and completeness of marketing and sales campaigns.”
KSN integrates with and enriches existing data mining environments or may be deployed entirely standalone. Exploiting viral marketing thinking, it eliminates the normally tedious and labour intensive aspects of social network analysis. The module provides as many social network maps as users want, recognising that individuals may belong to many different networks across their business, family and social lives.
KSN, shipping from today, complements the existing KXEN Text Coder module which allows organisations to include plain text data into their analytics activities. Together the two modules, along with KXEN’s core software, are behind the company’s Data Fusion approach which combines structured and unstructured data from multiple sources to generate fast accurate results, thus maximising organisations’ return on analytics investments.