In today's wireless environment, marketing is more frequently occurring at the server-to-device level--with that device being anything from a laptop or phone to a TV or car. In this real-time digital marketplace, human attributes such as income, marital status, and age are not the most reliable attributes for modeling consumer behaviors. A more effective approach is to monitor and model the consumer's device activities and behavioral patterns.
Machine-to-Machine Marketing (M3) via Anonymous Advertising Apps Anywhere Anytime (A5) examines the technologies, software, networks, mechanisms, techniques, and solution providers that are shaping the next generation of mobile advertising. Discussing the interactive environments that comprise the web, it explains how to deploy Machine-to-Machine Marketing (M3) and Anonymous Advertising Apps Anywhere Anytime (A5). The book is organized into four sections:
- Why - Discusses the interactive environments and explains how M3 can be deployed
- How - Describes which technologies and solution providers can be used for executing M3
- Checklists - Contains lists of techniques, strategies, technologies, and solution providers for M3
- Case Studies - Illustrates M3 and A5 implementations in companies across various industries
Providing wide-ranging coverage that touches on data mining, the web, social media, marketing, and mobile communications, the book's case studies show how M3 and A5 are being implemented at JP Morgan Chase, Hyundai, Dunkin' Donuts, New York Life, Twitter, Best Buy, JetBlue, IKEA, Urban Outfitters, JC Penney, Sony, eHarmony, and NASCAR just to name a few. These case studies provide you with the real-world insight needed to market effectively and profitably well into the future.
Each company, network, and resource mentioned in the book can be accessed through the hundreds of links included on the book's companion site: www.jesusmena.com
Jesus Mena is a former Internal Revenue Service Artificial Intelligence specialist and the author of numerous data mining, web analytics, law enforcement, homeland security, forensic, and marketing books. Mena has also written dozens of articles and consulted with several businesses and governmental agencies. He has over 20 years' experience in expert systems, rule induction, decision trees, neural networks, self-organizing maps, regression, visualization, and machine learning and has worked on data mining projects involving clustering, segmentation, classification, profiling and personalization with government, web, retail, insurance, credit card, financial and healthcare data sets. He has worked, written, and lectured on various behavioral analytics and social networking techniques, personalization mechanisms, web and mobile networks, real-time psychographics, tracking and profiling engines, log analyzing tools, packet sniffers, voice and text recognition software, geolocation and behavioral targeting systems, real-time streaming analytical software, ensemble techniques, and digital fingerprinting.
