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Why do people watch Reality TV???

A case study cum Term Paper

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Industry Perspective of Reality TVShows

In India, reality shows can be categorized as follows:

Reality shows inIndia

Planned category

Ex: Big Boss,

Sach ka samna

Scripted category

Ex: Date Trap,Emotional Atyachar

Planned Category shows:

Shows which are taken from theconcepts originated abroad Only framework provided by thecreative heads of the channels,

Scripted category shows:

Shows may or may not beoriginated in IndiaFramework and the script bothare provided by the creativeheads of the channels

Creators Mind : Reality shows in India run by tickling human emotion in India ( ex: physicallychallenged, tough childhood/livelihood, financial )Every reality show, tries to weave a story around every contestantMapping of the story to sell, talent and revenue contributed by the contestant

Every channel while designing a show must follow certain set of guidelines

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Objectives of the study

To find out the factors responsible forpreference to Reality TV

To probe and identify possible

consumer segments

Tools used Factor Analysis Cluster Analysis

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What is Factor Analysis (FA)?

FA and PCA (principal components analysis) are methods of datareduction

Take many variables and explain them with a few factors or components

Correlated variables are grouped together and separated from othervariables with low or no correlation

Patterns of correlations are identified and either used as descriptive(PCA) or as indicative of underlying theory (FA)

Process of providing an operational definition for latent construct(through regression equation)

FA and PCA are not much different than canonical correlation in termsof generating canonical variates from linear combinations of variables

Although there are now no sides of the equation

And your not necessarily correlating the factors, components, variates,etc.

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General Steps to FA

Step 1: Selecting and Measuring a set ofvariables in a given domain

Step 2: Data screening in order to prepare thecorrelation matrix

Step 3: Factor Extraction

Step 4: Factor Rotation to increase

interpretability

Step 5: Interpretation

Further Steps: Validation and Reliability of the

measures

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MEANING AND DEFINITION OFCLUSTER ANALYSIS

6

Exploratory data analysis tool for solving classificationproblems.

A cluster is a group of relatively homogenous cases orobservations.

Applied to data that have been recorded on interval scalessuch as 5-, 7-, or 10- point scales, but it can also be appliedto continuous variable data.

Cluster analysis identifies interdependencies amongvariables.

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Importance of cluster analysis

7

Describe a sample in terms of a typology.

Predict the future behavior of population types.

Optimize functional processes.

Formulate hypothesis concerning the origin of the sample.

Assist in identification.

Measure the different effects of treatments on classes within the population.

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Cluster analysis is usedfor..1. Segmenting the market and determining

the target markets.

2. Product positioning and new productdevelopment.

3. Selecting test markets.

8

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Methodology

To find out the reasons behindpeoples increasing preference or thepopularity of the Reality TV shows,

focus group discussions were carriedout

3 FGD each lasting for 30 minutes in agroup of 4 were arranged

Secondary research was done to findout reasons behind this phenomenon

Ultimately a list of 15 variables was

finalised

C i S li d

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Sampling Plan Convenient Sampling was done.

Sample size 159

Likert 5 point scale was used

Males61%

Females

39%

Distribution of

respondents by Gender

28%

64%

5% 2% 1%

Distribution of respondents

by age15-24

24-31

31-41

41-51

50+

20 24

71

31

4 3 1 2 1 1

male female male female male female male female male female

15-23 24-30 31- 40 41-50 50+

0

10

20

30

40

50

60

70

80

Demographics of Suvey

Number

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Results and Analysis

MS Excel was used for data recording

SPSS was used for providing results

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Testing the appropriateness of thefactor model

For factor analysis, the variables must becorrelated and if the correlations between thevariables are small, the factor analysis maynot be appropriate.

Bartletts Test ofSphericity H0 : Variables are uncorrelated in the population

Or

H0 : Population Correlation matrix is [I]

KMO test is another test statistic to judgewhether factor analysis is able to analyse thecorrelations taking place between thevariables

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KMO measure should be more than 0.5 and so the

results indicate that the it is a good model

Bartletts test is able to reject the null hypothesis that

the variables are uncorrelated with 99.9% confidence

level

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Method of Factor Analysis

Principal Component analysis has beenused as the focus is on finding theminimum number of factors that will

account for maximum variance in thedata. These factors are the principalcomponents.

Only those factors with Eigen valuesmore than 1 are retained.

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Four factors have been extracted based onEigen Values. Together they account for

61.594% of the variance

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Unrotated Factor Matrix

These coefficientsrepresentcorrelations betweenfactor and variables.

Larger the absolutevalue more is thecorrelation.

These can be usedto interpret thefactors

However, a betterinterpretation resultsby rotation

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Rotation

It doesnt affect the communalities and

percentage of total variance explained

But the percentage of total varianceaccounted for by the factor changes(Slide 6)

Varimax procedure has been used

It enhances the interpretability of thefactor in terms of the variables

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Rotated Factor Matrix

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Interpretation of Factors

Identifying the variables that havelarge loadings on a same factor

If a variable has a loading of >= 0.6 on

a particular factor, then that variableforms a part of that factor

Hence, the factors can be interpreted.

G i f V i bl F

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Grouping of Variables -> FactorsVar Variable name Factor 1 Factor 2 Factor 3 Factor 4

VAR00001 Special and unusual acts performed byparticipants

X

VAR00002 A platform to see talent XVAR00003 Just to be informed of whats happening around X

VAR00004 The people are not the real stars but if they cando it, even I can

X

VAR00005 We get attached to the emotions of these peopleas they are like ourselves

X

VAR00006 Helps to understand human mind andpsychology of people

VAR00007 Watching them getting rejected, we feel a senseof satisfaction.

X

VAR00008 Increases my intelligence X

VAR00009 To get sexual satisfaction /physical enjoyment X

VAR00010 Sense of competition XVAR00011 l like the judges X

VAR00012 People plotting against each other X

VAR00013 Family drama/ wholse some entertainment

VAR00014 teaches me how to handle success and failure in

life XVAR00015 I like a particular participant X

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Interpretation

The number of variables have beenreduced from 15 to 4 underlying factors.

Factor 1

Sense of competition Likeness for the judges

People plotting against each other

Teaches how to handle success and failure in

life Likeness for a particular participant

Therefore this factor can be interpreted as

Format of the show

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Factor 2

The people are not the real stars but if theycan do it, even I can

We get attached to the emotions of thesepeople as they are like ourselves

Watching them getting rejected, we feel asense of satisfaction.

Increases the intelligence

Therefore this factor can be interpreted asSelf- Relatedness

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Factor 3

Special and unusual acts performed by

participants A platform to see talent

Just to be informed of whats happening

around

Therefore this factor can be interpreted asEntertainment

Factor 4

To get sexual satisfaction /physical enjoyment

Therefore this factor can be interpreted asPhysical Stimulus

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Factor scores

Still to be done

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Cluster Anlaysis

To map the consumers/ audience indistinct segments, the same data wasanalysed using Cluster analysis

Likert scale used could be reproducedas:-

1-strong disagreement

2-disagreement

3-neutral

4-agreement

5-strong disagreement

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The analysis of output

1st stage Hierarchical ClusterAnalysis

2nd stage K-means (Quick Cluster)with a predetermined number of

clusters specified.

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Agglomeration schedule

MR\reality tv\results hierarch cluster.xls

This agglomeration schedule is as per

Hierarchical AnalysisDecision of number of clusters is to be

made.

Range selected is 2-5

http://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xlshttp://mr/reality%20tv/results%20hierarch%20cluster.xls

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Number of Clusters

Using high relative difference as thecriteria, no of clusters = 2

Also going by the dendogram, two

clusters are being observed Going by the frequency of the clusters

appearing against the cases in

membership table MR\reality tv\resultshierarch cluster membership.xls

(contd. On next slide)

http://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20membership.xls

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Number of Clusters.

Numberofclusters

Membersof Cluster1

Membersof Cluster2

Membersof Cluster3

Membersof Cluster4

Membersof Cluster5

5 19 63 25 23 9

4 44 74 23 18

3 62 74 23

2 64 95

Thus number of clusters should be either 2or 3 as the number of members need to besignificant in each cluster.

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K means ( Quick Cluster)

For 4 cluster solution

For 3 cluster solution

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Cluster Interpretations

MR\reality tv\results hierarch cluster final clustercentres.xls Cluster 1 consists of people

Neutral towards activities performed by participantson shows and the talent that is shown

They disagree with watching these shows just toknow whats happening around and do not getattached to the emotions of the people

They do not feel that these shows add to theirintelligence

They really do not feel any sense of satisfaction uponseeing the rejections in these shows and also do notexperience any physical pleasure

They are neutral to the idea of putting themselves intothe shoes of participants and the idea that theseshows helps them to understand human psychology.

http://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xlshttp://mr/reality%20tv/results%20hierarch%20cluster%20final%20cluster%20centres.xls