Transcript lecture03_Serving_Customer

CS5038 The Electronic Society
Lecture 3: Serving the Customer
Lecture Outline
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Consumer Behaviour
Demographics of Internet Surfers
Major Roles in Purchasing
Purchasing decision-making model
Consumer Satisfaction
One-to-One Marketing
Personalisation
Customer Service
Market Research
Data Mining
Intelligent Agents
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Consumer
Behaviour
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Prentice Hall, 2002
Consumer Behavior Online
Consumer types
 Individual consumers
 Commands most of the media’s attention
 Organizational buyers
 Governments and public organizations
 Private corporations
 Resellers
Purchasing types and experiences
 2 dimensions of shopping experiences
 Utilitarian—to achieve a goal
 Hedonic—because it’s fun
 3 categories of consumers
 Impulsive buyers—purchase quickly
 Patient buyers—make some comparisons first
 Analytical buyers—do substantial research before buying
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Demographics of Internet Surfers
Environmental variables
 Social variables – influenced by peers
 Cultural variables
 Psychological variables
 Other environmental variables - e.g. government restrictions
Personal characteristics / demographics
 Consumer resources and lifestyle
 Age; gender; marital status
 Knowledge and educational level
 Attitudes and values
 Motivation
 Personality
 Ethnicity
More experience on Web  more to buy online
Two major reasons people do not buy online
 Security
 Difficulty judging the quality of the product
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Major Roles in Purchasing
5 major roles
Initiator
 Suggests/thinks of buying a particular product or
service
Influencer
 Advice/views carry weight in making a final buying
decision
Decider
 Makes a buying decision or any part of it
Buyer
 Makes the actual purchase
User
 Consumes or uses a product or service
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Purchasing decision-making model
5 major phases
 Need identification
 marketer must get customer to recognise need
 Banner and URL advertising, community discussions
 Information search
 Web directories, search engines
 Alternatives evaluation
 Newsgroup discussions, cross-site comparisons
 Purchase and delivery
 Electronic cash, virtual banking
 After-purchase evaluation—customer service
 Discussions in newsgroups
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Consumer Satisfaction
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Prentice Hall, 2002
One-to-One Marketing
Build a long term association
Meeting customers cognitive needs
 Customer may have novice, intermediate or expert skill
E-loyalty—customer’s loyalty to an e-tailer
 costs Amazon $15 to acquire a new customer
 costs Amazon $2 to $4 to keep an existing customer
Trust in EC
 Deterrence-based —threat of punishment
 Knowledge-based —reputation
 Identification-based —empathy and common values
 Referrals – Viral Marketing
Personalisation…
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Personalisation - Marketing Model
“Treat different customers differently”
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Prentice Hall, 2002
Personalisation
“Process of matching content, services, or products to
individuals’ preferences”
Build profiles – N.B. Privacy Issues
 Solicit information from users
 Use cookies to observe online behavior
 Use data or Web mining
Personalisation applied through
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Rule-based filtering (35<age<40  Jeep Cherokee)
Content-based filtering (based on stated favourites)
Constraint-based filtering (based on demographics)
Learning-agent technology (intelligent, e.g. from cookies)
Collaborative filtering examples
 Predict preferences based on similarities with other
customers
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Customer Service
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Provide search and comparison capabilities
Provide free products and services
Provide specialized information and services – ge.com
Allow customers to order customized products and services – dell.com
Enable customers to track accounts or order status – e.g. FedEx, Amazon
Personalized Web pages - record purchases and preferences – aa.com
FAQs - Customers find answers quickly
Troubleshooting tools—assist customers in solving their own problems
Chat rooms — discuss with experts and other customers
E-mail (most popular: inexpensive and fast) and automated response
Help desks and call centers
 Well trained personnel with access to customer history, purchases
• Metrics—standards to determine appropriate level of support
 Response to problem (hours for human, real-time for agents)
 Site availability and download times (<30 seconds)
 Up-to-date site and availability of relevant content
 Order fulfillment – fast
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 Return policy
Market Research for EC
Market segmentation - divide consumer market into groups to conduct
marketing research, advertising, sales
 E.g. by geography, demographics or psychographics
 (psychological characterization: the study of the psychological
profiles of potential buyers of a product, to improve its marketing)
 Tailor mailing campaigns to each segment
 Easier and cheaper than one-one personalisation
Online market research methods
 Conducting Web-based surveys
 Track customer activities – possibly illegal
Limitations of online research
 Skewed toward educated males with high income
 >40% answers to questionnaires inaccurate
How to analyse the gathered data?  Data Mining…
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Data Mining
searching for valuable information in extremely large databases
Automated prediction of trends and behaviors
 Example: from data on past promotional mailings, find out
targets most likely to respond in future
Automated discovery of previously unknown patterns
 Example: find seemingly unrelated products often purchased
together
 Example: Find anomalous data representing data entry errors
Mining tools:
 Neural computing
 Intelligent agents
 Association analysis - statistical rules
Web Mining - Mining meaningful patterns from Web resources
 Web content mining – searching Web documents
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 Web usage mining – searching Web access logs
Intelligent Agents in Customer Applications
Need identification - determine what to buy to satisfy a need
 looks for product information and evaluates - Querybot.com
Product brokering – find best product to match need
Merchant brokering - find vendor offering best deal
 Jango (embedded in excite program)
Negotiation - determine price and other terms of transaction
 Kasbah - users create agents for selling or buying goods
Purchase and delivery—arrange payment and delivery of goods
After sale service and evaluation - automatic answering
Auction support agents
Fraud and detection protection agents – eFalcon
Character-based interactive (animated) agents – extempo.com
Future agents - Delegation
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Summary
Consumer Behaviour – characteristics, stimuli decisions
Consumer Behavior Online – consumer types and purchasing
experiences
Demographics of Internet Surfers – environmental, personal
Major Roles in Purchasing – 5 roles
Purchasing decision-making model – 5 stages
Consumer Satisfaction  loyalty
One-to-One Marketing
Personalisation – build profiles, filter information
Customer Service – personalised information, help desks
Market Research – surveys, surreptitious tracking
Data Mining – extracting useful information about customers
Intelligent Agents – gather data, facilitate customer
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QUIZ 4
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