LONG TAIL ECONOMICS IMPLICATIONS OF POWER LAW DISTRIBUTIONS

THE LONG TAIL Sales by sales rank: Blue line for Brick and Mortar Retailers; Red Line, Internet Retailers

LONG TAILS AND POWER LAWS S = aR k S is quantity sold R is sales rank of individual titles A log-linear equation: Log S = log(a) + klog(R) Brick and Mortar Retailers Market is limited to local area Inventory is limited by high probability that low ranking items will not sell Internet Retailer Market is national or international in scope Inventory relatively unlimited; even low ranking items likely to sell

TRADITIONAL RETAILER’S PRODUCTS ACCOUNT FOR ONLY 10% OF ONLINE RETAILER’S INVENTORY, 75% OF REVENUES, 66% OF PROFIT

TRADITIONAL VS. ONLINE RETAILING For Traditional Music Retail New album releases account for 63% of sales in 2005 The top 1000 albums make up almost 80% of sales At big-box retailers, top 200 account for 90% of sales For Online Music Retail New music accounts for one-third of sales with two-thirds from older “catalog” items The top 1000 albums account for less than 33% of sales Albums beyond the top 5000 account for 50% of sales

POWER LAW OR LONG TAIL MARKETS Require (Anderson): Variety (differentiated products) Inequality (variations in “quality”) Network effects that amplify differences Notice similarity to superstars Imperfect substitutability among “goods” Some sellers (“performers”) are preferred to others Differentiated products Economies of scale in production (realized online) Costs of production do not rise in proportion to a seller’s market Access to a market of large or increasing scope (due to Internet) Often due to technological change Online Retailing is a Superstar Phenomenon

ONLINE SUPERSTARS As online music markets grow Total number of retailers declines Traditional retail has become limited to Big-box retailers carrying 4,500 albums or less Small local “specialty” retailers often selling “used” music as well as new Online Retailers expand Amazon carries about 500,000 albums (CDs) iTunes, Amazon, Pandora, Spotify can carry almost unlimited digital inventory at near zero marginal cost

INFINITE VARIETY? About 30,000 items 500,000 itemsWalMart ≈ 5,000

POWER LAW SALES DISTRIBUTIONS DISPLAY “SELF-SIMILARITY AT MULTIPLE SCALES” If S = f(R) = aR k, then f(cR) = a(cR) k = c k (aR k ) = c k f(R), where c is a constant.

WHAT MAKES THE LONG TAIL CHANGE? Anderson Increasing market scope (technology) Network effects and filters or search functions Niche titles’ sales increase relative to hits Bentley, et al. Random copying behavior with “u” fraction of “innovators” Produces power law sales distributions Increasing numbers of “innovators” increases top list turnover producing a longer tail

REFERENCES Anderson, Chris The Long Tail. Hyperion: New York. Bentley, R. Alexander, Carl P. Lipo, Harold A. Herzog, and Matthew W. Hahn “Regular Rates of Popular Culture Change Reflect Random Copying.” Evolution and Human Behavior, 28,