Untangling the social web
Software: From retailing to counterterrorism, the ability to analyse social connections is proving increasingly useful — TELECOMS operators naturally prize mobile-phone subscribers who spend a lot, but some thriftier customers, it turns out, are actually more valuable.
Context & Ripple Effects
The corpus had already traced the technical and commercial foundations of connection-based analysis, from mapping relationships on the web to mobile phones as a source of location and behavioural signals. A July 2010 report on the commercial value of personal data placed those signals within a wider contest to turn user information into revenue.
The immediate significance is a change in what telecoms measure: an individual subscriber's bill is not the sole proxy for value when that subscriber's position in a network affects other customers' behaviour.
First-order effects
- Telecoms operators can rank subscribers using social-connection analysis rather than spending alone, elevating some low-billing customers in retention and service decisions.
- Retailers and counterterrorism users gain a common analytical approach: treating relationships among people as an input alongside attributes of individual customers or subjects.
Second-order effects
- Customer-value models become more dependent on access to call and connection data, making data stewardship and analytical capability more important to operators' marketing and retention programmes.
- Operators that continue to optimise around individual spending risk misallocating incentives against rivals that identify customers with wider network influence.
Third-order effects
- If connection-based scoring spreads across sectors, the economic value of personal data shifts from isolated records toward datasets that preserve relationships and interaction patterns.
- The trend raises the stakes around surveillance network effects: organisations with the broadest relationship data can produce inferences that narrower datasets cannot readily replicate.
The trend: Social-network analysis is moving from a specialised web technique toward a general-purpose system for valuing customers and detecting patterns through their connections.