1 Lecture 3: Serving the Customer Lecture Outline Consumer Behaviour Demographics of Internet Surfers Major Roles in Purchasing Purchasing decision-making.

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Presentation transcript:

1 Lecture 3: Serving the Customer Lecture Outline 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 CS5038 The Electronic Society

2 Consumer Behaviour Prentice Hall, 2002

3 Consumer Behavior Online Consumer types Individual consumers Commands most of the medias attention Organizational buyers Governments and public organizations Private corporations Resellers Purchasing types and experiences 2 dimensions of shopping experiences Utilitarianto achieve a goal Hedonicbecause its fun 3 categories of consumers Impulsive buyerspurchase quickly Patient buyersmake some comparisons first Analytical buyersdo substantial research before buying

4 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

5 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

6 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 evaluationcustomer service Discussions in newsgroups

7 Consumer Satisfaction Prentice Hall, 2002

8 One-to-One Marketing Build a long term association Meeting customers cognitive needs Customer may have novice, intermediate or expert skill E-loyaltycustomers 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…

9 Personalisation - Marketing Model Treat different customers differently Prentice Hall, 2002

10 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 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

11 Customer Service 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 toolsassist customers in solving their own problems Chat rooms discuss with experts and other customers (most popular: inexpensive and fast) and automated response Help desks and call centers Well trained personnel with access to customer history, purchases Metricsstandards 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 Return policy

12 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…

13 Data Mining 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 Web usage mining – searching Web access logs searching for valuable information in extremely large databases

14 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 deliveryarrange 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

15 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

16 QUIZ 4