1 / 11

Long Tail Economics

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

lida
Download Presentation

Long Tail Economics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Long Tail Economics Implications of Power Law Distributions

  2. The Long Tail Sales by sales rank: Blue line for Brick and Mortar Retailers; Red Line, Internet Retailers

  3. Long Tails and Power Laws • S = aRk • 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

  4. Traditional retailer’s products account for only 10% of Online retailer’s inventory, 75% of revenues, 66% of profit

  5. 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

  6. 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

  7. 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

  8. Infinite Variety? About 30,000 items WalMart ≈ 5,000 500,000 items

  9. Power Law sales distributions display “Self-similarity at multiple scales” If S = f(R) = aRk , then f(cR) = a(cR)k = ck(aRk) = ckf(R), where c is a constant.

  10. 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

  11. References • Anderson, Chris. 2006. The Long Tail. Hyperion: New York. • Bentley, R. Alexander, Carl P. Lipo, Harold A. Herzog, and Matthew W. Hahn. 2007. “Regular Rates of Popular Culture Change Reflect Random Copying.” Evolution and Human Behavior, 28, 5-158.

More Related