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Internet Marketing & e-Commerce Ward Hanson Kirthi Kalyanam Requests for permission to copy any part of the material should be addressed to: PERMISSIONS DEPARTMENT THOMSON BUSINESS and ECONOMICS 5109 Natorp Boulevard Mason, OH 45040 Phone: (800) 423-0563. Part Two: Chapter Nine Personalization .

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slide1

Internet Marketing & e-CommerceWard HansonKirthi KalyanamRequests for permission to copy any part of the material should be addressed to: PERMISSIONS DEPARTMENTTHOMSON BUSINESS and ECONOMICS5109 Natorp BoulevardMason, OH 45040Phone: (800) 423-0563

part two chapter nine personalization
Part Two: Chapter NinePersonalization

“The rediscovery of the customer is a byproduct – perhaps the most important one – of the onset of the information revolution.”

Blattberg and Glazer, The Marketing Information Revolution

benefits of personalization
Benefits of Personalization
  • Product distinction: a standard product becomes a specialized solution
benefits of personalization1
Benefits of Personalization
  • Product distinction: a standard product becomes a specialized solution
  • Low cost access to luxury and status of personalized services
benefits of personalization2
Benefits of Personalization
  • Product distinction: a standard product becomes a specialized solution
  • Low cost access to luxury and status of personalized services
  • Hard to evaluate experience goods become predictable search goods
benefits of personalization3
Benefits of Personalization
  • Product distinction: a standard product becomes a specialized solution
  • Low cost access to luxury and status of personalized services
  • Hard to evaluate experience goods become predictable search goods
  • Survival through differentiation
benefits of personalization4
Benefits of Personalization
  • Product distinction: a standard product becomes a specialized solution
  • Low cost access to luxury and status of personalized services
  • Hard to evaluate experience goods become predictable search goods
  • Survival through differentiation
  • Increased customer loyalty
the personalization balance
The Personalization Balance
  • Competitive advantage comes when personalization is supported by focus on customer-relating capabilities (CRC)
the personalization balance1
The Personalization Balance

SOURCE: George Day and Christophe Van den Bulte, “Superiority in Customer Rlationship Management,” working paper, Wharton School, September 2002

the personalization balance2
The Personalization Balance
  • Personalization efforts can produce backlash: First Class envy
  • Excessive personalization wastes time
  • Sometimes, standardization is just fine
personalization approaches
Personalization Approaches
  • Mass Customization: blending standard products with individual information
personalization approaches1
Personalization Approaches
  • Mass Customization: blending standard products with individual information
  • Choice Assistance: advice giving systems cut clutter of product choice
personalization approaches2
Personalization Approaches
  • Mass Customization: blending standard products with individual information
  • Choice Assistance: advice giving systems cut clutter of product choice
  • Personalized Messaging: consumer needs and choices tracked across repeated interaction
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Many Opportunities for Personalization

SOURCE: Adapted from Kai Riemer and Carsten Totz, “The Many Faces of Personalization,” in Tseng and Piller, The Customer Centric Enterprise, (New York/Berlin: Springer Verlag, 2003

mass customization
Mass Customization
  • Customization of how a product is represented or of a product’s specific attributes through four approaches:
    • Collaborative
    • Cosmetic
    • Transparent
    • Adaptive
mass customization1
Mass Customization
  • Collaborative Customization: Online reconfiguration of a product to match consumer preferences
    • Example: Choosing features for a new car
mass customization2
Mass Customization
  • Cosmetic Customization: Packaging choices personalize standard products
    • Example: Choosing an iPod case

SOURCE: Getty Images

mass customization3
Mass Customization
  • Transparent Customization: Product features learn the user and adjust accordingly
    • Example: Google Scholar
mass customization4
Mass Customization
  • Adaptive Customization: Product features naturally customize themselves or are individually configured
    • Example: Weather reports by zip code
choice assistance
Choice Assistance
  • Determining if a recommendation system could enhance online marketing:
    • Do customer lifetime values vary greatly?
    • Do customer needs vary greatly?
    • Are key product attributes qualitative or complex?
choice assistance1
Choice Assistance

A recommendation system flowchart

choice assistance approaches
Choice Assistance: Approaches
  • Rules-based: Combines information about customers with understanding of how products are used
choice assistance approaches1
Choice Assistance: Approaches
  • Rules-based: Combines information about customers with understanding of how products are used
  • Computer-assisted self-explication (CASE): Advice generated from databases of consumer input
choice assistance approaches2
Choice Assistance: Approaches
  • Rules-based: Combines information about customers with understanding of how products are used
  • Computer-assisted self-explication (CASE): Advice generated from databases of consumer input
  • Collaborative Filtering: For complex product choices, linking like-minded individuals for recommendations
choice assistance approaches3
Choice Assistance: Approaches
  • Rules-based: Combines information about customers with understanding of how products are used
  • Computer-assisted self-explication (CASE): Advice generated from databases of consumer input
  • Collaborative Filtering: For complex product choices, linking like-minded individuals for recommendations
  • Endorsement: Virtual word-of-mouth referrals link users with preferred providers
personalized messaging
Personalized Messaging
  • Users must be authenticated through a fixed, valid address
    • Online through Web servers, browser cookies or registration systems
    • Email and Instant Messaging accounts
    • Cell phones and wireless PDAs
personalized messaging1
Personalized Messaging

Increasing levels of knowledge about Web user

  • Valid Name and Database
  • Valid Name
  • User ID
  • Cookies
  • Log Analysis
  • Online Behavior
  • Visitor Statistics
  • Anonymous
personalized messaging2
Personalized Messaging
  • With an established address, online behavior patterns suggest best approach for personalized messaging
personalized messaging3
Personalized Messaging
  • With an established address, online behavior patterns suggest best approach for personalized messaging
  • Distinct online events or inquiries can provide trigger moments for messaging
    • Example: A user searching for home value calculator could need real estate services
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