Mining Everyone's Business


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An overview of customer data collection for better marketing.

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  • add reflection questions throughout, bring up corporate values. do we as a company want to do this?\n\ndata collection is going to happen, it’s how you act on that data that defines you, are you extracting more money from the consumer or actually improving their experience.\n\n
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  • data sharing habits\ndata gatherings habits\nget smart\n
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  • introduce the joke\n
  • please rob me looks like the title, move it elsewhere\n\n
  • add minority report footage\n
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  • “integration is too generous a term” \n\nthe stuff that they’re integrating is inconsequential, pale reflection of what we can do.\n\n
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  • add company names\n
  • set the background to some slide to a google maps overview of the hotel we’re presenting at\n\n
  • set the background to some slide to a google maps overview of the hotel we’re presenting at\n\n\n\n\nadd possible good bad ugly framework about who does what with data\n
  • set the background to some slide to a google maps overview of the hotel we’re presenting at\n\n
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  • move this somewhere else\n
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  • generic retail location\nsupply chain and partners behind the scenes\n\n
  • Fast food and soda companies being the new tobacco companies, signs that if you don’t do stuff for your customer’s well being, you’re going to get regulated\n
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  • move up to privacy discussion section as the questions we need to have at the privacy juncture\n
  • copy this to the end of the deck as the key takeaways\n\n
  • here are the questions we need to answer\n
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  • Mining Everyone's Business

    1. 1. Prepared and presented for nGenera Insight:Mining Everyone’s BusinessCustomer Data Integration in a Rich-Data EcosystemJeff DeChambeauJuly 27, 2010
    2. 2. We’ve done a great job integrating technology into many facets of consumption (and life). By going about their lives, consumers disclose their activities and interests. The presence of technology (and data) in our lives is only going to 2
    3. 3. Privacy advocate utopia VRM enthusiaststime “TMI” crew Data collection utopia 3
    4. 4. The Johari window Known to self Not known to self Known to others Arena Blind Spot Not known to others Facade 4
    5. 5. Agenda Customer data-sharing habits Enterprise data gathering Get smart about data creation and 5
    6. 6. Where does data ownership reside? 6
    7. 7. Part I: Customer data-sharing 7
    8. 8. Legacy consumer experience data collection: Source: PBF Comics Probably not optimal. 8
    9. 9. “TMI” 9
    10. 10. Hyper-sharers will be around no matter the privacy climate.Services like twitter, buzz, facebook, and foursquare are designed to entice users to share and over-share. If you want a speci c type of data, try making it easy for people to share it. 10
    11. 11. Part II: Enterprise data 11
    12. 12. Traditional data source types: publicly available, volunteered,gleaned/mined, uniquely identifying 12
    13. 13. Historically... 13
    14. 14. How much data does the enterprise need? 14
    15. 15. Ye Olde Privacy PolicyApple and our partners and licensees may collect, use, and share precise location data, including the real-time geographic location ofyour Apple computer or device. This location data is collected anonymously in a form that does not personally identify you and isused by Apple and our partners and licensees to provide and improve location-based products and services. -Apple“Nonaffiliated third parties are those not part of the family of companies controlled by Citigroup Inc. and/or Macys, Inc. We maydisclose personal information about you to nonaffiliated third parties.” -Macy’s Credit Card“We collect your information from the following sources: • Information you give us, such as during transactions, customer service, surveys, and online registrations. • Information from other sources, such as consumer reporting agencies, and • Information automatically collected when you visit our websites, such as via cookies, and in stores, e.g. via video cameras.” - Wal-Mart“We collect it automatically when you visit our Web sites or use our products and services.” -AT&T 15
    16. 16. Consider mobility: Rich, unique, personal, up-to-date data 16
    17. 17. I’m cash-poor but data-rich! 17
    18. 18. “Public” “Private” 18
    19. 19. What would it take to stop this progression? 19
    20. 20. 20
    21. 21. Part III: Get smart about data collection & 21
    22. 22. How do we get smart? Put on your data-goggles. Create data-rich customer experiences. Capture multiple types of data 22
    23. 23. Movie theater Facial recognition Punctuality assessment Social network analysis Brand preferences Emotional responses Post-event reviews Repeat visit 23
    24. 24. Grocery store Facial recognition Purchase historyHabit detection/prediction Recipe suggestions Suggested up-sells Emotion detection VCA path tracking 24
    25. 25. Best practices/words of warning It’s easier to back up than to catch up. Use data to make better experiences for your customers, not just to make more money. If you’re using customer data to improve the customer experience, chances are good that people will allow 25
    26. 26. Key takeaways There exists tremendous opportunity to use data to segment customers and understand their behaviours. This is accepted or ignored by customers, who abide by privacy policies that allow for data collection and sharing. It’s happening, it’s going to keep happening, and your competitors are probably looking into it—if not already 26
    27. 27. Questions How much sway could public policy have? If we can, do we increase sales at the expense of customer well-being? Like with everything, there will be a black market. How will we respond? What rights do consumers have over “their” data? If there is a line that the enterprise doesn’t cross, where is it? 27
    28. 28. Jeff DeChambeau