Secom%20 Online%20 Marketing

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    Secom%20 Online%20 Marketing - Presentation Transcript

    1. Online Marketing John Hale Center for Information Security University of Tulsa john-hale@utulsa.edu *Slides adapted from E-Commerce: Business, Technology, Society – 2/e by K. Laudon and C. Traver, Pearson/Addison-Wesley University of Tulsa - Center for Information Security
    2. Overview 1. Consumer behavior 2. Basic marketing 3. Internet marketing 4. Customer relationships University of Tulsa - Center for Information Security
    3. Consumer Behavior Models • Attempt to predict/explain what consumers purchase and where, when, how much and why they buy. • Consumer behavior models based on background demographic factors and other intervening, more immediate variables University of Tulsa - Center for Information Security
    4. A General Model of Consumer Behavior University of Tulsa - Center for Information Security 4
    5. Background Demographic Factors • Culture: Shapes basic human values, wants perceptions and behaviors • Subculture: Subset of culture; forms around major social differences such as ethnicity, age, lifestyle, geography • Direct reference group: Include one’s family, profession/occupation, religion, neighborhood, schools • Indirect reference group: Includes one’s life-cycle state, social class and lifestyle group • Opinion leaders (viral influencers): Influence the behavior of others through their personality, skills or other factors University of Tulsa - Center for Information Security
    6. Consumer Decision Process University of Tulsa - Center for Information Security 6
    7. A Model of Online Consumer Behavior • Adds two new factors: Web site capabilities – the content, design and functionality of a site Consumer clickstream behavior – the transaction log that consumers establish as they move about the Web University of Tulsa - Center for Information Security
    8. A Model of Online Consumer Behavior University of Tulsa - Center for Information Security 8
    9. Basic Marketing Concepts • Marketing: The strategies and actions firms take to establish a relationship with a consumer and encourage purchases of products and services • Internet marketing: Using the Web, as well as traditional channels, to develop a positive, long-term relationship with customers, thereby creating competitive advantage for the firm by allowing it to charge a higher price for products or services than its competitors can charge University of Tulsa - Center for Information Security
    10. Basic Marketing Concepts • Firms within an industry compete with one another on four dimensions: Differentiation Cost Focus Scope • Marketing seeks to create unique, highly differentiated products or services that are produced or supplied by one trusted firm (“little monopolies”) University of Tulsa - Center for Information Security
    11. Feature Sets Defined as the bundle of capabilities and services offered by the product or service University of Tulsa - Center for Information Security 11
    12. Products, Brands and the Branding Process • Brand: A set of expectations that consumers have when consuming, or thinking about consuming, a product or service from a specific company • Branding: The process of brand creation • Closed loop marketing: When marketers are able to directly influence the design of the core product based on market research and feedback. E-commerce enhances the ability to achieve • Brand strategy: Set of plans for differentiating a product from its competitor, and communicating these differences to the marketplace • Brand equity: estimated value of the premium customers are willing to pay for a branded product versus unbranded competitor University of Tulsa - Center for Information Security
    13. Marketing Activities: From Products to Brands University of Tulsa - Center for Information Security 13
    14. Internet Marketing Technologies • Web transaction logs • Cookies and Web bugs • Databases, data warehouses, and data mining • Advertising networks • Customer relationship management (CRM) systems University of Tulsa - Center for Information Security
    15. Web Transaction Logs • Built into Web server software • Records user activity at a Web site • WebTrends a leading log analysis tool • Can provide treasure trove of marketing information, particularly when combined with: Registration forms – used to gather personal data Shopping cart database – captures all item selection, purchase and payment data University of Tulsa - Center for Information Security
    16. Cookies • Cookies: small text file that Web sites place on a visitor’s client computer every time they visit, and during the visit as specific pages are accessed. • Cookies provide Web marketers with a very quick means of identifying the customer and understanding his or her prior behavior • Location of cookie files on computer depends on browser version University of Tulsa - Center for Information Security
    17. Web Bugs • Tiny (1 pixel) graphic files embedded in e-mail messages and on Web sites • Used to automatically transmit information about the user and the page being viewed to a monitoring server University of Tulsa - Center for Information Security
    18. Databases and Data Warehouses • Database: Software that stores records and attributes • Database management system (DBMS): Software used to create, maintain and access databases • SQL (Structured Query Language): Industry-standard database query and manipulation language used in a relational databases • Relational database: Represents data as two-dimensional tables with records organized in rows and attributes in columns; data within different tables can be flexibly related as long as the tables share a common data element • Data warehouse: Database that collects a firm’s transactional and customer data in a single location for offline analysis by marketers and site managers University of Tulsa - Center for Information Security
    19. Data Mining • Set of analytical techniques that look for patterns in data of a database or data warehouse, or seek to model the behavior of customers • Types include: – Query-driven – based on specific queries – Model-driven – involves use of a model that analyzes key variables of interest to decision makers – Rule-based – examines demographic and transactional data of groups and individuals at a Web site and attempts to derive general rules of behavior for visitors – Collaborative filtering – behavioral approach; site visitors classify themselves into affinity groups based on common interests; products are then recommended based on what other people in the group have recently purchased University of Tulsa - Center for Information Security
    20. Data Mining and Personalization University of Tulsa - Center for Information Security 20
    21. Advertising Networks • Best known for ability to present users with banner advertisements based on a database of user behavioral data • DoubleClick best-known example • Ad server selects appropriate banner ad based on cookies, Web bugs, backend user profile databases University of Tulsa - Center for Information Security
    22. How Advertising Networks Work University of Tulsa - Center for Information Security 22
    23. Customer Relationship Management (CRM) Systems • Repository of customer information that records all of the contacts that a customer has with a firm and generates a customer profile available to everyone in the firm with a need to “know the customer” • Customer profiles can contain: – Map of the customer’s relationship with the firm – Product and usage summary data – Demographic and psychographic data – Profitability measures – Contact history – Marketing and sales information University of Tulsa - Center for Information Security
    24. Customer Relationship Management Systems University of Tulsa - Center for Information Security 24
    25. Customer Retention Marketing Techniques • Customization: Changing the product (not just the marketing message) according to user preferences • Customer co-production: Allows the customer to interactively create the product (Nike) • Transactive content: Results from the combination of traditional content with dynamic information tailored to each user’s profile University of Tulsa - Center for Information Security
    26. Other Customer Retention Marketing Techniques (cont’d) Customer service tools include: • Frequently asked questions (FAQs) – text-based listing of common questions and answers • Real-time customer service chat systems – company’s service representatives interactively exchange text messages with one or more customers on a real-time basis • Intelligent agent technology – bots • Automated response systems – send e-mail confirmations and acknowledgments • VReps University of Tulsa - Center for Information Security

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