Market Segmentation

Separating customers into market groups provides the basis for successful strategy development in marketing a restaurant. Market segmentation is the process of dividing a total market into groups of people with similar needs, wants, values, and purchasing behaviors. A market is not a place, but rather a group of people, as individuals or organizations. The group needs products and possesses the ability, willingness, and authority to purchase them. A market segmentation is a mixture of individuals, groups, or organizations that share one or more characteristics, which causes them to have similar product needs.

In a homogenous market, a marketing mix is easier to design than one in a heterogeneous group with dissimilar needs. Choosing the correct variable for segmenting market is important in developing a successful strategy. Variables are often broken down into 4 categories for the segmentation process: geographic, demographic, psychographic, and behavioristic.

Variable: Geographic

          Region:

o   Pacific, Mountain, West North Central, West South Central, East North Central, East

          City/metro population:

o   Under 5,000; 5,000-20,000; 20,000-50,000; 50,000-100,000; 100,000-250,000; 250,000-500,000; 500,000-1,000,000; 1,000,000-400,000; 4,000,000 or over

          Density

o   Urban, suburban, rural

          Family life cycle

o   Northern, southern

Variable: Demographic

          Age:

o   Under 6, 6-11, 12-19, 20-34, 35-49, 50-64, 65+

          Gender:

o   Male, female

          Family size:

o   1-2, 3-4, 5+

          Family life cycle:

o   Young, single; young, married, no children; young, married, youngest child under 6; young, married, youngest child 6 or over; older, married, with children; older, married, no children under 18; older, single; other

          Income:

o   Under $10,000; $10,000-$15,000; $15,000-$20,000; $20,000-$30,000; $30,000-$50,000; $50,000-$100,000, $100,000 and over

          Occupation:

o   Professional and technician; managers, officials, and proprietors; clerical, sales; craftspeople, foreman; operatives; farmers; retired; students; housewives; unemployed

          Education:

o   Grade school or less; some high school; high school graduate; some college; college, graduate

          Religion:

o   Catholic, Protestant, Jewish, Muslim, Hindu, other

          Race:

o   White, Black, Asian, Hispanic

          Nationality:

o   American, British, French, German, Italian, Japanese

Variable: Psychographic

          Social class:

o   Lower lowers; upper lowers; working class, middle class, upper middles, lower uppers, upper uppers

          Lifestyle:

o   Straights, swingers, longhairs

          Personality:

o   Compulsive, gregarious, authoritarian, ambitious

Variable: Behavioristic

          Occasions:

o   Regular occasion, special occasion

          Benefits:

o   Quality, service, economy, speed

          User status:

o   Nonuser, ex-user, potential user, regular user

          Usage rate:

o   Light user, medium user, heavy user

          Loyalty status:

o   None, medium, strong, absolute

          Readiness stage:

o   Unaware, aware, informed, interested, eager, intending to buy

          Attitude toward product:

o   Enthusiastic, positive, indifferent, negative, hostile

Geographic variables include climate, terrain, natural resources, population density, and subculture values that influence customers’ product needs. Demographic variables consist of population characteristics that might influence product selection like age, gender, race, ethnicity, income, education, occupation, family size, family life cycle, religion, social class, and price sensitivity. Psychographic variables include many factors that can be used for segmenting the market, but the most common are motives and lifestyle. Lifestyle segmentation categorizes people according to what is important to them and their mode of living. A classification system for segmenting customers in terms of lifestyle factors is the VALS: Values and Life-Styles research program. The VALS model is broken down into 3 parts:

          Ideals:

o   Consumers make choices based on their knowledge and principles.

          Achievement:

o   Consumers make choices based on what they perceive will show their success to their peers.

          Self-expression:

o   Consumers make choices based on a desire for social or physical activity, variety, or risk.

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Quantity Demand: Historical Roots

The desire for an efficient foodservice operation requires that the production manager to know the estimated number of customers or the number of servings of each menu item in time to order prom the procurement unit. Good forecasts are essential for managers in planning smooth transitions from current to future output, regardless of the size or type of the foodservice (i.e., schools, hospitals, or restaurants). Forecasts vary in sophistication from those based on historical records and intuition to complex models requiring large amounts of data and computer time. Choosing a forecasting model that is suitable for a particular situation is essential.

Historical Records

Adequate historical records constitute the basis for most forecasting processes. Often, past customer counts, number of menu items prepared, or sales records re used to determine the number of each menu item to prepare. These records must be accurate and complete, or they cannot be extended into the future with any reliability.

Effective production records should include:

          Date and day of the week

          Meal or hour of service

          Notation of special event , holiday, and weather conditions, if applicable

          Food items prepared

          Quantity of each item prepared

          Quantity of each item served

Although production unite records reveal the vital information on menu items served to customers, production is by no means the only organizational unit that should keep records. Only by cross-referencing records of sales with those of production can a reliable historical basis for forecasting be formalized. Records of sales will yield customer count patterns that can be useful for forecasting. These data can be related to the number of times customers select a given menu item or the daily variations induced by weather or special events.

Historical records in the production unit provide the fundamental base for forecasting quantities when the same meal or menu item is repeated. These records should be correlated with those kept by the purchasing department, which include the name and performance of the supplier and price of the food items.

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