13.1 Introduction

This chapter demonstrates how the skills learned in Parts I and II can be applied to a particular domain: geomarketing (sometimes also referred to as location analysis or location intelligence).This is a broad field of research and commercial application.A typical example is where to locate a new shop.The aim here is to attract most visitors and, ultimately, make the most profit.There are also many non-commercial applications that can use the technique for public benefit, for example where to locate new health services (Tomintz, Clarke, and Rigby 2008).

People are fundamental to location analysis, in particular where they are likely to spend their time and other resources.Interestingly, ecological concepts and models are quite similar to those used for store location analysis.Animals and plants can best meet their needs in certain ‘optimal’ locations, based on variables that change over space [Muenchow et al. (2018); see also chapter 14].This is one of the great strengths of geocomputation and GIScience in general.Concepts and methods are transferable to other fields.Polar bears, for example, prefer northern latitudes where temperatures are lower and food (seals and sea lions) is plentiful.Similarly, humans tend to congregate in certain places, creating economic niches (and high land prices) analogous to the ecological niche of the Arctic.The main task of location analysis is to find out where such ‘optimal locations’ are for specific services, based on available data.Typical research questions include:

• Where do target groups live and which areas do they frequent?
• Where are competing stores or services located?
• How many people can easily reach specific stores?
• Do existing services over- or under-exploit the market potential?
• What is the market share of a company in a specific area?
  This chapter demonstrates how geocomputation can answer such questions based on a hypothetical case study based on real data.