112/04/19 Personalization in E-commerce Applications

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Personalization in E-commerce Applications

Presented by Ingrid Liao

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Topics

E-commerce (EC) Adaptation Frameworks for EC website development Trends in e-commerce applications Reminder

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E-commerce (EC)

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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)

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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

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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

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Adaptation

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Adaptable versus Adaptive

Adaptable Adaptation decided by

user Lower-level feature

Adaptive Adaptation performed

by system in an automated way

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Factors for Adaptivity

User Device Context of use

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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

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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 …

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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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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

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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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Frameworks for EC website development

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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

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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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Collaborative versus Content-based filtering

Collaborative 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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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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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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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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Personalized Product Presentation Example

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Personalized Product Presentation Example

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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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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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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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Mass Customization Example: Footwear

http://www.adidas.com/products/miadidas04/content/uk/container.asp

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Trends in e-commerce applications

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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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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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M-commerce Services and Applications

(Source: Grami and Schell)

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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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Design Elements of M-commerce Interface

(Source: Lee and Benbasat)

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M-commerce: Adaptation

Adapting product/service presentation to screen size

Adapting layout of user interface to characteristics of device

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Reminder

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Personalization

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