In order to investigate the market and its related variables, of perceptions, attitudes, opinions or customer’s behaviour respectively, marketing research has not got other capture tools than field observation and questionnarie inquiry, and neither data measurement/interpretation devices other than statistico-mathematical methods known as „data analysis”. Progresses recorded in the past years concerning development of methods and their implementation by means of some complex data processing systems but easy to handle, provided the marketing research a powerful introspection tool. This paper shows one of the descriptive methods of data analysis and its applications for marketing data.hierarchical classification, marketing data, typological analysis.

Manuela Rozalia Gabor

English

Research Papers in Economics

Management & Marketing (2009) Vol. 4, No. 4, pp. 125-132. 
 
 
TYPOLOGICAL ANALYSIS AS ANALYSIS METHOD  
OF MARKETING DATA  
 
Manuela Rozalia Gabor  
 „Petru Maior”University, Târgu Mureş 
 
 
Abstract. In order to investigate the market and its related variables, of perceptions, attitudes, 
opinions or customer’s behaviour respectively, marketing research has not got other capture 
tools than field observation and questionnarie inquiry, and neither data 
measurement/interpretation devices other than statistico-mathematical methods known as   
„data analysis”. Progresses recorded in the past years concerning development of methods 
and their implementation by means of some complex data processing systems but easy to 
handle, provided the marketing research a powerful introspection tool. This paper shows one 
of the descriptive methods of data analysis and its applications for marketing data. 
 
Keywords: hierarchical classification, marketing data, typological analysis. 
  
 
1. Introduction 
 
Marketing has as a key goal the orientation of a firm’s activities according to 
its customers’ current and future needs. It necessarily assumes the existence of a well 
organised information system, but also the knowledge of some modern analysis, 
processing and interpretation techniques of the so complex information in the field of 
marketing. 
In the studied literature, data analysis is mentioned as being one of the most 
important stages within a research survey preceded by another stage having the same 
importance namely, preliminary analysis  known as exploratory data analysis. 
The data analysis methods are many, their classification is done according to 
the nature of surveyed variables and existing information a priori concerning the 
nature of the cause-effect relations  in which variables are involved, the data analysis 
methods can be grouped in two major categories: 
  Interrelation analysis methods (descriptive)  
  Dependence analysis methods (explanatory)  
When there isn’t the possibility of separating the variables in two 
subquantities, one of dependent variables and another of independent variables the 
interrelation analysis methods are used and whose main goal is to set the cause and 
to what extent the surveyed variables are connected among them and to also measure 
the  interdependence rate, to identify the variables with relevant significance, to 
identify categories and or classes or variables.  
 
 Management & Marketing 
 
126
2. Typological analysis – theoretical and methodological  
considerations  
 
Known in the literature as group analysis, cluster analysis, numeric 
taxonomy  or  classification analysis, this method aims to classify a heterogenous 
quantity (made of objects, individuals or cases) in relatively homogenous groups, 
according to a series of variables or interdependence relations between them 
(Malhotra, 2004, p. 539). This classification is thus carried out to ensure the 
homogeneity of objects within groups and a higher differentiation among groups, the 
statistic principle on which is based is that of minimizing the variation between the 
statistic units (intraclass inertia) in order to gather them in classes and maximization 
of variation between classes (interclass inertia).  
The typological analysis (Giannelloni, J. L. and Vernette, E., 2001, p. 395) is 
established on the distances between individuals that can represent people, marks, 
products, regions etc., input data being presented as a picture of distances, selection of 
the calculation methods being one of the stages related to the making of typological 
analysis, the method being adapted to the type of data involved in the study (metric, 
ordinal or nominal).  
Compared to the other descriptive methods of data analysis, the typological 
analysis has a predominantly heuristic character and is not based on complex statistic 
tools, being much different than those. As a working method, the typological analysis 
aims the similitude reports between objects, and is used when there isn’t any a priori 
assumption and we are in the stage of  the exploratory analysis of research.  
The stages covered in the application of the typological analysis method are 
represented in Figure 1. 
 
 
 
 
 
 
 
 
 
Figure 1. Stages of making the typological analysis 
(Adaptation after Malhorta, N., Études marketing avec SPSS – 4e édition, Ed. Pearson 
Education France , Paris, 2004, p. 545) 
 
The stage of problem enunciation should have the following basic principle: 
the set of selected variables should aim the identification of some similarities between 
objects / cases to answer the issue of the marketing research.  
 
Problem 
enunciation  
Selection of the method  
of distance measurement 
Establishment of 
grouping procedure  
Decision over the 
number of groups  
Interpretation and 
establishment of group 
profile  
Verification of 
classification 
validation   Typological analysis as analysis method of marketing data  
 
127
 
 
 
 
Figure 2. Classification of grouping procedures 
(Adaptation after Malhotra, N., Études marketing avec SPSS – 4e édition, Ed. Pearson 
Education France, Paris, 2004, p. 547) 
 
In case of the second stage, in order to measure similarities, calculation of the 
distances between objects is most often used. However, this method requires the 
previous knowledge of the type of scale used to measure the variables. According to it, 
for  nominal variables  measurement of coefficient correspondence, and in case of 
metric variables, measurement of the distance or the configuration. Other types of 
distances that can be calculated are: Euclidean square distance, city – block distance 
(Manhattan or rectangular distance) the Cebîşev distance,  Mahalonobis  distance– 
used with the methodological goal of removing the influence of the measurement scale 
and of multicollinearity in distance calculation. For the third stage  there are several 
statistic grouping procedures shown in Figure 2.  
The classification methods (Everitt,1974, in Smajda, 1988) may contain: 
  ranking techniques (upward or downward) that lead to a tree structure or a 
dendogram; 
GROUPING 
PROCEDURES  
Hierarchical  
grouping ierarhică 
Non-hierarchical 
grouping (based p k - 
medii) 
Sequential treshold 
Parallel  
Parallel treshold  
Partitioning 
optimization  
Downward  
Aggregation 
based methods  
Minimum  dist.  
Maximum dist. 
Average dist. 
Variation based 
methods  
Ward  
method  
Centroid based 
methods  
Upward  Management & Marketing 
 
128
  partitioning techniques (with or without optimization) where, a 
classification criterium enables the definition of mutually exclusive classes also 
making a partition; 
  density techniques or the research on how groups are made in searching the 
regions containing a relatively dense concentration of points; 
  various techniques that cannot be classified in previous categories. 
The most common methods in marketing are the upward grouping methods, 
while the non-hierarhical methods (nodal) (Spircu, L., Calciu, Spircu, T., 1994, p. 
105) are usually used when the number of individuals is very high and these may 
classify – according to the group setting technique – in: 
A. Reallotment methods wherein an object, alloted to a group at an i iteration, 
can be realloted to another group at a subsequent iteration. The algorithms concerned 
end when there is not any object whose reallotment has as a result the improvement of 
the classification criterium used. 
B. Density searching methods that assume that variables follow repartition 
laws whose parameters vary from one group to another. In this assumption the 
quantity of individuals is represented by means of a repartition density for the groups 
of individuals. It is searched to identify individuals belonging to the same repartition. 
C. Direct methods classify individuals based on the proximity between the 
pairs of variables; more, they allow to classify simultaneously both individuals and 
variables. 
D. Methods of dimension reduction  (the oldest classification methods) 
exemplified by means of factor analysis of correspondences. 
As regards the upward hierarhical grouping [1], in Figure 3 it is shown the 
simple bonding, full bonding and average bonding schemes and the Ward method and 
the centroid method (mentioning that the studied literature also describes the flexible 
method of Lance and Williams and the median method ) 
 
 
 
Figure 3. Procedures of hierarhical classification 
(Source: Aaker, D. A., Kumar, V., Day G. S., Marketing research – Sixth Edition,  
ED. John Wiley & Sons, New York, 1998, p. 600)  Typological analysis as analysis method of marketing data  
 
129
For the downward hierarhical grouping, A. Smajda (1988, p. 83-103) 
describes the following methods:  
  The Mac – Nawghton – Smith method that is based on the fact that it 
does not entail that inlet data should be as a distance matrix and similarities and 
correlations are excluded, being prevailingly a heuristic method; 
  The Edwards – Cavalli – Sforza method; 
  The Howard and Harris method.  
The stage of group explaining and validation (Spircu, L., Calciu, Spircu, T., 
1994, pp. 112-113) mainly aims to find variables that play a major role in grouping. 
This issue can be done by describing each group both by means of active variables (of 
grouping) as well as passive variables. It can be asked if groups made are really 
different between them thus validation being necessary, another stage in classification 
analysis. There are several procedures of validation: 
  Analysis tests of variance for each active variable (quantitative) can be 
used; 
  Analysis techniques of discrimination can be chosen wherein the explained 
variable (nominal) is the type of group the individual belongs to; 
  A classification iterative procedure can be applied on a quantity of 
individuals – witnesses up to the group stabilization.  
  Indicators and notions related to typological data analysis are shown in 
Table 1. 
 
Table 1 
Indicators and statistic notions related to typological analysis 
 
Indicator or statistical term used  Description 
Grouping program  It provides information about objects or cases that are mixed, 
in each stage of hierarhical grouping processes. 
Group centroid  It is represented by the average values of variables for all 
objects  / cases of a certain group. 
Group centres   There are starting points in making the groups non-hierarhic, 
and groups are built around them. 
Proximity index between 
individuals  
 
The number expressing the existing similarity or disimilarity   
between two individuals considering all active variables that 
characterize them. 
Group affiliation   It indicates whose group each object/case belongs to. 
Active variables   Variables that serve the group making. Example: preference 
for certain brands 
 
Passive variables  
Variables that serve when explaining groups, describing 
classes but do not participate in their formation for instance 
age, socio-professional category, monthly income, Staregion 
etc 
 
Dendogram 
It is the tree-like graphic whereby groups are represented (how 
and when they form) in case of hierarhical grouping and it is 
read from right to left. Management & Marketing 
 
130
Indicator or statistical term used  Description 
 
Stalactite diagram  
It is a graphic that shows any time, the affiliation of cases to 
groups; the name of icicle comes from how it is represented, 
with vertical variables and horizontal groups, interpretation 
being done upwards. 
 
Distances between group centres  
 
It shows how much pairs of groups are separated between 
them. The higher the distances are the more different the 
groups are. 
 
 χ2distance  
It is used in case when variables are presented by frequency 
matrix thus transforming the probability matrix. 
 
Euclidian distance  
It is used when variables are ordinal obtaining the matrix of 
average ranks (most times the Spearman’s rank correlation 
coefficient is used or, sometimes, the tangular distance). 
Similarity/distance  matrix    It contains values of distances between objects/ cases. 
 
(Adaptation after Dăneţiu, T., Multivaried methods used in CAD analysis of marketing data – 
doctoral dissertation, p. 67-68, Spircu, L., Calciu, M., Spircu, T.,Data marketing analysis, Ed. 
ALL, Bucharest, 1994, p. 106  and Malhorta, N. - Études marketing avec SPSS – 4e édition, 
Ed. Pearson Education France, Paris, 2004, p. 542-543) 
 
In the studied literature, in the quoted paper Smajda details  the similarities 
ratios that can be calculated  (Smajda, 1988, p.53 -67), respectively: Jaccard and 
Tanimoto ratio,  Rao and Russel ratio, Ochriai ratio, Yula ratio, Kubeyski ratio, 
Sokal ratio,  Pearson ratio,  all starting from the number of positive coincidences 
between two comments,  the number of negative coincidences, the number of 
coincidences and the total number of  variables. 
 
3. Marketing data analysis of typological analysis  
 
In marketing there is a high interest in the descriptive classification techniques 
of objects. In this field, objects or individuals can be consumers, products or brands of 
various products, commodity markets, etc. concrete examples as regards the 
application of this method of marketing data analysis being comprised in Table 2. 
 
Table 2 
Marketing applications of typological analysis 
 
Purpose of research  Examples 
1. Market 
segmentation  
•  Segmentation tries to divide the quantity of consumers in groups of 
consumers, named segments or types.  Each segment is made of 
individuals whose features are similar. Thus it is about to admit, within 
diversity of buyers, their behaviour, in order to build up specific strategies, 
adapted to each segment in the surveyed population. 
•  We can define groups of consumers according to different geographic, 
socio-demographic, psychographic or behavioural variables and then focus  Typological analysis as analysis method of marketing data  
 
131
Purpose of research  Examples 
over behaviour or characteristics  of the components of these groups based 
on the information achieved in research. 
•  Segmentation according to the consumers’ life style, in line with benefits 
targeted for products bought; 
2. Research 
concerning brands   
•  The brands of the same product are surveyed, the perception of their 
characteristics being registered by the consumers. It results types  made 
from those brands that, within all the features, has similar perceptions at 
buyers. The knowledge of these types (classes) enables the knowledge of 
competitive brands (these are brands from the same class) and 
consequently, a suitable commercial policy can be adopted (Spircu, L., 
Calciu, M., Spircu, T. , 1994, p. 105). 
•  Brand grouping, determination of a brand competitive kit  and 
identification of some opportunities for new products, based on the analysis 
of attributes targeted by consumers as regards products and brands. Thus, 
as long as brands have been evaluated by means of these attributes, they 
can be grouped, and thus a better reporting to competition and consumers 
can be done. 
3. Marketing research 
concerning the launch 
of new products 
To this end, test markets are studied (either districts, either cities or even 
countries) following characteristics such as: the numbre of inhabitants,   
buying power per inhabitant, average age of inhabitants, number of 
unemployed people, number of selling points, audience of radio and TV 
spaces, newspaper circulation etc. specific markets result where tests can 
be done concerning the launch of a new product. 
4. The study of a 
population versus 
activities, interests 
and opinions  
•  It leads to the determination of a typology or a classification of the life 
style. Individuals belonging to the same group (the same class) express the 
same type of activities, interests and opinions. 
•  In order to group the clients with homogenous buying behaviour their 
classification is carried out starting from the amounts bought, the place of 
buying and the brand  of products purchased (Giannelloni, J. L., Vernette, 
E., 2001, p. 397). 
5. Data reduction  A number of thorough analyses can be carried out. These analyses can be 
evaluated at group level and not individually (comment), such as the case of 
studying the behaviour differencies between groups. 
(Adaptation after Spircu, L., Calciu, M., Spircu, T., Marketing data analysis, Ed. ALL, 
Bucharest, 1994, p. 112-113 and Dăneţiu, T. – Multivaried methods used in the CAD analysis 
of marketing data –doctoral dissertation, ASE, 2005, p. 66-67) 
 
Malhotra (2004, p. 542) also recommends it in the identification of the new 
production opportunities  (classifying brands and products in groups, for example, we 
can determine the competitive ensembles of the market), in selecting the market test 
and summarizing data. 
 
 
 Management & Marketing 
 
132
 
4. Conclusions 
 
The issues of data analysis descriptive methods are in line with many research 
objectives in the field of market analysis and not only, and comprises: 
•  Identification of the rules governing the movement of phenomena and 
economic and social processes, of main trends and regularities specific to their 
evolution; 
•  Identification of main factors whose influence leads to the making of some 
phenomena and processes; 
•  Determination of extent wherein an amount of influence factors concur to 
the formation of a certain effect; 
•  Ranking of factors that drive a certain effect according to the importance 
and significance of their influence; 
•  Identification of the main possibilities and as a result of them, behaviour of 
phenomena can be influenced in a desired way; 
In case of marketing data, the typological analysis has the major advantage 
that is applicable to qualitative, ordinary data, (most often used in practice in 
marketing research as analysis data), this classifying individuals in relation to their 
preferences compared to a certain characteristic.  
 
 
References 
 
Aaker, D. A., Kumar, V., Day G. S. (1998), Marketing research – sixth edition, John Wiley & 
Sons, New York, p. 600 
Dăneţiu, T. (2005), Multivaried methods used in CAD analysis of marketing data – doctoral 
dissertation, ASE Bucharest, p. 66-68 
Giannelloni, J. L., Vernette, E. (2001), Études de marche – 2e edition, Edition Vuibert, p. 395, 
p. 397 
Malhorta, N. (2004), Études marketing avec SPSS – 4e édition, Edition Pearson Education 
France, Paris, pp. 539, 542-543, 545, 547 
Smajda, A.  (1988),  Segmenter ses marches – applications pratique de technique de 
segmentation dans le marketing, Ed. PPR, p. 53-67, 67-73, 83-103 
Spircu, L., Calciu, M., Spircu, T. (1994), Marketing data analysis, Editura ALL, 
Bucureşti, pp. 105-106, 112-113 
 
 
Note 
In bibliographic information, these schemes are described as aggregation algorithms 
for proximity indices between classes, and are retrieved as the „method of most closest 
neighbours” for simple bonding, „method of most farthest neighbours” for full bonding and 
”method of average bonding” for average bonding. 

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Typological analysis as analysis method of marketing data

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