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SEGMENTATION INTERNET MARKETING 15.823 PROF. GLEN L. URBAN SPRING 2001.

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Presentation on theme: "SEGMENTATION INTERNET MARKETING 15.823 PROF. GLEN L. URBAN SPRING 2001."— Presentation transcript:

1 SEGMENTATION INTERNET MARKETING 15.823 PROF. GLEN L. URBAN SPRING 2001

2 OUTLINE REVIEW OF SEGMENTATION –BASES –METHODS LEVELS OF SEGMENTATION –GLOBAL –LOCAL –ONE TO ONE --PERSONALIZATION CONSUMER RELATIONSHIP MANAGEMENT

3 WHY SEGMENT MARKETS

4 WHY SEGMENT Preference Heterogeneity Balance Versus Costs –Variety versus Production INTERNET -- Some Costs Down –communicate individually –Interface customization Some Costs not Changed –Physical Production/Inventory –Software -- Service Design

5 DECISION Segment or Not? Low Cost or Custom Basis of Segmentation -- Many Choices Level of Segmentation -- Big Enough Common versus Segment Attributes -- Product/Service or Communication

6 On Line Trading eTrade? MLPFS Bridge Trader

7 TRADITIONAL BASES OF SEGMENTATION Demographics Attitudes -- Psychographics Preferences – products - like similar things – attribute importances -- benefit segmentation Uses -- Intensity (Heavy/Light)

8 TOP RIGHT SIDE LEFT SIDE FRONT VIEW

9 EXAMPLES PRIZM VALS

10 PRIZM USA census 1000 measures -- 34 factors -- 5 domains education and affluence family life cycle mobility ethnicity housing stock & urban cluster ZIP areas 12 and 40 cluster link to other zip data consumption

11 PRIZM THE 1980 ZIP CLUSTER MODEL TWELVE ZIP-CLUSTER GROUPS, IN DESCENDING ZQ RANK Group CodesGroup Titles S1Educated, Affluent Executives & Professionals in Elite Metro Suburbs S2Pre & Post-Child Families & Singles In Upscale, White-Collar Suburbs S3Upper-Middle, Child-Raising Families In Outlying, Owner-Occupied Suburbs U1Educated, White-Collar Singles & Ethnics in Upscale, Urban Areas T1Educated, Young, Mobile Families In Exurban Satellites & Boom Towns S4Middle-Class, Post-Child Families In Aging Suburbs & Retirement Areas T2Mid-Class, Child-Raising, Blue-Collar Families In Remote Suburbs & Towns U2Mid-Class Immigrants & Minorities In Dense, Urban Row & Hi-Rise Areas R1 Rural Towns & Villages Amidst Farms & Ranches Across Agrarian Mid-America T3Mixed Gentry & Blue-Collar Labor In Lo-Mid Rustic, Mill & Factory Towns R2Mixed Whites, Blacks, Spanish & Indians In Poor Rural Towns & Farms U3Mixed Blacks, Spanish & Immigrants In Aging, Urban Row & Hi-Rise Areas

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13 43 LIFE STYLE QUESTIONS My idea of fun at a national park would be to stay at an expensive lodge and dress up for dinner I could stand to skin a dead animal 1 to 7 agree --disagree scales cluster describe average person in cluster

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15 VALS2 GROUPS Actualizers Fulfilleds Believers Achievers Strivers Experiencers Makers Strugglers

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18 Levels of segmentation Global Country Local Individual

19 EXAMPLES Surgua -- SE Bank Wine.com -- California Wines Lycos/Terra Case Yahoo.Boston -- Local Audience Personalization

20 LOCAL AUDIENCE Like Minded Individuals Affinity Targeted commerce Segments –local residents –college student –new comers –Tourists –Business Travelers –Displaced/relocated natives

21 Personalization Screen Layout Targeted Marketing Permissive Marketing –ads –brochures/info Recommendations –Advisors –Intelligent Agents Mass Customization

22 CUSTOMER RELATIONSHIP MANAGEMENT Organize Data Profiling -- algorithms Rules Engine Delivery -- Communication/promotion Measurement Learning

23 TAKEAWAY Segmentation Art –Basis –Level Segmentation Science –Profiling –Rules Engines CRM -- Case Prime Response


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