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Pop-up commerce


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Imagine a commerce world where thematic and seasonal stores could automatically pop up and then disappear with minimal editorial work. Here we talk about the underlying platform that enables mining large-scale user behavior and query data to set up stores automatically based on themes of interest, and emerging and buzz-creating topics. We will describe the science and tools to build experiences that would drive commerce through custom experience and social media, and help sellers, shoppers, and the enthusiasts.

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Pop-up commerce

  1. 1. Up
  2. 2. eBay Showhouse
  3. 3. • 4-6 TB of User Session Data Collected Per Day• 150+ million sessions• 10+K event types• Hundreds of millions of user guids
  4. 4. Miami Phoenix Tampa Miami DFW(Colts/Bears) (Giants/Patriots) (Steelers/Cardinals) (Saints/Colts) (Packers/Steelers)
  5. 5. Paris Hilton wiiTemporal Pattern in Dotted line and Optimal State Sequence in Solid line
  6. 6.
  7. 7. Multi-year Query Burst Bursty QueriesVolume Time-series Detection Index the queries for periodicity searchPeriodically Bursting Queries Non-periodic , one-off buzz events royalSuperbowl Hannukah wedding justin bieber hair Cluster co-occurring Bursty queries Auto-detected events Cleaning and based on other dimensions labeling
  8. 8. Valentine Wreath Back to schoolPrimitive Valentines Girls backpackValentine Cards Valentines Day Back To School alice costume boutique halloween handmade costume teen halloween costumes mummy costume bat costume viking costume alice in wonderland costumes rainbow brite costume handmade costume pikachu costume ghost costume dora costume couples costume pocahontas costume mens halloween costume jim shore halloween angel costume gorilla costume zorro costume couples halloween costumes bear costume referee costume devil costume jester costume mens pirate costume egyptian costume tinker bell costume leg avenue costume saloon girl costume longaberger halloween werewolf costume funny costume elmo costume wizard of oz costume homemade costume couples costumes red riding hood costume halloween animated halloween costumes women gangster costume pig costume frankenstein costume Halloween
  9. 9. Products/Products/Categ Volume/Revenu eCategoriesories Sellers Buyers
  10. 10. Buyers outnumber sellers 5:1Seller-items sold has a power law distributionSeller-revenue has a power law distributionBuyer-items bought has a power law distribution For a sample period over 1 month mean is 3 and median is 1Buyer-spent money has a power law distribution For a sample period of 1 month mean is 98$ and median was 45$Categories browsed - mean 10.5, median 5~10M new items a day, most items eventually sell, items last from a day to 30 days, most items notcataloged, some auction-some fixed price