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The impact of piracy (and free) on book sales

The impact of piracy (and free) on book sales. A BEA update on the piracy project. This morning …. Project history Why look at this now? Approach and publishing partners Primary findings to date Next steps for this research. Born (Wakefield, Massachusetts ). College, business school.

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The impact of piracy (and free) on book sales

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  1. The impact of piracy (and free) on book sales A BEA update on the piracy project

  2. This morning … • Project history • Why look at this now? • Approach and publishing partners • Primary findings to date • Next steps for this research

  3. Born (Wakefield, Massachusetts) College, business school Time Inc. weekly magazines Catholic school education Finally left Massachusetts Married, kid

  4. “Faster, better, cheaper” More kids Started to consult Hammond Got a logo

  5. Brian: “How about using a co-op marketing model to assess whether it helps or hinders paid sales?” Intrepid NYU grad student starts tracking O’Reilly’s 2008 front list to find pirated content O’Reilly’s editors: “All of our content is pirated as soon as we publish it!” Random House joins the research, contributing several experiments with “free” content distribution MIP 2008: Andrew Savikas and Mac Slocum wonder, “Can we measure the impact of piracy on book sales?” Brian secretly worries that any analysis will not have a “quiet period” against which to measure baseline sales

  6. TOC 2009: Research paper and preliminary results are announced BEA 2009: Piracy and “free” results are updated Still consulting … Piracy research on O’Reilly titles Search for more participants

  7. Why tell you all of this? • You need to know me to trust me • Trust helps you hear what I have to say • Success (to me) = a fighting chance at recruitment and participation

  8. My point of view • IP matters • There are niches, and titles, for which piracy is a direct loss and enforcement makes sense • There are niches, and titles, for which piracy may help spur paid sales • This research is structured to find out which is which

  9. “Perhaps on the rare occasion that pursuing the right course demands an act of piracy, piracy itself can be the right course?” Governor Swann, in “Pirates of the Caribbean” (itself heavily pirated)

  10. “Free” is not “new” … • A long and successful history • Galleys, ARCs, blads, sample chapters • Digital sampling on the rise • … but only a small set of experiments using fully “free” content

  11. Book marketing: growing content discovery and access High Discovery Appearance on Oprah Coop Marketing Amazon Promotion Museum Stores Low Access High Access Over time, increase both discovery and access Catalog & BEA Corporate Web Site Low Discovery

  12. Why look at this topic now?

  13. Our research approach • Collate experiments • Segment attributes • Identify data gaps • Use a consistent data source (POS feeds) • Measure pre- and post-release • Populate a structured matrix • Look at combined results • Initial take on the impact of pirated content • Initial impact of “free” • Share the analysis • Invite discussion • Grow the test sample The research is data-driven, open (without compromising publisher data) and structured to share knowledge.

  14. A hands-on research project • Wil Johnson • Searched P2P sites for O’Reilly titles every day since fall 2008 • Built his own scraper • Running it made his (roommate’s) ISP cut off service • Figured out a way around it! NYU, candidate for M.S. in Publishing, Dec 2009

  15. A value in structured testing … • A robust set of variables • Appropriate segmentation • Captures content characteristics • Can collate like experiments • Can develop and test specific hypotheses and track results over time

  16. Why O’Reilly and Random House?

  17. Primary research findings • P2P “threat” may be overstated • Low incidence • Significant lag • Technical skills are not commonly held • The value of “free” is not binary

  18. Proposing a more nuanced model “White” market “Gray” market “Back channel” • Print sales • DRM-protected digital sales • “Trialware” • Unprotected digital sales • Galleys, ARCs • “Free” promotions • Unauthorized duplication • Pirated content Our current question: what impact does “free” have on sales?

  19. What we tested …

  20. What we found initially …

  21. Some research surprises… • Low volume of P2P incidence • Lag time on P2P seeding • Number and range of “under the radar” free experiments available for analysis • Interest among trade publishers

  22. The piracy research continued … • 13 more 2008 front-list titles • Average post-seed sales down 4.2% in the four weeks after seeds first seen • Ranged from 15.1% up to 48.7% down • Average first seeds appeared 19 weeks after publication date

  23. The number of seeds peaks quickly

  24. The number of leeches peaks immediately and quickly declines

  25. Lag time before seeding varies Average =19weeks

  26. Noodling over the data… The spread in results made us wonder if we had missed something in the bigger sample set.

  27. Where piracy may help … • Looked at sales patterns of pirated and un-pirated content • “Normed” the data to a common start point • Plotted the average sales per week for pirated and un-pirated titles • Uncovered a visual correlation between piracy onset and unit sales Because of different pub dates, the average time on sale for pirated content in this sample is shorter (35 weeks) than that for un-pirated content (47) weeks. Comparisons at the end of the on-sale period are not reliable.

  28. Average sales (weeks after pub date) Average week at which seeded content first seen

  29. Four-week rolling averages Average week at which seeded content first seen

  30. Data in what was not pirated… “Head First books break from the linear tradition, instead using a trajectory filled with successes, failures and lessons… The non-linear format makes them tough to reproduce in a digital form -- they're full of illustrations, thought bubbles, photos, quizzes, etc.”

  31. Since TOC, a new research project • John Hilton, a doctoral candidate at BYU • Used Bookscan data 8 weeks before & after free promotions • Found that Random’s five recent promotions coincided with an average 11% lift in sales • A parallel evaluation of Tor promotions saw sales drop an average of 26%

  32. Three useful cautions • Correlation isn’t causality • Larger data sets may uncover a sample skew • What works today may not work as well at some future date

  33. Next steps • Additional tests are in work now • We continue to monitor P2P activity • More publishers can help fill in the test matrix • Now gathering feedback • Will continue to refine the analysis

  34. For more information • “Rough Cut” research paper out now • Includes this research and future updates • Also provides background on free and P2P • http://tinyurl.com/q3v4b9 • brian.oleary@magellanmediapartners.com

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