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Big Data and Mobile Commerce - Privacy and Data Protection

  1. BIG DATA & MOBILE COMMERCE What does it mean for Privacy & Data Protection?
  3. Applying NEW technology
  6. Wait … WHAT!? What kind of data!?
  8. Nobody really understood
  9. Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it. “ ” Dan Ariely Professor at Duke University
  10. How Is Big Data?
  11. Byte = 1 grain of rice Kilobyte = 1 cup of rice Megabyte = 8 bags of rice Gigabyte = 3 trailers of rice Terabyte = 2 container ships Petabyte = blankets Manhattan Exabyte = blankets west coast states Zettabyte = fills the Pacific Ocean Yottabyte = AN EARTH SIZED RICE BALL!
  12. There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2. “ ”Eric Schmidt Executive Chairman at Alphabet Inc. Former CEO of Google
  13. 98,000+ tweets 695,000 status updates 11 million instant messages 698,455 Google searches 168+ million emails sent 1,820 TB of data created Every 60 seconds
  14. 90% of all the data in the world was created in the last 2 years
  15. 1 day worth of data burned on DVDs
  16. 4.4 million IT jobs created globally
  17. By 2019, Big Data Technology and Services Market will grow to $48.6 billion
  18. Big Data Characteristics
  19. VOLUME Vast Amounts of Data Zettabytes and Brontobytes
  20. VARIETY Different types of data we can use, both structured and unstructured. Sensors Photos Voice Recordings Social Media Conversations Messages Video
  21. VELOCITY Speed at which new data is generated and at which data moves around.
  22. VALUE Big amounts of data are highly valuable
  23. Capital One - harnessing behavioral data to shape customer offerings. For instance, their deal optimization engine analyzes customer demographics and spending patterns to determine how, where and when to put offers in front of people – leading to more revenue for Capital One and a more positive experience with the brand for customers.
  24. T-Mobile managed to reduce "churn" by 50% just by staying on top of things like usage patterns, geographical usage trends, customer purchases by location and most importantly, Customer Lifetime Value. T- Mobile has banked on the fact that customers with strong social networks can influence others' telecomm decisions, making a point of identifying its most influential customers and giving them perks.
  25. Free People uses millions of customer records (reviewed by an in house analytics team) to shape the next season's offerings. Information like what sold, what didn't, what was returned and more fuels the brand's product recommendations, the look of its website and what kinds of promotions customers see to improve Free People's bottom line.
  26. Starbucks' ability to maintain a surprising number of locations in close proximity to one another is a function of big data. The fact that two Starbucks can exist a block away from one another isn't luck; they were placed in their adjacent locations thanks to location-based data, street traffic analysis, demographic info and data culled from other locations.
  27. Big Data Opportunities
  28. #1 Optimize Business Processes The big objective - creating predictable models. Retailers are able to optimize their stock and delivery routes optimize using data from geographic positioning and RFIDs.
  29. #2 Improving Healthcare We can find new cures and better understand and predict disease patterns or we can use all the data from smart watches and wearable devices to better understand links between lifestyles and diseases.
  30. #3 Improving Cities and Countries Big data can improve many aspects of our cities, such as optimizing traffic flows based on real time traffic information as well as social media and weather data.
  31. The sky is the limit
  33. 1.2 billion people accessing the web from their mobile devices
  34. 15% of all Internet traffic is mobile
  35. 58% of smartphone owners have used it for shopping
  36. 63% of people expect to do more shopping on their mobile devices
  37. Includes all type of transactions Mobile Retailing Mobile Ticketing/Booking Mobile Billing Other mobile services
  38. $79 BN $284 BN 20.60% 45% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00% 45.00% 50.00% 0 50 100 150 200 250 300 2016 2020 Mobile commerce % of e-commerce Mobile Commerce Growth
  39. Top Growing Emerging Markets India Taiwan Malaysia 2012 2014
  40. Go mobile or risk falling behind
  41. Uber - the reason Uber is so “frictionless” is that when you are done with your ride, you just get out of the car. No cash, no credit cards, no signing receipts (or hassles over requesting receipts).
  42. Square - with this small, square plastic device that plugs into any smartphone or tablet, any business can now set up an account to process credit and debit cards and then sweep the proceeds directly into their bank account.
  43. Amazon – its mobile app leverages the best of all that Amazon has done on desktops and laptops for the last 15 years
  44. Future Opportunities
  45. #1 Optimize Mobile Check-out Mobile commerce conversion rates are still low due to shoppers giving up on the process when it becomes too hard to finalize an order.
  46. #2 Create a holistic mobile approach For retailers, the money is in the mobile Web, not the app
  48. Everything you do on your mobile leaves a trail
  49. Goals of using Big Data Understanding consumer behavior Increasing customer loyalty Increase ARPU Decrease churn
  50. The ultimate destination: Increase customer life time value
  51. Providing value to clients Real Time Offers Customer Segmentation
  52. Areas of development Personalized Retail Content Easy Payment Process
  53. You are privileged
  55. 38%of people surveyed said that privacy and protection of data are the main concerns of Big Data in Mobile Commerce
  56. More and more data is collected, often without consent.
  57. The challenge is how to apply analytics for deeper consumer insights, while maintaining the highest levels of security and individual privacy. “ ” Diarmuid Mallon Direct of Global Marketing Solutions at SAP
  58. How secure is your data?
  59. Threats are real! Target Data Breach – 40M credit card info & 70M personal info Korea Credit Bureau – 20M credit card & personal info
  60. Regulations are happening!
  61. Example of EU Framework Data controllers transparency Clear info on Data processing Data protection in 3rd party transfers 24h for data disclosure in case of breach
  62. With great power comes great responsibility.“ ”Ben Parker
  63. Identity authentication Security Strengths
  64. THANK YOU! Kenneth Ho Big Data Enthusiast