What a Big-Data Business Model Looks Like - R “Ray” Wang by R “Ray” Wang | 10:00 AM December 6, 2012 The rise of big data is an exciting — if in some cases scary — development for business. Together with the complementary technology forces of social, mobile, the cloud, and unified communications, big data brings countless new opportunities for learning about customers and their wants and needs. It also brings the potential for disruption, and realignment. Organizations that truly embrace big data can create new opportunities for strategic differentiation in this era of engagement. There are a number of new business models emerging in the big data world. Differentiation creates new experiences. Big data offers opportunities for many more service offerings that will improve customer satisfaction and provide contextual relevance. Brokering augments the value of information. For example, retailers like Amazon could sell raw information on the hottest purchase categories. Delivery networks enable the monetization of data.
Contextual Marketing | Big Data Analytics Globys combines data science and advanced marketing techniques to uncover customer motivations and then dynamically trigger the right message at the right time in the right context The value that this approach to contextual marketing offers is helping carriers to monetize their data by addressing customer needs in the specific context of a moment.”Yankee Group Globys’ Contextual Marketing solutions enable mobile operators to leverage big data and advanced marketing to make a paradigm shift on how they market to their existing customers. The Globys solutions are based on unique, patent-pending techniques developed specifically to address the needs of targeted one-to-one contextual marketing. Today operators around the world are leveraging our Contextual Marketing solutions to drive game changing results around maximizing customers’ lifetime value — generating 10-15 percent improvements in customer revenues and retention. Learn More About Our Contextual Marketing Solutions CMO Council
Mobile Application Analytics | Mobile Application Performance Analysis | Appcelerator Inc Appcelerator Analytics Appcelerator Analytics, part of the Appcelerator Platform, gives you deep, real-time insight and visibility into how your published mobile apps are performing, what features are being used the most, and where there are opportunities for improvement to provide the most compelling experience. By understanding your users’ behavior, their preferences and application usage, you can continue to refine the application for continued successful adoption. With Appcelerator Analytics, user and session application events are automatically added to your mobile apps. User analytics are central for measuring top-line application adoption metrics such as the tracking of new, active and total users over time, by geography, or by platform over a specific time period.Session analytics measure engagement with your application. These allow you to view total sessions, average sessions, and session length over time, by geography or by platform.
Gnip - Providing Social Media Data for the Enterprise Data virtualization makes 'information as a service' a reality: Forrester Enterprise architects are getting busier by the month. Not only do they need plan out service-oriented architecture and cloud services at the application level, but need to start considering how data can fit into the agile, flexible organization -- especially since many are starting to become overwhelmed by multi-terabytes and even petabytes' worth of data. Data virtualization, now enabled by today's generation of solutions, is seen by many as the latest great enabler for getting information out across the enterprise. Once data virtualization takes hold, 'Information as a Service' -- in which data and analysis is available, on demand, to anyone who needs it -- becomes more of a reality. But does anyone really "get" data virtualization and IaaS? Data virtualization offers a means to get around the relatively clunky ETL (extract, transform, load) paradigm that has dominated integration projects for the past decade or so, Hopkins says. However, it's going to take time to get there.
Big Data Hype (and Reality) - Gregory Piatetsky-Shapiro The potential of “big data” has been receiving tremendous attention lately, and not just on HBR’s site. With interest in the topic growing exponentially, it has been the focus of countless articles and perhaps too many meetings and conferences. But to the extent that big data will have big impact, it might not be in the classic territory addressed by analytics. Film ratings. In just two weeks, several teams had beaten the Netflix algorithm, although by very small amounts, but after that, progress was surprisingly slow. Netflix Price Competition Progress It took about three years before the BellKor’s Pragmatic Chaos team managed to win the prize with a score of 0.8567 RMSE. Customer attrition. A study [pdf] that Brij Masand and I conducted would suggest the answer is no. Web advertising response. The average CTR% for display ads has been reported as low as 0.1-0.2%. What are we to conclude from these three areas — all of them problems with fine, highly motivated minds focused on them?