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Encyclopedia > Proximity mapping

In marketing and business strategy, proximity mapping is a technique used by IBM, McKinsey and other corporations to illustrate the relative closeness of market segments or characteristics in a two-dimensional space -- typically a sheet of paper or a presentation slide. It has been suggested that Product marketing be merged into this article or section. ... Strategic management is the process of specifying an organizations objectives, developing policies and plans to achieve these objectives, and allocating resources so as to implement the plans. ... International Business Machines Corporation (IBM, or colloquially, Big Blue) NYSE: IBM (incorporated June 15, 1911, in operation since 1888) is headquartered in Armonk, NY, USA. The company manufactures and sells computer hardware, software, and consulting services. ... McKinsey & Company is a privately owned management consulting firm. ...

Contents


Examples

Adjacent Markets

Here, for example, is a proximity map of the IT market in the UK, based on 2004 values:

Proximity map of the UK IT market
Proximity map of the UK IT market

The map was constructed in response to the often-repeated statement that Dell, Inc. expands into adjacent markets. Such statements have tended not to be supported by an explanation of what an adjacent market might be, leaving many with the tautologous feeling that an adjacent market is simply one that Dell expands into. Image File history File links UK_IT_market. ... Image File history File links UK_IT_market. ... Dell Inc. ...


This map was constructed on the basis that, given any pair of IT markets, the more vendors that are common to both markets, the closer they should be on the map.

  • The relative size of each circle is proportional to the size of that UK market in 2004, as measured by IDC.
  • The relative distance between the centres of any pair of circles is negatively correlated with the number of vendors which operate successfully in both markets.
    • This entails comparing the Top 10 vendors in each of the two markets, counting the number of vendors common to both, and creating a distance metric equal to 10 minus that vendor count.
    • The use of a tool such as Excel Solver can then be used to find the optimum placing of these points which minimises the difference between the required distance as measured by the metric and the compromise distance needed to locate all the points in two-dimensional space.
  • The colouration of each circle is simply to aid the eye in locating all middleware markets, server markets etc.

Related IT Solutions and Technologies

Proximity map of IT solutions and technologies
Proximity map of IT solutions and technologies

This proximity map was designed to show the strength of the association between various IT technologies and solutions, in terms of UK-focussed documents on the Internet. A lengthy series of searches on Google was conducted: Image File history File links Download high resolution version (948x639, 155 KB)Created by Gavin Wilson 2005 File history Legend: (cur) = this is the current file, (del) = delete this old version, (rev) = revert to this old version. ... Image File history File links Download high resolution version (948x639, 155 KB)Created by Gavin Wilson 2005 File history Legend: (cur) = this is the current file, (del) = delete this old version, (rev) = revert to this old version. ...

  • The size of each circle represents the total number of documents that Google found containing 'UK' and the solution name.
  • The distance between each pair of circles is negatively correlated with the number of documents found by Google containing 'UK' and solution1-name and solution2-name.
  • The basis for colouring the circles is independent of the proximity mapping, but in this case it is based on the number of documents found by Google that associate IBM with the solution relative to the number of documents associating the best competitor with the solution.

Choosing a distance metric

To avoid a potentially absurd result, the formula d(A, B) chosen to represent the distance between any two sets A and B must satisfy the four basic requirements of a metric space:

  1. d(A, B) >= 0
  2. d(A, B) = 0 if and only if A = B
  3. d(A, B) = d(B, A)
  4. d(A, B) + d(B, C) >= d(A, C)


Examples of the types of entities that can be proximity-mapped include:

  • Markets, by the number of vendors common to each pair,
  • Keywords, by the number of documents containing each pair of keywords,
  • Segments and needs, by the percentage of members of each segment rating the need a high priority.

An example of an entity that cannot be proximity-mapped is:

  • People, by the closeness of their relationships. (This fails one of the requirements of a metric because A can be very close to both B and C, yet B and C might be very distant from each other.)

See also

Multidimensional scaling (MDS) are a set of related statistical techniques often used in data visualisation for exploring similarities or dissimilarities in a given data set. ... Morphological analysis is a technique developed by Fritz Zwicky (1966, 1969) for exploring all the possible solutions to a multi-dimensional, non-quantified problem complex. ...

Further reading

  • [[|Aaker, Kumar and Day]] () ( 1989). ""  [ Marketing Research]New York: John Wiley. ISBN 0471363405..
  • [[|Sutherland, W. A.]] () ( 1975). ""  [ Introduction to Metric and Topological Spaces]Oxford: Clarendon Press. ISBN 0198531613..

</math> Image File history File links Crystal_kchart. ... This article does not cite its references or sources. ...


  Results from FactBites:
 
Proximity GIS/Mapping Software (506 words)
Proximity makes widespread use of "shapefiles" and "shapefile structures." This "GIS data file design" was originally introduced by ESRI and is in widespread use today with ESRI and non-ESRI products.
Proximity has no business relationship with ESRI and is not a reseller of ESRI products.
Proximity recognizes the important contribution that has been made by ESRI in the development of the shapefile architecture and support.
Map Analysis Topic 14: Deriving and Using Travel-Time Maps (3925 words)
The small map in the top-left of figure 1 is a display of the travel-time map developed last month.
Travel-time maps are most often used within the context of a road system connecting people with places via their cars.
The map processing steps for considering aesthetics are identical—calibrate the visual exposure map for a Beauty_weights map and multiply it times the basic Hiking_friction map.
  More results at FactBites »


 

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