Introduction to Big data, March 2013
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Prepared by Helene Andre in March 2013 Short presentation about big data explaining what it is and what are its marketing applications. Specific focus on the impact of big data on advertising
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Introduction to Big data, March 2013
- 1. INTRODUCTION TO BIG DATA MARCH 2013
- 2. “Humans now create in two days the same amount of data that it took from the dawn of civilization until 2003 to create” Eric Schmidt, Google‟s Executive Chairman
- 3. Aggregate data Vs. Big data Aggregate data • • What marketers & analysts have used for years Maybe simpler, but you lose context Loss of efficiency & money Big data • • A single platform to track every user interaction More complicated to implement Better understanding of interactions & optimized actions
- 4. A few massive players DATA INFRASTRUCTURE DATA COLLECTION
- 5. A few massive players Data infrastructure Solutions for companies • Data acquisition • Data storage & organization Data analysis
- 6. A few massive players Data collection Solutions for companies • • Data acquisition Consumer behavior analysis Targeted advertising
- 7. 1.06 billion monthly active users 680 million mobile monthly active users 17 billion location-tagged posts, including check-ins The button ‘Like’ has been hit 1.13 trillion times 210,000 years of music have been played $5.1 billion in revenue in 2012 $5.32 in average revenue per user Connections between Facebook members
- 8. Google Search 20 billion pages indexed daily 3,3 billion requests every day (40 000/sec) Android 500 million users on Google’s mobile OS Google Chrome 1st browser worldwide 37% of market share Youtube 800 million users 4 billion hours of video watched monthly 72 hours of video uploaded every minute Gmail 425 million users Google + 250 million members One of Google’s data centers
- 10. Two appealing opportunities Customization More efficient advertising • More & more accurately targeted • In real time
- 11. Two appealing opportunities Customization Tailored services & goods • • Ever narrower segmentation of customers More knowledge on product usage
- 12. Two appealing opportunities Prediction Thanks to iterative models, programs can learn new probabilistic associations over time • • Accurate detection of behaviors, patterns Prediction of future events, trends
- 13. Two appealing opportunities Prediction Applications • • NY Times archives to predict future disease outbreaks, riots & deaths Amazon‟s tools to recommend more purchases or to stop the forgetful ones from buying the same book they purchased five years ago
- 14. What’s next ? DATAVIZ WEARABLE TECH
- 15. What’s next ? Dataviz Data viz To make this amount of data understandable David McCandless
- 16. What’s next ? Wearable tech • • • Google Glass & the „talking shoe‟ project Nike+ FuelBand to track daily activity Oakley Airwave to provide real-time feedback to skiers
- 17. What’s next ? Hyper-rationalism & magical experiences