E-Commerce on the basis of current Web technology has created fierce competition with a strong focus on price. Despite a huge variety of offerings and diversity in the individual preferences of consumers, current Web search fosters a very early reduction of the search space to just a few commodity makes and models. As soon as this reduction has taken place, search is reduced to flat price comparison.
This is unfortunate for the manufacturers and vendors, because their individual value proposition for a particular customer may get lost in the course of communication over the Web, and it is unfortunate for the customer, because he/she may not get the most utility for the money based on her/his preference function. A key limitation is that consumers cannot search using a consolidated view on all alternative offers across the Web.
In this talk, I will (1) analyze the technical effects of products and services search on the Web that cause this mismatch between supply and demand, (2) evaluate how the GoodRelations vocabulary and the current Web of Data movement can improve the situation, (3) give a brief hands-on demonstration, and (4) sketch business models for the various market participants.
Similaire à Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction?
Similaire à Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction? (20)
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
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
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
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
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
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
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
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
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
73. Additional Information
• Web Page
– Ontology
– Language Reference
– Primer
– Recipes
– Wiki
http://purl.org/goodrelations/
Martin Hepp, 73
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
