Long Tail by Chris Anderson

1. Long Tailby Chris Anderson Hassan Sayyadi sayyadi@s.umd.edu

2. Touching the Void Phenomenon • Touching the Void, a harrowing account of near death in the Peruvian Andes • Joe Simpson, 1988 • Into Thin Air • Jon Krakauer, 1997

3. Touching the Void Phenomenon: How? • Amazon.com recommendations and online booksellers' software • From the pattern in buying behavior • People took the recommendation • More sales • more algorithm-fueled recommendations the positive feedback loop

4. Touching the Void Phenomenon: Why? • Hit-driven economy • Two limitation of physical world • The need to find local audience • The physics itself • But are hits enough for everybody? • Online retails • A world of abundance • Solve the problem of long tail

5. Online Retailer Examples: Music • Rhapsody vs. Walmart • Walmart • Carry a title if it sells at least 100,000 copies • Less than 1 percent of CDs do that kind of volume • Rhapsody • Power low demand • Hits for tracks below top 40,000 even 400,000 tracks

6. Online Retailer Examples: Books and Movies • Amazon vs. Barnes & Noble • Barnes & Noble • Carries 13,000 titles • Amazon • More than half of its sales come from outside its top 13,000 titles • Netflix vs. Blockbuster • Blockbuster: Carries 3,000 DVDs • Netflix: a fifth of Netflix rentals are outside its top 3,000 titles

7. Rules for the new entertainment economy • Rule 1: Make everything available • Don’t look at physical shelves for an item in the long tail • Online retailers can aggregate dispersed audience • Almost anything is worth offering on the off chance it will find a buyer. • The opposite of the way the entertainment industry now thinks.

8. Rules for the new entertainment economy • Rule 2: Cut the price in half. Now lower it • No cost of the retail channel - CD manufacturing, distribution, and retail overheads • When you lower prices, people tend to buy more • Rhapsody experiment: • The service offered tracks at 99, 79, and 49 cents • Although the 49-cent tracks were only half the price of the 99-cent tracks, it sold three times as many of them. • Future Market • On-demand and free to listeners and advertising-supported, like radio

9. Rules for the new entertainment economy • Rule 3: Help me find it • MP3.com • Only long tail • No familiar point of entry for consumers, no known quantity from which further exploring could begin • Need both ends of the curve • How to find • Rhapsody: a combination of human editors and genre guides • Amazon: collaborative filtering • Netflix: 60 percent of rentals come from recommendations

10. Website Morphingby John R. Hauser, Glen L. Urban, Guilherme Liberali, and Michael Braun

11. Website Design

12. Motivation • Intel website redesign • Added a verbal advisor for digital camera drivers.  Successful download increased 27%. • But Intel may increase downloads even more • Different users prefer different characteristics  Automatically change website characteristics for each users

13. Website Design Selection Issues • Solutions • Personalized self-selection • Cognitive-style surveys • Difficulties • Complex, confusing websites which are difficult to use • Too cumbersome and intrusive for retail website visitors

14. Website Morphing • Morphing the website automatically by matching characteristics to costumers’ cognitive style. • Challenges • First-time visitors • Learning best website characteristics for each cognitive-style • Finding prior distributions • Real-time working

15. Website Morphing Model

16. Cognitive-Style Inference Each visitor’s click is a decision point that reveals the visitor’s cognitive style preferences. Posterior distribution

17. Naïve Morph Assignment • For cognitive style r: • a_i = the number of users who bought the plan after assigning morph i • b_i =the number of users who did not buy a plan aftre assigning morph i • Best Morph • The morph i which maximize {a_i / (a_i + b_i)}

18. Optimal Morph Assignment • Exploration VS Exploitation • Reward: Immediate reward+ discounted future reward • Immediate reward • Probability of selling an item times the profit earned by selling the item • Discounted future reward • expected reward of acting optimally in the future discounted by factor a.  Dynamic Programming

19. Optimal Morph Assignment • Reward Function to maximize • G is a decreasing function of n • High uncertainty (small n): Exploration • Low uncertainty (large n): Exploitation • G converges to a/(a+b)

20. Cognitive-Style uncertainty in Optimal Morph Assignment • The Bayesian cognitive-style inference model gives a probability for each cognitive style. • Results in the uncertainty in the optimal morph assignment • Model update by replacing absolute values with expected values:

21. Experiments: Cognitive-Style measures Leader vs. follower Analytic/visual vs. holistic/verbal Impulsive vs. deliberative (Active) reader vs. (passive) listener

22. Experiments: Morph Characteristics Graphical vs. verbal Small-load vs. large-load Focused content vs. general content

23. Estimation of Click-Alternative preferences Clickstream likelihood Pair comparison likelihood Cognitive-style preference posterior

24. Experimental Result

25. Thank you!