Convenience store retailers may eventually reach a point of diminishing returns and so they are trying to find out ways to use transactional promotional and loyalty data in a better manner. we could get valuable insight from Big Data by deciding what type of data streams could combine to provide insights. According to Jim Manzi of the analytics firm Applied Predictive Technologies, Arlington, VA, if retailers want to understand how certain business choices affect the bottom line, Customer Data, Transaction Log Data, Weather Information, Area Demographics and Competitor fuel pricing must be prioritized. Full-motion video from all stores, High-volume website clickstreams, and Raw Twitter feeds are less important. According to Manzi, tweeter feeds are not that important for analysis as they cannot help to out the cause and effect on key-metrics. There is a "first law of big data usefulness," said Adrian Bridgwter a contributing editor at Forbes magazine. The first law says, "The degree to which we take the exact depth of big data analytics is directly determined by the corresponding level of insight it produces and where we can still say that we gain 'productive incremental value' from doing so." Businesses like convenience stores gather a lot of information for regulatory purposes, which could ultimately be analyzed as people grow in their technological sophistication, Bridgwater said. Read more at:

http://www.cspnet.com/industry-news-analysis/technology/articles/what-first-law-big-data-usefulness