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Similar a Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction?
Similar a Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction? (20)
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Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction?
- 1. Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction? September 2, 2009, Linz, Austria Martin Hepp http://www.unibw.de/ebusiness/
- 2. Part I: Diversity in Markets The specificity of exchanged goods has kept on growing...
- 3. Specificity How much you loose when you can‘t use a good for what it was designed. Martin Hepp, 3 mhepp@computer.org
- 4. Growth in Specificity Reason # 1: Division of Labor Martin Hepp, 4 mhepp@computer.org
- 5. Range of Production on the Level of the Overall Economy Parts = N * c x Similarity of components weakens the effect. N = Number of Commodities c = Number of Components per Level of Division of Labor x = Depth of the Division of Labor Martin Hepp, 5 mhepp@computer.org
- 6. Growth in Specificity Reason # 2: Technical Advancement and Innovation Martin Hepp, 6 mhepp@computer.org
- 7. 1920: 5168 Types of Goods Martin Hepp, 7 mhepp@computer.org
- 8. Growth in Specificity Reason # 3: Logistics Temporal Constraints etc. Martin Hepp, 8 mhepp@computer.org
- 9. Growth in Specificity Reason # 4: Wealth Abraham H. Maslow (1908-1970) A Theory of Human Motivation (1943) Martin Hepp, 9 mhepp@computer.org
- 10. Examples Martin Hepp, 10 mhepp@computer.org
- 11. Examples Martin Hepp, 11 mhepp@computer.org
- 12. Examples Martin Hepp, 12 mhepp@computer.org
- 13. Specificity Increases the Search Space Martin Hepp, 13 mhepp@computer.org
- 14. Multi-Dimensional Trade-Off Problems • Product Features • Price • Services • Logistics • Preferences regarding business partners • Etc. Martin Hepp, 14 mhepp@computer.org
- 15. Part II: E-Commerce on the Web
- 16. History Lesson: Search for Suppliers 1992: 1 Week 2009: 1 Minute Martin Hepp, 16 mhepp@computer.org
- 17. But: Search for Suppliers, 2009 Martin Hepp, 17 mhepp@computer.org
- 18. Limitations of the Web, 2009
- 19. No Unified View: Jumping Back and Forth Across Data Silos Site Page Page Search Engine Results Search Engine Results 1 1 2 Search Engine Results Search Engine Results Page Page 3 4 Site Page 2 5 Site Page Page Page 3 6 7 8 Martin Hepp, 19 mhepp@computer.org
- 20. We know the best hits only when done. Site Page Page 1 1 2 Search Engine Results Page Page 3 4 Site Page 2 5 Site Page Page Page 3 6 7 8 Martin Hepp, 20 mhepp@computer.org
- 21. Specificity vs. Keyword-based Search • Synonyms • Homonyms • Multiple languages • No parametric search Martin Hepp, 21 mhepp@computer.org
- 22. Limited Ability to Reuse Data Martin Hepp, 22 mhepp@computer.org
- 23. The Web: A Bottleneck for Sharing Product Data Martin Hepp, 23 mhepp@computer.org
- 24. Challenge: Web-wide Product Search • Find all MP3 players that have a USB interface and a color display, and sort them by weight (lightest first). ...on a Web Scale! Martin Hepp, 24 mhepp@computer.org
- 25. Today: Loss of Variety and Detail Many Different Variety in Products Preferences Web Search Manufacturers & Consumers Retailers Martin Hepp, 25 mhepp@computer.org
- 26. What’s the Consequence? Martin Hepp, 26 mhepp@computer.org
- 27. Effect: Overly Price Competition Only 1 – 2 Product Models Considered Comparison Shopping on the Small Subset Martin Hepp, 27 mhepp@computer.org
- 28. This will change soon. Actually, very soon.
- 29. Deep Comparison Shopping Search Engine Results Site Site Site 3 1 2 Page Page Page 6 5 1 Page Page 7 3 Page 2 Page Page 8 4 Martin Hepp, 29 mhepp@computer.org
- 30. Part III: The Web of Linked Data
- 31. The World Wide Web, Essentially: Turn References in Documents from Road Signs into Roads Click! Martin Hepp, 31 mhepp@computer.org
- 32. The Web of Linked Data, Essentially: 1. Cluster Web links by what they mean 2. Use URIs to indicate the type of links 3. Use HTTP URIs so that it is quick and easy to explore what this URI means. 4. Make clear whether you are referring to something or its representation. Martin Hepp, 32 mhepp@computer.org
- 33. The Web of Linked Data, Essentially: 1. Cluster Web links by what they mean 2. Use URIs to indicate the type of links 3. Use HTTP URIs so that it is quick and easy to explore what this URI means. 4. Make clear whether you are referring to something or its representation. Martin Hepp, 33 mhepp@computer.org
- 34. The Web of Linked Data, Essentially: 1. Cluster Web links by what they mean 2. Use URIs to indicate the type of links 3. Use HTTP URIs so that it is quick and easy to explore what this URI means. 4. Make clear whether you are referring to something or its representation. Martin Hepp, 34 mhepp@computer.org
- 35. Technical Effects & Working Assumption • This will reduce the computational complexity of processing, combining, reusing data on a Web scale Martin Hepp, 35 mhepp@computer.org
- 36. Core Web of Linked Data Technology Pillars • URIs for everything • RDF: A data model for exchanging conceptual graphs based on triples – Triple: (Subject, Predicate, Object) – Exchange syntax: RDF/XML, N3, etc. • RDFS and OWL: Formal languages for that help reduce ambiguity and codify implicit facts – foo:human rdfs:subClassOf foo:mammal • SPARQL: Standardized query language and endpoint interface for RDF data • LOD Principles: Best practices for keeping the current Web and the Web of Data compatible Martin Hepp, mhepp@computer.org 36
- 37. Part IV: E-Commerce on the Web of Linked Data
- 38. E-Commerce on the Web of Linked Data Martin Hepp, 38 mhepp@computer.org
- 39. Discovery Effort Martin Hepp, 39 mhepp@computer.org
- 40. Both Sides Can Help Build a Bridge Martin Hepp, 40 mhepp@computer.org
- 41. What Do We Need? • Vocabularies • Tools – Product or service • Applications types – Businesses – Offerings • Data Sets – Product model data – Businesses, contact details, opening hours – Offering data Martin Hepp, 41 mhepp@computer.org
- 42. Part V: The GoodRelations Vocabulary and Data Space
- 43. GoodRelations: A Unified View on Commerce Data on the Web Extraction Arbitrary Query and Reuse Manufacturers Retailers Payment Delivery Product Model Warranty Master Data Shop Spare Parts & Offerings Auctions Consumables Martin Hepp, 43 mhepp@computer.org
- 44. On the Shoulders of Giants A Unified View of Commerce Data on the Web Martin Hepp, 44 mhepp@computer.org
- 45. The GoodRelations Vocabulary • A universal and free Web vocabulary for adding product and offering data to your Web pages. • Compatible with all relevant W3C standards and recommendations – RDF – OWL http://purl.org/goodrelations/ Martin Hepp, 45 mhepp@computer.org
- 46. GoodRelations Design Principles • Keep simple things Lightweight Heavyweight simple and make Web of Data Web of Data complex things possible LOD OWL DL • Cater for LOD and OWL RDF + a little bit DL worlds • Academically sound • Industry-strength engineering • Practically relevant Martin Hepp, 46 mhepp@computer.org
- 47. Albert Einstein on Schema Design "Make everything as simple as possible, but not simpler.“ Albert Einstein Martin Hepp, 47 mhepp@computer.org
- 48. Basic Structure of Offers Object or Agent 1 Promise Happening Compensation Transfer of Rights Agent 2 Martin Hepp, 48 mhepp@computer.org
- 49. Data, Standards, Ontologies Martin Hepp, 49 mhepp@computer.org
- 50. GoodRelations: License • Permanent, royalty-free access for commercial and non-commercial use. http://purl.org/goodrelations/ Martin Hepp, 50 mhepp@computer.org
- 51. Domain Structure and Use Cases
- 52. The Minimal Scenario • Scope – Business entity – Points-of-sale – Opening hours – Payment options • Suitable for – Every business – E-commerce and brick-and-mortar Martin Hepp, 52 mhepp@computer.org
- 53. The Simple Scenario • Scope: Minimal scenario plus – Range of products or services – Business functions – Eligible regions or customer types – Delivery options • Suitable for – Any business: E-Commerce and brick-and-mortar – Specific products or services Martin Hepp, 53 mhepp@computer.org
- 54. GoodRelations Annotator http://www.ebusiness-unibw.org/tools/goodrelations-annotator/ Martin Hepp, 54 mhepp@computer.org
- 55. The Comprehensive Scenario • Scope: Simple scenario plus – Individual products or services – Product features – Pricing, rebates, etc. – Availability • Suitable for – Any business: E-commerce and brick-and-mortar – Specific products or services – Structured product database Martin Hepp, 55 mhepp@computer.org
- 56. osCommerce Extension http://code.google.com/p/goodrelations-for-oscommerce/ Martin Hepp, 56 mhepp@computer.org
- 57. Joomla/VirtueMart Extension http://code.google.com/p/goodrelations-for-joomla/ Martin Hepp, 57 mhepp@computer.org
- 58. Google Product Feed Converter http://tr.im/sLcX Martin Hepp, 58 mhepp@computer.org
- 59. Product Model Data Scenario • Scope – Individual product models – Quantitative and qualitative features • Suitable for – Manufacturers of commodities Martin Hepp, 59 mhepp@computer.org
- 60. Others Do Care: Pick-up in Industry • BestBuy • Smart Information Systems • ebSemantics • Yahoo! SearchMonkey • Virtuoso Sponger Cartridges for Amazon, eBay, and • Major German mail order companies • etc. Martin Hepp, 60 mhepp@computer.org
- 61. Yahoo Enhanced by SearchMonkey Martin Hepp, 61 mhepp@computer.org
- 62. Yahoo Enhanced SearchMonkey Martin Hepp, 62 mhepp@computer.org
- 63. Linked Open Commerce Dataspace http://loc.openlinksw.com/sparql Martin Hepp, 63 mhepp@computer.org
- 64. Linked Open Commerce Dataspace http://loc.openlinksw.com/sparql Martin Hepp, 64 mhepp@computer.org
- 65. Conclusion
- 66. Today: Loss of Variety and Detail Many Different Variety in Products Preferences Web Search Manufacturers & Consumers Retailers Martin Hepp, 66 mhepp@computer.org
- 67. 2010: Point-to-Point Commerce Many Different Variety in Products Preferences Manufacturers & Consumers Retailers Martin Hepp, 67 mhepp@computer.org
- 68. Why Should I Bother? • Web Shops: Better visibility in latest generation search engines (e.g. Yahoo) – Same holds for any business that has a Web page, from A as in Amusement Park to Z as in Zoo. • Manufacturers: Allow your retailers to reuse product feature data with minimal overhead at both ends. • Software Developers: Help your customers to use and generate Semantic Web data. It’s easy! Martin Hepp, 68 mhepp@computer.org
- 69. What Should I Do? • Web Shops: Create a GoodRelations data dump of your range of offers (rather simple) • Vendors of Web Shop Software: Create GoodRelations import and export interfaces (we can help you with that) • Every Business: Ask your webmaster to create at least a basic description of your range of products or services • Entrepreneurs: Invent new business models based on GoodRelations data Martin Hepp, 69 mhepp@computer.org
- 70. Part VII: The Sky Is the Limit Semantics in Affiliate Models, Serendipity, Matchmaking
- 71. Thank you! http://purl.org/goodrelations/ Prof. Dr. Martin Hepp Chair of General Management and E-Business Universitaet der Bundeswehr University Muenchen Werner-Heisenberg-Weg 39 D-85579 Neubiberg, Germany Phone: +49 89 6004-4217 Fax: +49 89 6004-4620 http://www.unibw.de/ebusiness/ http://purl.org/goodrelations/ mhepp@computer.org Martin Hepp, 71 mhepp@computer.org
- 72. Bonus Track: Tools and Resources
- 73. Additional Information • Web Page – Ontology – Language Reference – Primer – Recipes – Wiki http://purl.org/goodrelations/ Martin Hepp, 73 mhepp@computer.org
- 74. GoodRelations User‘s Guide („Primer“) http://www.heppnetz.de/projects/goodrelations/primer/ 74
- 75. GoodRelations Cookbook: Recipes & Examples http://www.ebusiness-unibw.org/wiki/GoodRelations#Recipes_and_Examples Martin Hepp, 75 mhepp@computer.org
- 76. GoodRelations Annotator http://www.ebusiness-unibw.org/tools/goodrelations-annotator/ Martin Hepp, 76 mhepp@computer.org
- 77. GoodRelations Validator http://www.ebusiness-unibw.org/tools/goodrelations-validator/ Martin Hepp, 77 mhepp@computer.org
- 78. RDF2dataRSS Tool http://www.ebusiness-unibw.org/tools/rdf2datarss/ Martin Hepp, 78 mhepp@computer.org
- 79. osCommerce Extension http://code.google.com/p/goodrelations-for-oscommerce/ Martin Hepp, 79 mhepp@computer.org
- 80. Joomla/VirtueMart Extension http://code.google.com/p/goodrelations-for-joomla/ Martin Hepp, 80 mhepp@computer.org
- 81. Thank you! http://purl.org/goodrelations/ Prof. Dr. Martin Hepp Chair of General Management and E-Business Universitaet der Bundeswehr University Muenchen Werner-Heisenberg-Weg 39 D-85579 Neubiberg, Germany Phone: +49 89 6004-4217 Fax: +49 89 6004-4620 http://www.unibw.de/ebusiness/ http://purl.org/goodrelations/ mhepp@computer.org Martin Hepp, 81 mhepp@computer.org