1st Edition

Machine-to-Machine Marketing (M3) via Anonymous Advertising Apps Anywhere Anytime (A5)

By Jesus Mena Copyright 2012
    436 Pages 92 B/W Illustrations
    by Auerbach Publications

    436 Pages
    by Auerbach Publications

    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:

    1. Why – Discusses the interactive environments and explains how M3 can be deployed
    2. How – Describes which technologies and solution providers can be used for executing M3
    3. Checklists – Contains lists of techniques, strategies, technologies, and solution providers for M3
    4. 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

    Introduction

    Why?
    M3 and A5
    What, Where, and How to Monetize Device Behaviors
    Building A5s
    Search Marketing versus Social Marketing via A5s
    Google, Facebook, and Twitter Places
    M3 via GPS and Wi-Fi Triangulation
    You Are Where You Will Be
    Data Mining Devices

    How
    M3 via Machine Learning
    Clustering Autonomously Device Behaviors
    Real-Time Demographic Networks
    Geolocation Triangulation Networks
    Deep Packet Inspection for M3
    Mob M3
    Data Aggregation and Sharing Networks
    Twitter Is Organic TV for M3
    Blogs Are Studios for M3
    Dialing Up iPhone and Android A5 Numbers
    Mobile Cookie A5s for M3
    Mobile Advertising Networks for A5
    M3 via Voice Recognition
    Facial Recognition
    Mobile Rich Media for M3 and A5
    Mobile Ad Exchanges for A5
    Anonymous Consumer Categories for M3
    Digital Fingerprinting for A5 and M3

    Checklists
    Why M3 Checklists?
    Checklist for Clustering Words and Consumer Behaviors
    Checklist of Clustering Software
    Checklist of Text Analytical Software
    Checklist of Classification Software
    Checklist of Streaming Analytical Software for M3
    A5 Checklist
    M3 Privacy Notification Checklist
    Checklist of M3 Marketing Terminology, Techniques, and Technologies
    Checklist of Web A5s Software and Services
    Ad Network M3 Checklist
    M3 Marketers Web Checklist
    Checklist of Social Metric Consultancies for M3
    Social Marketing Agencies’ Checklist for M3
    Recommendation Engines’ Checklist for M3
    Data Harvesters’ Checklist for A5
    WOM Techniques and Companies’ Checklist for M3
    Checklist of Mobile Website Developers for A5s
    Checklist for Constructing A5s
    Checklist of A5 Developers
    Checklist of A5 Marketing Companies
    M3 Marketer’s Checklist
    Checklist of Digital M3 and A5 Agencies
    Final M3 Marketer Checklist

    Case Studies
    Examples of M3 and A5 in Action
    WizRule Case Study
    Groupon Case Study
    Living Social Case Study
    Zynga Case Study
    Tippr Case Study
    BuyWithMe Case Study
    Hyundai Case Study
    Instapaper Case Study
    Kony Solutions Case Study
    Urban Airship Case Study
    Foursquare Case Studies
    Gowalla Case Studies
    Hipstamatic Case Study
    PointAbout Case Study
    MLB Case Study
    Dunkin’ Donuts Case Study
    Skyhook Case Study
    eBay Mobile Case Study
    TheFind Case Study
    Vivaki Case Studies
         Razorfish
         Digitas
    360i Case Studies
    Skype Case Studies
    Clearwire Case Study
    Greystripe Case Studies
    Univision Case Study
    LTech Case Studies
         Advent International
         New York Life
              Challenges
         PC Magazine
         PayPal
    Discovery Communications Case Study
    Touch Press Case Studies
         Major League Entertainment Experience
         Executive-Class Travel Experience
    Twitter Case Studies
         Best Buy
         Etsy 
         JetBlue 
         Moxsie
    Salesforce Case Study
    Shopkick Case Study
    IKEA Case Study
    Urban Outfitters Case Study
    Tumblr Case Study
    Crimson Hexagon Case Study
    Usablenet Case Studies
         ASOS 
         Fairmont Hotels
         Garnet Hill
         JC Penney
         Marks & Spencer
         PacSun
    Bazaarvoice Case Studies
         Benefit Cosmetics
         Sears Canada
         DRL 
         Evans Cycles
         Epson
    Quova Case Studies
         BBC 
         24/7 Real Media
    Procera Case Study
    Clickstream Technologies Case Studies
    RapLeaf Case Study
    TARGUSinfo Case Study
    Quantcast Case Studies
    BrightCove Case Study
    Rocket Fuel Case Studies
         Belvedere Vodka
         Brooks® 
         Ace Hardware
         Lord & Taylor
    Admeld Case Studies
    Pandora 
         IDG’s TechNetwork
         Forward Health
    adBrite Case Study
    Datran Media Case Studies
         ChaCha 
         PGA 
         Sony 
         eHarmony
         NASCAR
         BabytoBee
    NetMining Case Studies
    interclick Case Studies
    Audience Science Case Studies
         Automotive
         Consumer Products
         Entertainment
         Finance 
         Manufacturing
         Pharmaceutical
         Retail
    PubMatic Case Studies
    Turn Case Studies
         Automotive
         Retail 
         Telecommunications
    Red Aril Case Study
    DataXu Case Studies
         Education
         Travel 
         Financial
    Triggit Case Study
    BlueKai Case Studies
         Automotive
         Travel 
         Appliances
    Xplusone Case Study
    Placecast Case Studies
         The North Face
         White House Black Market
         SONIC 
         O2
    TellMe Case Studies
         Financial
         Banking 
         Shipping
    Mobile Posse Case Study
    Medialets Case Studies
         HBO 
         JP Morgan Chase
         MicroStrategy
    AdMob Case Studies
         Flixster 
         Volkswagen
         Adidas
    PhoneTag Case Study
    Xtract Case Study
    BayesiaLab Case Study
    PolyAnalyst Case Study
    Attensity Case Study
    Clarabridge Case Study
    dtSearch Case Studies
         Simon Delivers
         Cybergroup
         Reditus
    Lexalytics Case Studies
         DataSift 
         Northern Light
    Leximancer Case Study
    Nstein Case Studies
         ProQuest
         evolve24
         Gesca
    Recommind Case Studies
         Law 
         Energy 
         Search and Social
    C5.0 Case Study
    CART Case Study
    XperRule Miner Case Studies
         Financial
         Energy
    StreamBase Case Study
    Google Analytics Case Study
    SAS Case Study
    Unica Case Studies
         Citrix 
         Corel 
         Monster
    WebTrends Case Studies
         Virgin Mobile
         Rosetta Stone
         Gordmans
    ClickTale Case Study
    24/7 RealMedia Case Studies
         Jamba Juice
         Accor Group
         Personal Creations
         Forbes
    AdPepper Case Studies
         BBC 
         BDO Stoy Hayward
         T-Mobile
    Adtegrity Case Study
    BURST! Media Case Studies
         Take Care Health Systems
         Fuse 
         Kaboose
    Casale Media Case Studies
         Industry: Publishing
         Industry: Telecommunications
         Industry: Automotive
    Federated Media Case Studies
         Client: Milk-Bone
         Client: My Life Scoop (Intel)
         Client: Hyundai Tucson Movie Awards Season
    Gorilla Nation Media Case Study
    InterClick Case Studies
         Mobile 
         Automotive
         Juice
    Tribal Fusion Case Study
    Value-Ad Case Study
    DRIVEpm Case Studies
    Linkshare Case Studies
         Smartbargains.com
         Toshiba 
         North Face
    Epic Direct Case Study
    ShareASale Case Study
    AdKnowledge Case Study
    Marchex Case Study
    Vibrant Media Case Studies
         Bing™ 
         Toyota 
         Best Buy
         Canon
    BlogAds Case Studies
         Norml 
         Gala Darling
         Funky Downtown
         Drudge Retort
    Pheedo Case Study
    Sedo Case Study
    Cymfony Case Study
    Jivox Case Study
    ContextOptional Case Study
    KickApps Case Study
    ATG Case Study
    Aggerateknowledge Case Studies
    InfiniGraph Case Study
    SocialFlow Case Study
    Hyperdrive Interactive Case Studies
         Dreamfields Pasta
         LaRosa’s Pizzerias
         Sharpie 
         Sensor Technology Systems
    Brains on Fire Case Study
    Likeable Media Case Study
    360 Digital Influences Case Study
    BzzAgent Case Studies
         HTC 
         Thomas 
         Black Box Wine
    Keller Fay Group Case Studies
    Fanscape Case Study
    BrickFish Case Studies (Figure 4.17)
    TREMOR Case Study
    Porter Novelli Case Study
    Room 214 Case Studies
         Qwest 
         Travel Channel
         Strategic Media
         SmartPig
    Converseon Case Study
    Oddcast Case Studies
         McDonald’s
         Kellogg 
         Ford 
         M&M 
         Nokia
    Mr. Youth Case Study
    Blue Corona Case Study
    Mozeo Case Study
    Mobile Web Up Case Study
    Mobify Case Studies
         The New Yorker
         Threadless
         Alibris
    Usablenet Case Studies
         ASOS 
         Fairmont Hotels
         JC Penney
    Digby Case Study
    Bianor Case Study
    xCubeLabs Case Studies
         McIntosh Labs
         Eat That Frog
    Glympse Case Study
    DataXu Case Studies
         Social 
         Mobile 
         Auto
    GeniousRocket
         Amazon 
         Heinz 
         Aquafina
    MediaMath Case Studies
         Financial Advertiser
         Travel Advertiser
         Retail Advertiser
    Profero Case Study
    x + 1 Case Study
    Victors & Spoils Case Studies
         DISH Network
         Virgin America
         Harley–Davidson
    DoubleClick Case Study
    ClickTracks Case Study
    SiteSpect Case Study
    Jumptap Case Studies
         Hardees 
         Swap
    Valtira Case Study
    ContextOptional Case Study
    Satmetrix Case Study
    Nsquared Case Study
    FetchBack Case Studies
         Cosmetics
         Clothing
         Electronics
    Future 
         Mobility
         Intelligibility
         $

    Index

    Biography

    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.