Social Media Based Predictive Analytics

Jeff LoCastro, Founder and CEO of Neener Analytics based in the United States participate in Risk Roundup to discuss Social Media Based Predictive Analytics. Social Media Based Predictive Analytics Social media is becoming as common as air, food, and water. Now irrespective of nations, when almost everyone is using social media today, the question is why is social media gaining enormous popularity and usage? Is it because social media allows social connectivity? Perhaps! Social media seems to have made it easier for individuals and entities across nations: its government, industries, organizations, and academia (NGIOA) to make a personal connection with friends, family, followers, and fans. It has changed the way we communicate within, between, and across nations’ boundaries in cyberspace, geospace, and space (CGS). It is because of social media that communication is now personal and direct. In addition to the communication becoming personal and direct, the feedback is also personal and direct. Why is that important? It is important because the role of the middleman is disappearing. As a result, entities are seeing their initiatives, products, and services in ways they imagined, was not possible before. So how do individuals being connected on social media help entities across NGIOA in seeing things differently or understand things better or take more effective decisions? It is by using social media analytics. Social Media Analytics has made it important for entities across NGIOA to understand or listen to what is being said on social media. What is being said about entities or businesses and their products/services was important before. However, what is being said about businesses, products,s or services in the digital global age has become a matter of survival and sustainability. While social media listening or monitoring is intended to help entities across NGIOA understand what is being said about them on the social web at any given time, understanding it in real-time is now a survival necessity. Over the years, businesses across many industries have been monitoring their customers’ posts on their websites. This has been more of an attempt to identify, contain and manage some angry or unhappy customers.  Is that approach sufficient today in a digital global age? Perhaps not.  When we evaluate the “Lending Industry”, especially how lenders evaluated their lending decisions before digitization, what stands out is, how decisions are taken today, which is strikingly different from how lending decisions were made yesterday. Social media and predictive analytical tools have given entities across NGIOA an opportunity and platform to understand and connect with customers, citizens, followers, fans directly. While having that connection, and being able to reach fans and followers immediately and directly is working wonders for branding and understanding concerns and complaints, it is only the first step in the digital journey. Entities across NGIOA need to broaden their social connectivity in a digital global age. Lending decisions are only the first step. It is time to take a closer look at the potential of  Social Media-Based Predictive Analytics! For more please watch the Risk Roundup Webcast or hear the Risk Roundup Podcast About the Guest Jeff LoCastro is the Founder and CEO of “Neener Analytics” and is based in the United States. Jeff started his first company when he was a sophomore in college, the second one when he was a junior. From being a part of the first “Online Social Network” in the world to scaling a location-based car care chain both in the US and China, to developing commercial and multifamily buildings to creating a large-scale professional association. Jeff has always been developing, creating, scaling, and delivering a high-quality product with a focus on Excellence, not just profits. He believes that “if you are only focused on “winning”, you are not focused on the things it takes to win”. Jeff is also a published author about business building, management, and strategy with editorials appearing in Los Angeles Business Journal, San Jose Business Journal, Central Valley Business Journal, The China Business Review, Bloomberg China, and Asian Business Daily (Australia & China). As a public speaker about business strategy, product development, execution, and creating a nimble organization, some of his recent engagements include the World Affairs Council, UC Irvine, Internet World, and conferences in the US and abroad. About Risk Group Risk Group is a strategic security risk research and advisory organization. Copyright Risk Group LLC. All Rights Reserved Reference Episodes Machine Learning Based Market ForecastingMachine Learning on Insurance Data to Predict HospitalizationFuture of Work – Battle between Human Work Force and Machine Work ForceMachine Learning Bias – An Existential RiskUnderstanding Cognitive ComputingCloud Powered Artificial Intelligence PlatformBlockchain & Machine Learning Based Content PlatformPowering Collective Human IntelligenceCollective IntelligenceCollective Machine IntelligenceArtificial Intelligence based Healthcare SystemMachine Learning for Medical DiagnosisScience of Intelligence – Human Intelligence to Computational IntelligenceHow will Deep Learning Disrupt Financial Sector?Credit Scoring using Machine LearningCancer Detection to Credit Lending – Intelligent Machine Applications of Artificial IntelligenceAdvances in Artificial Intelligence – Human and Non-Human Gesture and Action RecognitionFinancial Industry Moves Towards Artificial Intelligence Based MachinesMan-Machine Interaction – Communicating with ComputersMachine Intelligence Impact on Human SocietyThe Rise of Artificial IntelligenceArtificial Intelligence driven Cyber-SecurityAdvances in Artificial Intelligence – Human and Non-Human Gesture and Action RecognitionAgricultural RobotsComputational Intelligence & Security RisksBusiness Logic Monitoring and AutomationSocietal Impact of RoboticsEnterprise Digital Intelligence Risks – Need for Smarter Search Tools The post Social Media Based Predictive Analytics appeared first on Risk Group.