How the following retail question might be answered within a GI analytical environment? Suppose a consumer lives at location i (to be found at coordinate xi, yi)?
To answer this question, two ideas seem intuitive. First, that the attraction of the store to the consumer depends on what the store has to offer. This we shall quantify as the store’s mass (Mj), for reasons that will become clear. Second, that the consumer would prefer to travel a shorter distance to visit a store than a longer one and so the attraction of the store is related to the distance between locations i and j. These two assumptions allow the following spatial interaction model to be formed:
Continue reading SPATIAL INTERACTION MODELS – Richard Harris, Peter Sleight, Richard Webber
Geographic information systems have been described as a set of technologies that help us to see our small blue planet in better ways (Longley et al., 1999). More commonly referred to by the acronym GIS, applications include: local governance; business and service planning; logistics; and environmental management and modelling. In both public and private sector research, GIS are used to manage geographic information, help identify geographical trends and patterns and to model spatial processes.
However, GIS have been described as a “nearly” technology for marketers (McLuhan, 2003). Beyond the hype, the actual use of GIS presently is limited to the larger retailers and suppliers, with little expansion into marketing applications. This, despite widespread agreement that the true value of geographical information is only revealed once that information is analysed geographically! McLuhan (2003) cites a survey by GeoBusiness Solutions revealing that only 28% of company boards fully understand the operation and marketing benefits of GIS, with the perceived (and often, actual) high cost of investing in GI software and data products being one of the barriers to GIS reaching its potential. Continue reading Geodemographics and GIS – Richard Harris, Peter Sleight, Richard Webber
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.” The figure illustrates this link between people and places. 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.
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