1. Personalization in E-commerce Applications
Presented by Ingrid Liao
2018/11/23
Personalization in E-commerce Applications

2. Personalization in E-commerce Applications
Topics
E-commerce (EC)
Adaptation
Frameworks for EC website development
Trends in e-commerce applications
Reminder
2018/11/23
Personalization in E-commerce Applications

3. Personalization in E-commerce Applications
E-commerce (EC)
2018/11/23
Personalization in E-commerce Applications

4. E-commerce (EC): Introduction
Definition: the conducting of business communication and transactions over networks and through computers
Buying and selling of goods and services
All aspects of business interaction, two levels:
Business to Business e-commerce (B2B)
Business to Consumer e-commerce (B2C)
( Source: Glossary of IT & Internet Terms)
2018/11/23
Personalization in E-commerce Applications

5. E-commerce (EC): Advantages
Geographical and time zone distance are no longer important
Presentation of products and services in a web-based catalog is an effective way to publish information at low costs
2018/11/23
Personalization in E-commerce Applications

6. E-commerce (EC): Problems & Solutions
Lack of face to face dialog
Good EC product candidates: software, music, book, high-tech products
Good EC service candidates: information, booking, shipping services
Problematic candidates: dress, insurance
One size fits all catalog
Personalization
Allowing individuals to customize website appearance and functionality
2018/11/23
Personalization in E-commerce Applications

7. Personalization in E-commerce Applications
Adaptation
2018/11/23
Personalization in E-commerce Applications

8. Adaptable versus Adaptive
Adaptation decided by user
Lower-level feature
Adaptive
Adaptation performed by system in an automated way
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Personalization in E-commerce Applications

9. Factors for Adaptivity
User
Device
Context of use
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Personalization in E-commerce Applications

10. Personalization in E-commerce Applications
User Characteristics
User characteristics
Knowledge & skills
Interests & preferences
Needs about disability
Goals
B2C e-commerce
Complex products/services
Category or properties
Accessible services
Application domain
2018/11/23
Personalization in E-commerce Applications

11. Personalization in E-commerce Applications
Type of Devices
Environment data
PC, laptop, mobile phone, PDA, on-board device, …
Different characters
Screen size
Computation and memory capabilities
I/O mechanism
Connection speed, bandwidth …
2018/11/23
Personalization in E-commerce Applications

12. Personalization in E-commerce Applications
Context of Use
Broad
Physical context
User location (most popular context feature)
Environment conditions
Social Context
Social community or group
Task being performed
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Personalization in E-commerce Applications

13. Personalization in E-commerce Applications
What is Adapted?
Suggestion of product/service (content recommendation)
Recommender
Tailored to user/device/context characteristics
Configuration guide
Presentation of product/service
Media, presentation styles
User interface (structure)
Layout e.g. information & navigation structure
Adaptation features
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Personalization in E-commerce Applications

14. More HCI, Less Adaptation
Accessibility
3D, virtual reality UI
Usability
Guidelines e.g. Serco
Users w/ special needs
Emotional buying style
Being usable is the 1st step for being successful
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Personalization in E-commerce Applications

15. Frameworks for EC website development
2018/11/23
Personalization in E-commerce Applications

16. Personalization in E-commerce Applications
Merchant Systems
Facilitate creation and management of electronic catalogs
Support transactional, secure services and integration with legacy software
Only basic personalization features, e.g. product recommendation
Personalization strategies, e.g. BroadVision
Push: recommend information and access
Pull: handle user request in a personalized way
Quantifier matching
“Quantifier matching”, a filtering strategy, allowing companies to target content delivery, access to applications by using quantifies that match appropriate content and capabilities
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Personalization in E-commerce Applications

17. Personalized Product Recommendation
Enhance recommendation capabilities
Interactive: user search according to own selection criteria, e.g. dynamic taxonomies
Inference: based on user behavior
Recommendation techniques
Collaborative filtering: analyzing similarities in different people’s purchase history, e.g. Amazon
Content-based filtering: analyzing product properties similar to individual’s past purchase
Taking indirect users into account
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Personalization in E-commerce Applications

18. Collaborative versus Content-based filtering
Pros
Items as elementary entities
Cons
“Bootstrapping” problems: minimum number of ranking
Sparse user-rank matrix
Content-based
Pros
Successfully recommend new items
Cons
Information must be available
User behavior monitor
Similar items
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Personalization in E-commerce Applications

19. How to Enhance Customer’s Trust in Recommender
Transparency and explanation
Right amount of information
Negotiation between customer and system
Explanation of recommendation
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Personalization in E-commerce Applications

20. Customer Information Sharing
Increase knowledge about common customers
Points for attention
Respect customer’s privacy preferences
Mutual trust between service providers
Misuse
Competitors
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Personalization in E-commerce Applications

21. Personalized Product Info Presentation
Individual customer’s interests & preferences
Dynamically generated product descriptions in electronic catalogs
How?
Individual user model
Different levels of detail
Information on demand
Customized compare table
Example: SeTA system
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Personalization in E-commerce Applications

22. Personalized Product Presentation Example
For layperson, customers with low receptivity and minimal background in telecommunication products:
a few features are described using simple terminology
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Personalization in E-commerce Applications

23. Personalized Product Presentation Example
Highly receptive user: more detailed and technical descriptions are generated for expert customers
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Personalization in E-commerce Applications

24. Personalized Product Presentation Example
Customized compare table
Enable user to check product similarities and differences important to him/her
Unobtrusively identify user priorities
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Personalization in E-commerce Applications

25. Customer Relationship Management (CRM)
One-to-one interaction
Ultimate goal: profit increase
Individual and personalized interaction
Customer satisfaction
Long-term relationship with customers
Increase customer loyalty
Accurate user model
Supplement the lack of direct and personal contact with a human being
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Personalization in E-commerce Applications

26. Personalization in E-commerce Applications
Mass Customization
Production of product/services tailored to specific customer needs, maintaining mass production efficiency and costs
Past: off-the-shelf goods
Good
Enhance relationship between customer & vendor
Limitation
Costly and require expertise knowledge in configuration from scratch
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Personalization in E-commerce Applications

27. Mass Customization Example: Footwear
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Personalization in E-commerce Applications

28. Trends in e-commerce applications
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Personalization in E-commerce Applications

29. Personalization in E-commerce Applications
Ubiquitous Computing
Possibility of accessing a serve anytime, anywhere and exploiting different types of (mobile) devices
Adaptation in particular to context of use and device specific requirements
Context-aware Applications
Example: mobile guides
Ability to integrate different adaptation strategies
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Personalization in E-commerce Applications

30. Personalization in E-commerce Applications
M-commerce
Commercial transactions performed by exploiting wireless devices
Support e-commerce transactions by providing information access and promotion
Information about user’s local context
Timely, relevant, focused services
Physical context
Type of activity
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Personalization in E-commerce Applications

31. M-commerce Services and Applications
(Source: Grami and Schell)
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Personalization in E-commerce Applications

32. Low Acceptance of Mobile Devices
Technical limitation of mobile devices
High cost yet poor quality services
Lack of standards and protocols
Individual’s attitudes
User’s goal …
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Personalization in E-commerce Applications

33. Design Elements of M-commerce Interface
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Personalization in E-commerce Applications
(Source: Lee and Benbasat)

34. M-commerce: Adaptation
Adapting product/service presentation to screen size
Adapting layout of user interface to characteristics of device
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Personalization in E-commerce Applications

35. Personalization in E-commerce Applications
Reminder
2018/11/23
Personalization in E-commerce Applications

36. Personalization in E-commerce Applications
Not a goal, but
Add values to
CRM by supporting long-term relationship
Quality of the offer if tailored to customer needs
Usability if make navigation easier
Back-office integration
2018/11/23
Personalization in E-commerce Applications