There are also potential negative effects from use of data in a way that fails to take customer sensitivity into account the audience heard. An extreme example (reported in the New York Times) was of the Target retail chain predicting from customers' buying patterns those who were likely to be or soon become pregnant and sending them "appropriate" promotional material. When such material went to a 15-year-old, her father protested angrily. Target's analysis turned out to be right; she was pregnant; but it still didn't make for a happy customer.
A company will have to consider the impact of using a customer's praise for a product to pitch to their social-media "friends". While technology makes it possible, it may not be a good commercial move.
Panellist David Wasley of TradeMe, says his company cannot be as cavalier with its customer data as, say, Facebook is, because many of its customers are regulars. "We have to care about our users," he says. Committing money to a transaction with an unknown seller or buyer requires trust in the platform. "It's worth it to us to take care to retain that trust."
Members of the audience brought the discussion back to the UFB/RBI schemes and their suitability for big data. Aggregating and replicating relatively large databases is not a matter of bandwidth so much as latency, said one delegate. The perennial bugbear of data caps, said others, would be a limiting factor on big-data-style analysis until they disappeared.