by Cheryl D. Krivda Do you know the game “Six Degrees of Kevin Bacon?” It’s the one in which competitors try to link celebrities to the prolific “Footloose” star in six or fewer steps by finding movie relationships between him and various actors.
The promise of a Big Data enterprise is enticing. For companies that have successfully implemented Big Data strategies are seeing big payoffs.
Despite its promise of enabling seamless customer views and creating tangible business results, many marketers and customer experience leaders today are stymied by their data. Rather than quickly acting on data across all business units, numerous leaders have information overload when it comes to capturing, analyzing, and acting on Big Data.
In a recent CustomerThink blog post, my colleague, Jay Houghton, discussed some guiding principles required for a big data strategy to avoid getting into trouble. In addition to a sound strategy, adopting big data solutions into an organization also requires a unique implementation approach.
Applicants for this year’s freshman class at Ithaca College didn’t have to send their standardized test scores. If they did, the scores were considered, but so were some surprising other factors — how many friends and photos they had on social media, for instance. The same big data techniques that are transforming other industries are …
Most business leaders understand that an excellent customer experience is a brand differentiator. To achieve this mission, companies need to innovate. However, it's easy to get distracted by the bright, shiny objects afforded by the latest technology or to simply focus on process design. The most successful companies know that customers value experiences that demonstrate a deep understanding and respect for their needs and preferences.
“You should presume that someday, we will be able to make machines that can reason, think and do things better than we can,” Google co-founder Sergey Brin said in a conversation with Khosla Ventures founder Vinod Khosla.
Google Inc.’s Calico, a biotechnology firm created by the search-engine giant to study aging and related diseases, will delve into the genetic database amassed by a unit of Ancestry.com LLC to look for hereditary influences on longevity.
Pattern of Life analytics (POL) is a new predictive data analytical method that is similar to profiling. The implications of POL in the context of the Internet of Things (IoT) are far-reaching for both governments and business.
Data science is one of the biggest trends in business. For many teams, however, the concept remains a black box. Positioned at the intersection of engineering and statistics, we often thinking of data science as closely tied to IT, marketing, analytics, and product. We imagine complex algorithms, messy datasets, and endless lines of statistical code.
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