product variety, consumer preferences, and web technology: can the web of data reduce price...

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/

Part I: Diversity in Markets

The specificity of exchanged

goods has kept on growing...

Specificity

How much you loose when you can‘t

use a good for what it was designed.

3 Martin Hepp,

mhepp@computer.org

Growth in Specificity

Reason # 1: Division of Labor

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Range of Production on the Level of the Overall Economy

Parts = N *cx

5

N = Number of Commodities

c = Number of Components per Level of

Division of Labor

x = Depth of the Division of Labor

Martin Hepp,

mhepp@computer.org

Similarity of components

weakens the effect.

Growth in Specificity

Reason # 2: Technical Advancement

and Innovation

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1920: 5168 Types of Goods

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Growth in Specificity

Reason # 3: Logistics

Temporal Constraints etc.

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Growth in Specificity

Reason # 4: Wealth

Abraham H. Maslow (1908-1970)

A Theory of Human Motivation (1943)

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Examples

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Examples

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Examples

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Specificity Increases the

Search Space

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Multi-Dimensional Trade-Off Problems

• Product Features

• Price

• Services

• Logistics

• Preferences regarding business partners

• Etc.

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mhepp@computer.org

Part II: E-Commerce on the Web

History Lesson: Search for Suppliers

1992: 1 Week 2009: 1 Minute

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But: Search for Suppliers, 2009

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Limitations of the Web, 2009

No Unified View: Jumping Back and Forth

Across Data Silos

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Site

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Searc

h E

ngin

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esults

Searc

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ngin

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esults

Searc

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ngin

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esults

Searc

h E

ng

ine R

esu

lts

Martin Hepp,

mhepp@computer.org

We know the best hits only when done.

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Site

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esults

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Martin Hepp,

mhepp@computer.org

Specificity vs. Keyword-based Search

• Synonyms

• Homonyms

• Multiple languages

• No parametric

search

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Limited Ability to Reuse Data

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The Web: A Bottleneck for Sharing

Product Data

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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!

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mhepp@computer.org

Today: Loss of Variety and Detail

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mhepp@computer.org

Many Different

Products

Variety in

Preferences

Manufacturers &

Retailers Consumers

Web Search

What’s the

Consequence?

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Effect: Overly Price Competition

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Only 1 – 2 Product Models Considered

Comparison Shopping on the Small Subset

This will change soon.

Actually, very soon.

Deep Comparison Shopping

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Site

1

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Search Engine Results

Part III: The Web of Linked Data

The World Wide Web, Essentially:

Turn References in Documents from

Road Signs into Roads

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Click!

Martin Hepp,

mhepp@computer.org

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.

32 Martin Hepp,

mhepp@computer.org

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.

33 Martin Hepp,

mhepp@computer.org

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.

34 Martin Hepp,

mhepp@computer.org

Technical Effects & Working Assumption

• This will reduce the

computational

complexity of

processing,

combining, reusing

data on a Web scale

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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

36 Martin Hepp,

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Part IV: E-Commerce on the Web of

Linked Data

E-Commerce on the Web of Linked Data

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Discovery Effort

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Both Sides Can Help Build a Bridge

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What Do We Need?

• Vocabularies

– Product or service

types

– Businesses

– Offerings

• Data Sets

– Product model data

– Businesses, contact

details, opening hours

– Offering data

• Tools

• Applications

41 Martin Hepp,

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Part V: The GoodRelations

Vocabulary and Data Space

GoodRelations: A Unified View on

Commerce Data on the Web

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Product Model

Master Data Shop

Offerings Auctions Spare Parts &

Consumables

Warranty

Delivery Payment

Retailers Manufacturers

Arbitrary Query

Extraction

and Reuse

Martin Hepp,

mhepp@computer.org

On the Shoulders of Giants

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A Unified View of Commerce Data

on the Web Martin Hepp,

mhepp@computer.org

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/

45 Martin Hepp,

mhepp@computer.org

GoodRelations Design Principles

• Keep simple things

simple and make

complex things possible

• Cater for LOD and OWL

DL worlds

• Academically sound

• Industry-strength

engineering

• Practically relevant

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Lightweight

Web of Data

LOD

RDF + a little bit

Heavyweight

Web of Data

OWL DL

Martin Hepp,

mhepp@computer.org

Albert Einstein on Schema Design

"Make everything as simple as possible, but

not simpler.“

Albert Einstein

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Basic Structure of Offers

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Agent 1 Object or

Happening Promise

Agent 2

Compensation Transfer of

Rights

Martin Hepp,

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Data, Standards, Ontologies

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GoodRelations: License

• Permanent, royalty-free access for commercial and non-commercial use.

http://purl.org/goodrelations/

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Domain Structure and Use Cases

The Minimal Scenario

• Scope

– Business entity

– Points-of-sale

– Opening hours

– Payment options

• Suitable for

– Every business

– E-commerce and

brick-and-mortar

52 Martin Hepp,

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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 53 Martin Hepp,

mhepp@computer.org

GoodRelations Annotator

54

http://www.ebusiness-unibw.org/tools/goodrelations-annotator/

Martin Hepp,

mhepp@computer.org

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

55 Martin Hepp,

mhepp@computer.org

osCommerce Extension

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http://code.google.com/p/goodrelations-for-oscommerce/

Martin Hepp,

mhepp@computer.org

Joomla/VirtueMart Extension

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http://code.google.com/p/goodrelations-for-joomla/

Martin Hepp,

mhepp@computer.org

Google Product Feed Converter

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http://tr.im/sLcX Martin Hepp,

mhepp@computer.org

Product Model Data Scenario

• Scope

– Individual product

models

– Quantitative and

qualitative features

• Suitable for

– Manufacturers of

commodities

59 Martin Hepp,

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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.

60 Martin Hepp,

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Yahoo Enhanced by SearchMonkey

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Yahoo Enhanced SearchMonkey

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Linked Open Commerce Dataspace

http://loc.openlinksw.com/sparql

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Linked Open Commerce Dataspace

http://loc.openlinksw.com/sparql 64 Martin Hepp,

mhepp@computer.org

Conclusion

Today: Loss of Variety and Detail

66 Martin Hepp,

mhepp@computer.org

Many Different

Products

Variety in

Preferences

Manufacturers &

Retailers Consumers

Web Search

2010: Point-to-Point Commerce

67 Martin Hepp,

mhepp@computer.org

Many Different

Products

Variety in

Preferences

Manufacturers &

Retailers Consumers

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!

68 Martin Hepp,

mhepp@computer.org

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

69 Martin Hepp,

mhepp@computer.org

Part VII: The Sky Is the Limit

Semantics in Affiliate Models,

Serendipity, Matchmaking

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

71 Martin Hepp,

mhepp@computer.org

Bonus Track: Tools and Resources

Additional Information

• Web Page – Ontology – Language Reference – Primer – Recipes – Wiki

http://purl.org/goodrelations/

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mhepp@computer.org

GoodRelations User‘s Guide („Primer“)

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http://www.heppnetz.de/projects/goodrelations/primer/

GoodRelations Cookbook:

Recipes & Examples

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http://www.ebusiness-unibw.org/wiki/GoodRelations#Recipes_and_Examples

GoodRelations Annotator

76

http://www.ebusiness-unibw.org/tools/goodrelations-annotator/

Martin Hepp,

mhepp@computer.org

GoodRelations Validator

77

http://www.ebusiness-unibw.org/tools/goodrelations-validator/

Martin Hepp,

mhepp@computer.org

RDF2dataRSS Tool

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http://www.ebusiness-unibw.org/tools/rdf2datarss/

Martin Hepp,

mhepp@computer.org

osCommerce Extension

79

http://code.google.com/p/goodrelations-for-oscommerce/

Martin Hepp,

mhepp@computer.org

Joomla/VirtueMart Extension

80

http://code.google.com/p/goodrelations-for-joomla/

Martin Hepp,

mhepp@computer.org

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

81 Martin Hepp,

mhepp@computer.org