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Mining everyone's business: Customer data integration in a rich-data ecosystem
 

Mining everyone's business: Customer data integration in a rich-data ecosystem

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    Mining everyone's business: Customer data integration in a rich-data ecosystem Mining everyone's business: Customer data integration in a rich-data ecosystem Presentation Transcript

    • Mining Everyone’s BusinessCustomer Data Integration in a Rich-Data EcosystemJeff DeChambeauJuly 27, 2010
    • 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 increase.Copyright 2010 Moxie Insight. All rights reserved. 2
    • Privacy advocate utopia VRM enthusiaststime “TMI” crew Data collection utopiaCopyright 2010 Moxie Insight. All rights reserved. 3
    • The Johari window Known to self Not known to self Known to others Arena Blind Spot Not known to others Facade UnknownCopyright 2010 Moxie Insight. All rights reserved. 4
    • Agenda Customer data-sharing habits Enterprise data gathering Get smart about data creation and collectionCopyright 2010 Moxie Insight. All rights reserved. 5
    • Where does data ownership reside?Copyright 2010 Moxie Insight. All rights reserved. 6
    • Part I: Customer data-sharing habitsCopyright 2010 Moxie Insight. All rights reserved. 7
    • Legacy consumer experience data collection: Source: PBF Comics Probably not optimal. 8
    • “TMI” crewCopyright 2010 Moxie Insight. All rights reserved. 9
    • 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 specific type of data, try making it easy for people to share it. 10
    • Part II: Enterprise data gatheringCopyright 2010 Moxie Insight. All rights reserved. 11
    • Traditional data source types: publicly available, volunteered,gleaned/mined, uniquely identifying 12
    • Historically... 13
    • How much data does the enterprise need?Copyright 2010 Moxie Insight. All rights reserved. 14
    • Ye Olde Privacy PolicyApple and our partners and licensees may collect, use, and share precise location data, including the real-timegeographic location of your Apple computer or device. This location data is collected anonymously in a form thatdoes not personally identify you and is used by Apple and our partners and licensees to provide and improvelocation-based products and services. -Apple“Nonaffiliated third parties are those not part of the family of companies controlled by Citigroup Inc. and/orMacys, Inc. We may disclose 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
    • Consider mobility: Rich, unique, personal, up-to-date data sources.Copyright 2010 Moxie Insight. All rights reserved. 16
    • I’m cash-poor but data-rich!Copyright 2010 Moxie Insight. All rights reserved. 17
    • “Public” “Private”Copyright 2010 Moxie Insight. All rights reserved. 18
    • What would it take to stop this progression?Copyright 2010 Moxie Insight. All rights reserved. 19
    • 20
    • Part III: Get smart about data collection & creationCopyright 2010 Moxie Insight. All rights reserved. 21
    • How do we get smart? Put on your data-goggles. Create data-rich customer experiences. Capture multiple types of data simultaneously.Copyright 2010 Moxie Insight. All rights reserved. 22
    • Movie theater Facial recognition Punctuality assessment Social network analysis Brand preferences Emotional responses Post-event reviews Repeat visit incentivesCopyright 2010 Moxie Insight. All rights reserved. 23
    • Grocery store Facial recognition Purchase historyHabit detection/prediction Recipe suggestions Suggested up-sells Emotion detection VCA path tracking 24
    • 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 it.Copyright 2010 Moxie Insight. All rights reserved. 25
    • Key takeaways There exists tremendous opportunity to use data to segment customers and understand their behaviors. 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 users.Copyright 2010 Moxie Insight. All rights reserved. 26
    • 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?Copyright 2010 Moxie Insight. All rights reserved. 27
    • Jeff DeChambeaujeffd@moxieinsight.com 416.836.8880