Machine-to-machine marketing (M3) via anonymous advertising apps anywhere anytime (A5). (2012)
- Record Type:
- Book
- Title:
- Machine-to-machine marketing (M3) via anonymous advertising apps anywhere anytime (A5). (2012)
- Main Title:
- Machine-to-machine marketing (M3) via anonymous advertising apps anywhere anytime (A5)
- Further Information:
- Note: Jesus Mena.
- Other Names:
- Mena, Jesus
- Contents:
- 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’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 … (more)
- Publisher Details:
- Place of publication not identified : Auerbach Publications
- Publication Date:
- 2012
- Extent:
- 1 online resource, illustrations
- Subjects:
- 658.872
Internet advertising
Internet marketing
Application software -- Development
Machine learning
Electronic commerce - Languages:
- English
- ISBNs:
- 9781466566613
1466566612 - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.144242
- Ingest File:
- 02_080.xml