Although thirteen distinct stages were suggested, there is no unanimity among research studies as to the most appropriate categorization of life cycle. For example, the dividing line for terms such as young and older might be 40 years of age in one study and 45 in another, which makes it difficult to compare results among various research studies. In spite of these definitional difficulties there is nevertheless widespread agreement on the relationship between life cycle and consumer behavior.
Sears & Roebuck Inc did a large study to find out who purchased what at what stage of life. They found that people leaving the young single stage and entering the young family stage were far more likely to buy and own all types of appliances. Such information helps Sears corporate buyers, marketers advertisers and desks staff. For instance sales people are encouraged to identify the customer’s position in the lifecycle – how many kids, what are their ages, and so forth to sell products to appropriate prospects.
The financial services industry clearly recognizes that households act out different stages in the family life cycle, various financial needs arise. For example, research has shown that the family lifecycle is a key determinant of banking interest and behavior. Implementation of this philosophy is illustrated by citizens Savings Bank of Ithaca, New York, which began using selling system based on family life cycle. The system used a visual sales aid book and customer data gathering forms that enabled bank branch personnel to analyze new customer’s needs when accounts were opened thereby helping them to present other financial products. Using colorful point of sale graphics and a computer based household central information file the program became very successful and won industry awards. In a test group of customers, Citizens increased its penetration level from 1.8 services per household to 3.4 services per household in just six months.
Research done using the family life cycle model has revealed many consumption differences across house holds lifecycle stages indicating that the model is a useful segmentation tool. It is a good prediction of individual attitudes and leisure activities. The model is strongly and significantly related to food and beverage consumption, major and minor appliance ownership, dollar value of major household acquisitions (first and second homes, autos, RVs, boats, etc) and dollar value of home entertainment devices (stereo, TVs, VCRs etc) and furniture.
A dimension related to the family life cycle concept is the household’s acquisition pattern of durable goods. Research on this subject has sought to classify households based on their durable goods ownership and / or purchase plans. Thus, newly formed households start out with a set of durable goods acquired through gifts, purchases, lease / rentals previous ownership or as part of the first home dwelling. But because newly formed households are seldom able to purchase the complete set of durables needed to furnish a household, families must decide on an order of purchase and a decision plan for how the purchases will be made over time. Researchers have demonstrated the existence of some underlying priority pattern or order in which household durables are brought. For example, a set of comfort products (such as washer, dryer, dishwasher, freezer, and microwave oven) were found to be acquired in a pattern. A more extensive study that tracked the decision and purchase behavior of the same households for ten durable items for a thirteen year period also found an order of acquisition for household durables. Such findings can have relevance to marketers interested in forecasting consumer demand and targeting market segments.
Further evidence is provided by cross national research studies in which the sizes and compositions of household expenditures were found to be systemically reacted to the stage of the family cycle. Such findings are relevant to marketing mangers when developing forecast, for example. Demand for different products and service categories may be estimated from knowledge of the relationship between demand and stage in life cycle and the predicted number of households in the various stages. A number of other studies have related shopping behavior to life cycle stage.