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VORTEXVORTEXVersion 8.1.
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Software ApplicationSoftware ApplicationSociologySociology;;Marketing researchMarketing research;;Social-psychological researchSocial-psychological researchSocial-medical researchSocial-medical researchStaff recruitment, staff development Staff recruitment, staff development objectivesobjectives
Processing of surveys dataProcessing of surveys data::Corporate customersCorporate customers;;Consumers Consumers ((actual, potentialactual, potential););Experts;Experts;EmployeesEmployees. .
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Development of Data Collection ToolsDevelopment of Data Collection Tools
Development of Development of dictionary – dictionary – questionnaire layout.questionnaire layout.
Support of various types Support of various types of variables of variables ((alternativealternative, , polyvariantpolyvariant, , numericalnumerical, , stringstring).).
Import of layout toImport of layout to Word Word ((for printingfor printing). ).
Import of layout toImport of layout to HTMLHTML ((for Internet surveysfor Internet surveys).).
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Data EntryData Entry
Ergonomic type-in Ergonomic type-in methods. methods.
Visual list of answer Visual list of answer options including the options including the option of adding new option of adding new variants.variants.
Tracking of input errorsTracking of input errors..
Export/Import to/fromExport/Import to/from ExcelExcel, , SPSSSPSS and other and other programs.programs.
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Data ConversionData Conversion
Conversion of initial Conversion of initial variables to analysis-variables to analysis-friendly form.friendly form.
Generation of new Generation of new information from information from available data through available data through development of development of secondary indexes. secondary indexes.
Data standardizationData standardization..
Replacement of missing Replacement of missing data by various data by various methodsmethods..
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Information AnalysisInformation Analysis
Procedures of univariate, Procedures of univariate, bidimensional and bidimensional and multivariate analysis.multivariate analysis.
Application of Application of mathematical statistics mathematical statistics and qualitative data and qualitative data analysis methods.analysis methods.
Table and graphic Table and graphic representation of representation of analysis results. analysis results.
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Table and Graphical Representation of Table and Graphical Representation of ResultsResults
Import of any Import of any analysis results to analysis results to Microsoft Word as Microsoft Word as editable tables and editable tables and diagramsdiagrams;;
Copying of analysis Copying of analysis results as tables results as tables and diagrams to and diagrams to clipboard for clipboard for inserting in other inserting in other application application programs;programs;
Open Office Open Office compatibility.compatibility.
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Vortex characteristics:Using of polyvariant variables to optimize data input and analysis
Quantitative indexes for qualitative variables
Logical constructor of secondary variables
String variables handling
Quick analysis and output
Analysis of specific groups or segments
Multivariate qualitative interpretation of any option
Special marketing procedures and diagrams
((you may choose the relevant slide to switch you may choose the relevant slide to switch to)to)
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Using of polyvariant variables to optimize Using of polyvariant variables to optimize data input and analysisdata input and analysis
Polyvariant variable is designed for the Polyvariant variable is designed for the multiply choice questions handling. multiply choice questions handling.
Polyvariant variable reserves only one Polyvariant variable reserves only one column in data matrix to save space and column in data matrix to save space and time.time.
You can quickly input data as 1+3+5 You can quickly input data as 1+3+5 (numbers of selected options) or 2-5 (from (numbers of selected options) or 2-5 (from 2 to 5).2 to 5).
Polyvariant variables can be analyzed also Polyvariant variables can be analyzed also as alternative variables, so that all options as alternative variables, so that all options are together in a united table or graph.are together in a united table or graph.
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Quantitative indexes for qualitative variablesQuantitative indexes for qualitative variables
When a variable is When a variable is defined each value defined each value may receive an may receive an index – equivalent index – equivalent of quantitative valueof quantitative value
These indexes will These indexes will be used to calculate be used to calculate the approximate the approximate mean and other mean and other statistics without statistics without creating of a new creating of a new variable.variable.
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Logical constructor of secondary variablesLogical constructor of secondary variables
A fast way to unite A fast way to unite several variables in several variables in one multi-one multi-dimensional dimensional variable is variable is “Secondary variable “Secondary variable design” wizard design” wizard
The program will The program will calculate all calculate all possible possible combinationscombinations,, you you just have to assign just have to assign them new values.them new values.
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String variables handlingString variables handling
String variables can be used String variables can be used for open-ended questions for open-ended questions handling.handling.
Data may be set as text Data may be set as text strings.strings.
For the first time string For the first time string classification should be done classification should be done mostly manually using drag mostly manually using drag and drop method.and drop method.
However results of manual However results of manual classification can be saved classification can be saved and used the next time.and used the next time.
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Quick analysis and outputQuick analysis and output
Any analysis is simpleAny analysis is simple::
Select procedureSelect procedure
Select variablesSelect variables
Add characteristics Add characteristics of a table or graph.of a table or graph.
Copy a table or Copy a table or graph to MS Word graph to MS Word or clipboard to paste or clipboard to paste in other applicationin other application
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Analysis of specific groups or segmentsAnalysis of specific groups or segments
Any analysis Any analysis procedure can be procedure can be done both for the done both for the whole sample and whole sample and for a specific group for a specific group or segment. or segment.
Button “Selection” Button “Selection” allows to set allows to set analysis conditionsanalysis conditions
Specific group can Specific group can be selected by the be selected by the logical formula if logical formula if you click on you click on variables and variables and values.values.
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Multivariate qualitative interpretation of any Multivariate qualitative interpretation of any choicechoice
Double click on any Double click on any value in the value in the frequencies table frequencies table activates “Group activates “Group description” description” procedureprocedure..
The selected group The selected group will be described by will be described by Distinct features, Distinct features, Important features Important features and Segments and Segments which constitute this which constitute this group.group.
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Special marketing procedures and Special marketing procedures and diagramsdiagrams::
Different procedures of consumer segmentations including cluster analysis.
Different methods which research influence of various factors on consumer behaviour, including linear regression with multiple effect and multidimensional graph.
Polar profiles graph for brand image research.
Demand curve calculation and graph for estimation of the optimal product price.
((you may choose the relevant slide to switch to)you may choose the relevant slide to switch to)
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Consumer SegmentationConsumer Segmentation
Forming of various Forming of various target groupstarget groups..
Separate analysis for Separate analysis for various target groups.various target groups.
Comparative analysis Comparative analysis of various target of various target groups.groups.
Comparative analysis of Household income
Men 21-25 Men 15-20 Men 26-30
50000and more
40001 to50000
30001 to40000
20001 to30000
15001 to20000
12001 to15000
freq
uenc
y
100
90
80
70
60
50
40
30
20
10
0
Comparative analysis of Household income
Men 21-25 Men 15-20 Men 26-30
50000and more
40001 to50000
30001 to40000
20001 to30000
15001 to20000
12001 to15000
freq
uenc
y
100
90
80
70
60
50
40
30
20
10
0
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Graphs in consumers behavior Graphs in consumers behavior
Compare various Compare various groups in two groups in two dimensions. dimensions.
Regression lines for Regression lines for optimal price optimal price
Estimate optimal curve Estimate optimal curve
Optimal Price for 1 bottle of beer (0,5 lt.)
Megapolis Middle City
Age65605550454035302520
Opt
imal
Pric
e fo
r 1 b
ottle
of b
eer (
0,5
lt.)
9,49,2
98,88,68,48,2
87,87,67,47,2
76,86,66,46,2
6
Optimal price dependenсe from age
Smoothed regression lineRegression lineLower and upper borders of 95% error interval
Age
646260585654525048464442403836343230282624222018Opt
imal
Pric
e fo
r 1 b
ottle
of b
eer (
0,5
lt.)
8
7
Curve estimation
Smoothed series Cubic
Age65605550454035302520
Opt
imal
Pric
e fo
r 1 b
ottle
of b
eer (
0,5
lt.)
8
7
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Polar profiles graphPolar profiles graph
Comparison of various Comparison of various groups by preferences.groups by preferences.
Comparison of various Comparison of various brands by several brands by several parametersparameters
Definition of product Definition of product preferences or brand preferences or brand imageimage
Beer
Men Women
Str
ong
Lig
ht
Pre
serv
ativ
e
Pas
teur
ized
Ful
l
Bitt
er
With
Add
itive
s
Muc
h F
oam
Lage
r
Dar
k
Non
Pre
serv
ativ
e
Non
Pas
teur
ized
flavo
ured
-Fla
vour
less
Non
Bitt
er
No
Add
itive
s
Sm
al F
oam
1
0
-1
1
0
-1
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Demand CurveDemand Curve
Demand curve Demand curve calculation as an calculation as an interval between high interval between high and low price and low price preferences.preferences.
Optimal price interval Optimal price interval definitions using price definitions using price oriented variables. oriented variables.
Demand curve…
Prices, $
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
% s
ampl
e
95
90
85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
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Contact InformationContact Information::
Software Developer:Denis Shkurin, PhD in Sociology, Associate Professor of UrGU E-mail: [email protected]
XX
Software Distributor:SOCIS MR Russiahttp://socismr.comTel/Fax: +7 4852-73-92-37E-mail: [email protected]