Com300 Ecommerce

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My presentation for Com 300 on the topic of E-Commerce - more specifically, on website personalization. Businesses use techniques such as online analytical processing, data mining, and statistical tools to gather information about each consumer. Is this right?

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Com300 Ecommerce

  1. 1. The Personalization Equation How the E-Commerce industry is using your information productusp.com
  2. 2. Important Business Questions 1. How efficient is our web site in delivering information? 2. How do the users perceive the structure of the web site? 3. Can we predict the user's next visit? 4. Can we make our site meet user needs? 5. Can we increase user satisfaction? superstock.com 6. Can we target specific groups of users and personalize web content for them?
  3. 3. Hall, C. (2001, April). THE Personalization = equation =. (Cover story). Software Magazine, 21(2), 26. ibm.com
  4. 4. “If I have 3 million customers on the Web, I should have 3 million stores on the web” - Jeff Bezos, CEO of Amazon.com
  5. 5. quot;Getting Personalquot; with Your Best Customers Our Relationship Management solutions personalize the entire online shopping experience, allowing retailers to and to present assortments, content, offers that reflect their tastes and preferences, and relevant related items for and opportunities.
  6. 6. Analysis and Segmentation Techniques  Online Analytical Processing (OLAP): performs complex queries on the customer information store.  Data Mining: applies pattern- matching, classification, and prediction algorithms to segment customers into categories.  Statistical Tools: used to perform complex mathematical operations on data sets. thomascheah.com
  7. 7. Analysis and Segmentation Techniques  ClickstreamData: provides a detailed activity path that is generated when a user interacts with a website.  Recommendation Systems  Content-based Filtering: tracks the user's behavior and recommends similar items to those liked in the past.  Collaborative Filtering: based on other users' ratings with similar preferences.  Rule-based Filtering: asks the user questions and provides services tailored to his/her needs. superstock.com
  8. 8. Customer Response to Personalization  57% of consumers would trade demographic information for personalized content.  2006 eMarketer study  77% of customers say they find product recommendations somewhat to extremely useful.  Forrester survey • 59% of online shoppers would return to buy again if presented with special offers based on previous purchases. •DoubleClickPerformics survey ana.net heatedmousepad.info
  9. 9. Privacy Concerns? Dr. Amanda Reeve didn't know about data-miner Choicepoint, but they know all about her... and you! http://www.youtube.com/watch?v=VrlO8WtZ- 1Y&feature=channel getentrepreneurial.com
  10. 10. Discussion  Have you ever noticed a website tailoring their site to you? Do you find this useful or disturbing?  Do you believe that website personalization brings up privacy concerns?  What do you see as the future of website personalization? corbis.com

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