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Using Big Data to Quantify Loyalty - 'Do you come here often?'


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Barnes & Noble presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012

Presentation title: Using Big Data to Quantify Loyalty - 'Do you come here often?', by Rafael Mejia

Customer loyalty traditionally has been measured by running surveys to determine the customer’s 'willingness to recommend', satisfaction, etc. Now, with the ability to analyze vast amounts of sales data, online behavior, and reading patterns, Barnes & Noble can measure shifts in customer loyalty at individual stores, regions, or channels. Methods that have long been available for measuring online behavior are now being applied to their brick-and-mortar stores, for a comprehensive view of customer purchase patterns, enabling Barnes & Noble to improve services that better address an individual customer’s needs.

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Using Big Data to Quantify Loyalty - 'Do you come here often?'

  1. 1. Democratizing AnalyticsLessons Learned at Barnes & Noble
  2. 2. Company Overview • Established in 1873 • Nearly 700 retail locations, hosting nearly 100,000 community events every year • Yearly sales of 300 million copies of 1 million unique titles • Extremely dynamic sales environment, Bestsellers account for less than 5% of sales12/18/2012© 2012 Barnes & Noble, Inc. 3
  3. 3. NOOK® • B&N introduced NOOK in 2009, now represents 27% of all eBook sales • Business has grown to include apps, magazines, movies and TV shows12/18/2012© 2012 Barnes & Noble, Inc. 4
  4. 4. Background • Aster customer since 2010 • Aster is our enterprise data warehouse • Our implementation contains over 100TB of data and is growing by ~6TB per month • Recent adoptee of Tableau Reporting Software12/18/2012© 2012 Barnes & Noble, Inc. 5
  5. 5. Data Culture • Top-down mandate to eliminate information silos • ETL group “loads first, asks questions later” • Users have access to as much data as we can provide12/18/2012© 2012 Barnes & Noble, Inc. 6
  6. 6. Analysts • Some subject matter expertise • Comfortable with spreadsheets and SQL • Fully immersed in the specific challenges and priorities of their department • Readily available12/18/2012© 2012 Barnes & Noble, Inc. 7
  7. 7. Data Scientists • Experts in math, statistics, data engineering, pattern recognition and learning, modeling, etc, etc. • Expensive, hard to find and often hard to integrate into non- technical teams12/18/2012© 2012 Barnes & Noble, Inc. 8
  8. 8. Business Leaders • Significant subject matter expertise • Limited technical expertise • Responsible for departmental outcomes • Swamped12/18/2012© 2012 Barnes & Noble, Inc. 9
  9. 9. Citizens Analysts Data Scientists Business Leaders12/18/2012© 2012 Barnes & Noble, Inc. 10
  10. 10. Lesson 1 Analytics have to keep pace with the organization if they have any hope of adding value to the organization12/18/2012© 2012 Barnes & Noble, Inc. 11
  11. 11. Lesson 2 There is a lot to be gained in allowing business users access to data systems before they are ‘perfect’12/18/2012© 2012 Barnes & Noble, Inc. 12
  12. 12. Lesson 3 The best tools encourage collaboration12/18/2012© 2012 Barnes & Noble, Inc. 13
  13. 13. Questions or Comments? Rafael Mejia rmejia@book.com12/18/2012© 2012 Barnes & Noble, Inc. 14