Geodemographics is the “analysis of people by where they live” (Sleight, 1997, p. 16). It is the suggestion that WHERE you are, says something about WHO you are; that knowing where someone lives provides useful information about how that person lives. To quote some product advertising, it is the possibility that “we know who you are, because we know where you live”. It is a simple idea – one that has shown itself to be of commercial value and the catalyst of a rapidly growing and globalizing industry. Continue reading Geodemographics, GIS and Neighbourhood Targeting – Richard Harris, Peter Sleight, Richard Webber
“While the real-estate industry is most closely associated with location, it has been one of the slowest to catch on to the potential (Sherwood-Bryan 1993d). Nevertheless, it has started to implement a variety of applications (Castle 1993b). One of the most obvious, and least implemented, applications is supporting Multiple Listing Services (MLS) (Castle 1993c). An MLS is the tool that almost every residential realtor (estate agent) uses to analyse available properties. It is a computerized system that lists available properties and includes the characteristics of each property including size, type, number of bedrooms, listing price, etc. We are beginning to see inclusion of mapping capabilities into these systems. Continue reading GIS FOR REAL ESTATE – GIS for Business and Service Planning
Telecommunications is currently one of the most dynamic industries in the United States and worldwide. Competition for the cellular telephone services market is strong in the US, and the company that can provide the best service has a significant advantage (Roan 1993). Current technology primarily relies on equipment within a “cell site” to control the communications interface between other cell sites and the traditional telephone system. Because the location of each very expensive cell site determines coverage, which in turn determines the level of service offered, optimal location of the cells is critical (Sherwood-Bryan 1993c). Continue reading GIS FOR TELECOMMUNICATIONS – GIS for Business and Service Planning
Consumer packaged goods are small, non-durable items that are generally bought at the grocery store. These might include soda, breakfast cereal and laundry detergent. Like most retailers and manufacturers of consumers’ goods of any type, the consumer packaged goods industry is beginning to use micro-marketing techniques (Buxton 1993). Through using a sophisticated combination of databases and manipulation techniques, product marketing programmes can be developed at the retail chain level. In the US, almost all grocery stores use check-out scanners. These scanners read a bar-code on each product and automatically provide the price of the product. This is convenient for stores because they can change the price of the product (such as for a sale) without having to re-tag each item. Not only is this convenient for stores, but because of this process, a very rich database of what brand’s products are purchased at what stores is generated. These data are aggregated into approximately 50 “scanner markets” that cover various portions of the US. By combing these data with the demographics that tend to drive product demand, such as age and income, a buying power index (BPI) can be modelled for stores. The BPI indicates how much of various products could be sold at that store. By knowing a store’s BPI, the retailer can improve the product mix (micro-marketing) to “push through more product” – to use the industry jargon.
Among fast-food chain restaurants such as McDonald’s and Burger King, the most visible and vocal users of GIS are at Arby’s. Among a variety of applications used at Arby’s is one that uses drive time to establish the likely trade area for an existing or potential store (Freeling 1993). In the fast-food business, customers are likely to be attracted more to the convenience of the product than to its gourmet appeal. It is, therefore, important to look at a trade area from the perspective of drive-time accessibility. Like many retailers, Arby’s personnel know how long someone will drive to access their product. In addition, they are familiar with the demographic characteristics of their typical customers. By analysing the demographics of a trade area established by using drive times, the likely sales performance for a store can be modelled. Arby’s is careful not to “cannibalize” an existing store when developing a new store. Cannibalizing means taking customers from one of their existing stores. Cannibalization should be avoided since a new store should increase overall business, not spread it around. By the same token, they are very eager to take away their competitors’ customers, and so they carefully analyse their competitors’ existing locations in comparison with their own.
Levi Strauss & Company (LS&Co) is a good example of a product retailer that has begun to use geographical technology to customize “product mix”, or the combination of products available in specific stores (Allen 1993). LS&Co is one of the world’s largest clothing manufacturers, and sells many product lines in addition to Levi’s jeans. Unfortunately, the company’s sales had been lagging significantly primarily as a result of mergers, acquisitions, price wars and significant retailers such as GAP chain creating their own product lines instead of selling LS&Co’s products. Continue reading GIS FOR RETAIL AND PRODUCT MIX – GIS for Business and Service Planning
It is highly likely that the insurance industry will soon face similar regulations to those already faced by the banking industry (Mertz 1993a). The reporting is likely to be at the zipcode (postcode) level. However, since this is in the future, this section on insurance will focus on current applications: risk assessment and avoidance. In the US, natural disaster after natural disaster has occurred over the last four years, bringing the total insurance industry’s bill to $34 billion (Mertz 1993b). Because of this, the industry has begun seriously to consider how it underwrites policies. The Oakland fire, Hurricane Andrew and the floods and other catastrophes of the summer of 1003 each pointed out the need for greater underwriting care. Insurance companies are beginning to realize that they must either refuse to insure properties that are at great risk from natural disasters, or justify larger premiums for doing so, or clearly identify precise areas in which property damage may be partially reimbursed from other sources. For example, the cross-hatched areas in the figure are wind-pools: insurers who write property-damage policies in these areas may be partially reimbursed by a state fund. Continue reading GIS FOR INSURANCE – GIS for Business and Service Planning