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Transcript of Analytical Marketing Report
Henko Brand
Positioning in
Detergent Industry Factor Analysis Approach
Analytical Marketing
Under guidance of
Prof. Srinivas Prakhya
Prepared by:
Dharmesh Gandhi
Alok Shukla
Kaveri Ingale
Kumar Ashutosh
Venkata Phani Prasad Chavali
Apurva Pushpen Thanawala
Indian Institute of Management, Bangalore 2 | P a g e
Contents
1 Introduction...........................................................................................................................................3
2 Approach ...............................................................................................................................................3
3 Qualitative Analysis ...............................................................................................................................4
4 Analysis for detergent brands ...............................................................................................................7
4.1 Two Factor Solution: ....................................................................................................................................9
4.1.1 No rotation ............................................................................................................................................11
4.1.2 Varimax rotation....................................................................................................................................12
4.1.3 Promax rotation (allow the factors to be correlated) ...........................................................................13
4.2 Three Factor Solution: ...............................................................................................................................14
4.2.1 No rotation ............................................................................................................................................15
4.2.2 Varimax rotation....................................................................................................................................16
4.2.3 Promax rotation.....................................................................................................................................19
5 Analysis with Surf Excel, Ariel and Henko ...........................................................................................22
5.1 Two Factor Solution: ..................................................................................................................................24
5.2 Three Factor Solution: ...............................................................................................................................25
5.2.1 No rotation ............................................................................................................................................26
5.2.2 Varimax rotation....................................................................................................................................27
5.2.3 Promax rotation.....................................................................................................................................28
6 Recommendation and Conclusions.....................................................................................................31
Indian Institute of Management, Bangalore 3 | P a g e
1 Introduction
The case we have taken here is of the detergent industry. The motive was to select a brand that has not been
doing well and do a repositioning exercise. From the newspapers sources, we found that approximately share
for the HUL’s ‘Surf Excel’ is 14%, P&G’s Ariel is 3% and Henkel’s Henko is 1%. Considering the fact that Henkel is
operating in India since early 90s, and still has not make any significant progress in terms market share, we
selected this brand for repositioning.
The idea is to find out the core factors driving the consumer choice. The approach was to do a dip stick survey
to find out the observable attributes that are important to the consumer (decision maker). From this we try to
find the unobservable latent factors that are driving these attributes. Then we map the chosen brands on these
factors to get a perceptual map.
We also reduce the consideration set to just the competing brands of Henko to see if the results make more
sense. This perceptual map is then used to get an insight of where these different brands figure in the minds of
the consumer. Hopefully, then it can become very clear where Henko is going wrong and an approach to correct
that can be figured out.
2 Approach
Firstly, we do a qualitative analysis to get a feel of the situation on the ground. To do that we analyze the
advertisements for the different brands in the industry and try to understand what the brand managers are trying
to portray and what is the positioning stance taken by the different brands.
To be able to figure out the factors, we needed to have data at our disposal which would quantify the various
perceptions of different users of detergents.
To design our survey attributes, we first went ahead with a dip stick survey to understand the various factors that
are considered by a consumer while buying his/her choice of detergent powder.
The factors thus distilled out of the dip-stick survey were as follows.
• Wash Quality
• Price
• Fragrance
• Packaging
• Appropriateness for washing machine
• Brand Recall
Indian Institute of Management, Bangalore 4 | P a g e
• Gentle on Hands
We gave equal weight age to these attributes. Probably, the weight ages of these attributes would be different in
a consumer’s mind. However, we shall start with this and see whether the results are intuitive enough.
Once these variables were decided, the next task was to define the questionnaire. The idea of the end result of the
survey was to be able to create a perception map of the brands in question and figure where Henko figures among
those.
To meet the goal we decided to pick up well known brands (along with Henko) to figure in our questionnaire. The
brands thus picked up were – Surf Excel, Ariel, Rin and Nirma.
Sample set of questions (that were put for each of these brands) is as follows.
• How would you rate the "wash quality" of Surf Excel?
• How do you rate the fragrance of Surf Excel?
• How attractive is the packaging of Surf Excel?
• Do you think Surf Excel is appropriate for a washing machine?
• Do you think that Surf Excel is gentle on your hands?
• How do you rate the brand recall of Surf Excel?
The survey was a web survey and was floated to decision makers mainly in the IT segment. We got around 80
responses which we used for the analysis.
3 Qualitative Analysis
Brand Positioning and Imagery – as conveyed through the advertisements
S.No. Brand
Name Proposition/Positioning Advertising Imagery*
1 Surf Excel
Stain Removal, Less Water,
Special offering for Washing
Machine, Extra Bright Clothes.
Middle and premium segment.
Specific emphasis on school kids
.Mothers now have the freedom to
let their kids experience life without
worrying about stains. An
association with colour BLUE to
imply a whitening characteristic,
though the new offerings have white
color detergent.
Indian Institute of Management, Bangalore 5 | P a g e
2 Wheel
"Best clean with less effort", For
heavty duty laundry. Mass
market consumers.
Lower & medium-price segment.
Middle class woman going to a bank
to send money order to his old
father. Clear focus on savings.
Economy brand. Empowerment of
women.
3 Tide
Whiteness, Value proposition
when offering some smaller
packs at Rs. 11/- motivating
intention to buy aspect, reaching
both lower & upper class
segment consumers through
these introductory packings.
For mid-priced segment
Typical rainy season problems
associated with wearing white
clothes. Humorous ad. "White ho to
Tide ho” is a nice way to rhyme the
word and make it easy to recall.
Trying to create transaction utility by
crossing out 43 and promoting the
price as Rs. 23/- . Significantly above
the JND.
4 Henko
Stain Removal, Oxygen power,
Kills germs. washing machine
Middle and premium segment.
Celebrity(Juhi Chawla) used along
with a person in a doctor's apprin -
shining WHITE. Use of oxygen
baloon to attract attention. Trying to
portay country of origin (Germany)
to highlight quality, but not stated
that explicitly. Boring informational
ad.
5 Mr White
Whiteness benefit. Lime and
indigo ingredient. Mass market
consumers.
Lower & medium-price segment.
College going guy and housewife
emphasizing on whiteness of clothes
Monotonous, Boring ad with not
much audio video for quick recall.
6 Rin Whiteness, Superior cleaning.
Lower price segment
The flash of light is synonymous with
the brand Rin The characters used in
a regular day to day environment so
that people can relate with them,
middle class environment
Indian Institute of Management, Bangalore 6 | P a g e
7 Ariel
Stain removal, fragrance, washing
machine. Medium and premium
segment. oxygen-oxyblue, oxyrich
Technology focus. Packaging with
celebrity – Zaheer khan. No audio
video repetition, jingle etc.
8 Nirma
Whiteness. Lower price
segment.No special benefits of
the powder mentioned.
"Washing powder Nirma" a popular
jingle etched in consumer's mind.
Dancing girl imagery. Same audio /
visual identity since many years.
Good brand recall. "sabki pasand
nirma"- mass market appeal.
Indian Institute of Management, Bangalore 7 | P a g e
4 Analysis for detergent brands
The analysis of the detergent survey data is done for finding the factors and their loading. We started with two
factor analysis on the given set of data. The brands in consideration are Surf Excel, Henko, Rin, Ariel and Nirma.
The scree plot indicates the fact that most of the variance is explained by the first factor.
Indian Institute of Management, Bangalore 8 | P a g e
Correlation Matrix
Wash Quality Fragrance Packaging
Washing Machine
Appropriateness
Gentle on
hands Brand Recall Price
Wash Quality 1 0.708 0.631 0.693 0.589 0.595 0.526
Fragrance 0.708 1 0.672 0.681 0.612 0.481 0.506
Packaging 0.631 0.672 1 0.631 0.521 0.497 0.497
Washing Machine Appropriateness
0.693 0.681 0.631 1 0.591 0.467 0.651
Gentle on hands
0.589 0.612 0.521 0.591 1 0.427 0.445
Brand Recall 0.595 0.481 0.497 0.467 0.427 1 0.335
Correlation
Price 0.526 0.506 0.497 0.651 0.445 0.335 1
There is a significant amount of correlation across the factors underscoring the usefulness of factor analysis. (They
have to be correlated if they are representing the same underlying set of latent variables).
Determinant=.02 => there is no singularity in the data.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure
of Sampling Adequacy.
.908
Approx. Chi-Square 1549.372
df 21
Bartlett's Test of Sphericity
Sig. .000
KMO value of 0.908 indicates suitability of factor analysis. Bartlett’s test is also significant.
Indian Institute of Management, Bangalore 9 | P a g e
4.1 Two Factor Solution:
Communalities
Extraction
Wash Quality .739
Fragrance .689
Packaging .586
Washing Machine
Appropriateness
.793
Gentle on hands .491
Brand Recall .445
Price .544
Extraction Method: Maximum Likelihood.
However if we see the communalities matrix, the “Gentle on hands” and “Brand Recall” attributes have less than
50% of their variance explained. Even “price” and “packaging” have very less variance explained by the 2 factors.
Hence we might need to move onto 3 factors because of this significant data loss.
Indian Institute of Management, Bangalore 10 | P a g e
Total Variance Explained
Extraction Sums of Squared Loadings
Factor Total % of Variance Cumulative %
1 4.023 57.478 57.478
2 .264 3.772 61.250
Extraction Method: Maximum Likelihood.
In fact the second factor explains only 3.772% of the variance.
Indian Institute of Management, Bangalore 11 | P a g e
4.1.1 No rotation
The factor loadings for two factor analysis shows that the first factor describes all the variables and the second
factor does not give any specific information about the loadings of the attributes.
Factor 1 Factor 2
Wash Quality .842 .171
Fragrance .823 .107
Packaging .761 .085
Washing Machine Appropriateness .862 -.223
Gentle on hands .699 .056
Brand Recall .609 .273
Price .675 -.298
2 Factor No Rotation
Indian Institute of Management, Bangalore 12 | P a g e
4.1.2 Varimax rotation
Factor 1 Factor 2
Wash Quality .729 .455
Fragrance .671 .488
Packaging .610 .462
Washing Machine Appropriateness .473 .755
Gentle on hands .545 .440
Brand Recall .630 .221
Price .285 .681
2 Factor Varimax Rotation
Varimax rotation provides two factors which explain two choices. First factor explains the brand, wash quality,
packaging etc. The second factor explains washing machine appropriateness and price.
Total Variance Explained
Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Factor Total % of Variance Cumulative % Total % of Variance Cumulative %
1 4.023 57.478 57.478 2.353 33.620 33.620
2 .264 3.772 61.250 1.934 27.630 61.250
Here, the variance is distributed across the 2 factors in a much more even manner and a perceptual map makes
more sense here.
Indian Institute of Management, Bangalore 13 | P a g e
4.1.3 Promax rotation (allow the factors to be correlated)
Pattern Matrix
Factor 1 Factor 2
Wash Quality .752 .128
Fragrance .638 .223
Packaging .567 .230
Washing Machine Appropriateness .129 .783
Gentle on hands .485 .248
Brand Recall .784 -.151
Price -.099 .816
2 Factor Promax Rotation
Factor Correlation Matrix
Factor 1 2
1 1.000 .811
2 .811 1.000
Here you can see that the factors are highly correl ated
• As discussed earlier, a 3-Factor solution might be more appropriate
Indian Institute of Management, Bangalore 14 | P a g e
4.2 Three Factor Solution:
Objective: We further tried to go for three factor solution to see if it provides additional information on the
detergent attributes.
Communalities
Extraction
Wash Quality .708
Fragrance .867
Packaging .580
Washing Machine
Appropriateness
.805
Gentle on hands .485
Brand Recall .707
Price .534
The communalities show a better result compared to the 2 factor solution. However the “Gentle on Hands” is
still not adequately explained.
Extraction Sums of Squared Loadings
Total % of Variance Cumulative %
4.056 57.945 57.945
.366 5.234 63.179
.262 3.742 66.921
Indian Institute of Management, Bangalore 15 | P a g e
The 3 factor solution explains around 5% more variance than the 2 factor solution and the communalities also
suggest a better explanation of the attributes.
4.2.1 No rotation
The factor loadings for three factor analysis for all the five products shows that the first factor describes all the
variables and the second & third factor does not give a lot of information about the loadings of attributes.
Factor 1 Factor 2 Factor 3
Wash Quality .831 .130 .012
Fragrance .882 -.165 -.248
Packaging .761 .023 -.014
Washing Machine
Appropriateness
.842 -.083 .300
Gentle on hands .696 -.014 .009
Brand Recall .631 .552 -.061
Price .647 -.098 .325
Three Factor Analysis with No Rotation
Indian Institute of Management, Bangalore 16 | P a g e
4.2.2 Varimax rotation
Factor 1 Factor 2 Factor 3
Wash Quality .481 .488 .488
Fragrance .380 .805 .273
Packaging .443 .500 .364
Washing Machine Appropriateness .756 .395 .279
Gentle on hands .430 .458 .300
Brand Recall .208 .235 .780
Price .661 .257 .175
Three Factor Analysis with Varimax Rotation
4.2.2.1 Perceptual Map – Three factor Varimax Rotation
Three-factor perceptual map has been broken into three two-dimensional perceptual map for better
understanding. The three maps are drawn against three factor solutions achieved in the previous section.
Factor-1: Price, Washing machine appropriateness
Factor-2: Wash Quality, Packaging, Gentle to hand
Factor-3: Brand Recall
Washing Machine
Appropriateness (Premium-ness)
Basic Features
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The first perceptual map shows that Henko is placed poorly with factor 2, which means wash quality and
packaging is not so good. Also it is not perceived as gentle to hand. It scores positive on the washing machine
appropriateness and price, but again it scores low with respect to other brands.
Henko is having a very poor brand recall; in fact it is having the lowest brand recall in the five brands studied. Surf
scores the highest and Nirma is the only other brand which is having negative score in brand recall. <Please explain
further>
This perceptual map shows brand positions with respect to Factor-2 and Factor-3. Henko is very poorly placed if
these two factors are considered.
Washing Machine Appropriateness
(Premium-ness)
Brand
Recall
Basic Features
Brand
Recall
Indian Institute of Management, Bangalore 18 | P a g e
Total Variance Explained
Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Factor Total % of Variance Cumulative % Total % of Variance Cumulative %
1 4.056 57.945 57.945 1.810 25.856 25.856
2 .366 5.234 63.179 1.622 23.169 49.024
3 .262 3.742 66.921 1.253 17.897 66.921
Extraction Method: Maximum Likelihood.
The rotation spreads the variance across these factors which might make the perceptual map more relevant.
Indian Institute of Management, Bangalore 19 | P a g e
4.2.3 Promax rotation
Factor Correlation Matrix
Factor 1 2 3
1 1.000 .818 .681
2 .818 1.000 .730
3 .681 .730 1.000
• There is a high degree of correlation amongst these factors as expected.
The significant factors have been highlighted.
Factor 1 Factor 2 Factor 3
Wash Quality .269 .337 .318
Fragrance -.059 1.046 -.095
Packaging .235 .435 .151
Washing Machine
Appropriateness
.837 .085 -.016
Gentle on hands .264 .396 .084
Brand Recall -.070 -.051 .922
Price .817 -.051 -.070
Three Factor Analysis with Promax Rotation
• The 3 factor promax solution has the cleanest output.
• The factor 1 is the clearly the washing machine appropriateness factor which commands a premium in the
market probably because of the target segment differentiation.
Indian Institute of Management, Bangalore 20 | P a g e
4.2.3.1 Perceptual Map- Three factor promax rotation
The axes are shown orthogonal just for the sake of representation
Factor-1: Washing Machine Appropriateness (and/or price)
(Premium-ness)
Factor-2: Fragrance
Factor-3: Brand Recall
Indian Institute of Management, Bangalore 21 | P a g e
The analysis till now has been over the five brands that have been assumed to constitute the industry.
However, Henko effectively competes only with Surf Excel and Ariel. So it might make sense to only look at the
data for Surf Excel, Henko and Ariel.
Indian Institute of Management, Bangalore 22 | P a g e
5 Analysis with Surf Excel, Ariel and Henko
Correlation Matrix
Wash Quality Fragrance Packaging
Washing Machine
Appropriateness
Gentle on
hands Brand Recall Price
Wash Quality 1 0.653 0.623 0.666 0.578 0.753 0.511
Fragrance 0.653 1 0.618 0.608 0.535 0.547 0.343 Packaging 0.623 0.618 1 0.603 0.459 0.69 0.504
Washing Machine Appropriateness
0.666 0.608 0.603 1 0.492 0.631 0.483
Gentle on hands 0.578 0.535 0.459 0.492 1 0.523 0.235
Brand Recall 0.753 0.547 0.69 0.631 0.523 1 0.544
Price 0.511 0.343 0.504 0.483 0.235 0.544 1
There is a significant amount of correlation across the factors underscoring the usefulness of factor analysis.
(They have to be correlated if they are representing the same underlying set of latent variables).
Indian Institute of Management, Bangalore 23 | P a g e
As was the case with the all-brands case, most of the variance can be explained by one factor itself.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure
of Sampling Adequacy.
.891
Approx. Chi-Square 936.039
df 21
Bartlett's Test of Sphericity
Sig. .000
KMO value of 0.891 indicates suitability of factor analysis. Bartlett’s test is also significant.
Indian Institute of Management, Bangalore 24 | P a g e
5.1 Two Factor Solution:
Communalities
Extraction
Wash Quality .737
Fragrance .881
Packaging .610
Washing Machine
Appropriateness
.583
Gentle on hands .402
Brand Recall .804
Price .390
As can be seen in the communalities output, the “Gentle on Hands” and “Price” attributes are not explained
significantly
Extraction Sums of Squared Loadings
Factor Total % of Variance Cumulative %
1 3.964 56.629 56.629
2 .441 6.305 62.934
The 2 factors explain around 63% of the variance which is about the same as when compared with the all
brands case.
The factor loadings for two factor analysis shows that the first factor describes all the variables and the second
factor does not give any specific information about the loadings of the attributes.
Indian Institute of Management, Bangalore 25 | P a g e
Factor 1 Factor 2
Wash Quality .842 .168
Fragrance .854 -.390
Packaging .771 .124
Washing Machine Appropriateness .758 .094
Gentle on hands .633 .001
Brand Recall .814 .376
Price .543 .309
2 Factor No Rotation
So looking at the above scenario, it makes sense to look at the 3 factor solution.
5.2 Three Factor Solution:
Objective: We further tried to go for three factor solution to see if it provides additional information on the
detergent attributes.
Communalities
Extraction
Wash Quality .755
Fragrance .999
Packaging .624
Washing Machine
Appropriateness
.583
Gentle on hands .549
Brand Recall .776
Price .514
All the variables have more than 50% of their variance explained which can be termed satisfactory.
Indian Institute of Management, Bangalore 26 | P a g e
5.2.1 No rotation
The factor loadings for three factor analysis shows that the first factor is strongly loaded with most of the variables
but mostly with fragrance, wash quality and packaging. The second factor is strongly loaded with brand recall ,
wash quality and price. The 3rd
factor has relatively weaker factor loadings.
Factor 1 Factor 2 Factor 3
Wash Quality .656 .560 .101
Fragrance .999 -.005 .000
Packaging .621 .472 -.124
Washing Machine
Appropriateness
.611 .458 -.013
Gentle on hands .537 .337 .383
Brand Recall .551 .687 .003
Price .346 .537 -.324
Three Factor Analysis with No Rotation
So this makes a strong case for rotating the solution and getting a cleaner solution that is more intuitive.
Indian Institute of Management, Bangalore 27 | P a g e
5.2.2 Varimax rotation
Factor 1 Factor 2 Factor 3
Wash Quality .552 .582 .333
Fragrance .267 .355 .895
Packaging .605 .346 .373
Washing Machine
Appropriateness
.527 .425 .353
Gentle on hands .186 .660 .280
Brand Recall .679 .525 .201
Price .695 .117 .130
Three Factor Analysis with Varimax Rotation
In contrast with the all brands case, the washing machine appropriateness is not that strong an attribute in driving
the factor loadings.
Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Factor Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2.900 41.430 41.430 1.998 28.540 28.540
2 1.622 23.172 64.602 1.491 21.294 49.834
3 .278 3.968 68.570 1.312 18.736 68.570
Around 6% more variance is explained by a 3 factor solution compared to a 2 factor solution. The variance is
much more “equitably distributed”
Factor-1: Price, brand recall, packaging
Factor-2: Gentle on hands, brand recall, wash quality
Factor-3: Fragrance
Indian Institute of Management, Bangalore 28 | P a g e
5.2.3 Promax rotation
Pattern Matrix
The significant factors have been highlighted.
Factor 1 Factor 2 Factor 3
Wash Quality .351 .519 .058
Fragrance -.028 .030 .995
Packaging .589 .062 .207
Washing Machine
Appropriateness
.420 .254 .163
Gentle on hands -.244 .895 .036
Brand Recall .607 .409 -.127
Price .935 -.270 -.041
Three Factor Analysis with Promax Rotation
As can be seen from the above factor loadings, the promax gives the cleanest solution which is expected given the
extent of correlation amongst the factors.
Factor Correlation Matrix
Factor 1 2 3
1 1.000 .798 .628
2 .798 1.000 .722
3 .628 .722 1.000
Factor-1: Price, brand recall
Factor-2: Gentle on hands, wash quality
Factor-3: Fragrance
Indian Institute of Management, Bangalore 29 | P a g e
Indian Institute of Management, Bangalore 30 | P a g e
5.2.3.1 Perceptual Map- Three factor promax rotation
The axes are shown orthogonal just for the sake of representation
Indian Institute of Management, Bangalore 31 | P a g e
6 Recommendation and Conclusions
It is very clear where Henko is lagging. It does not have the brand strength to compete with either Surf Excel or
Ariel in its category. It is interesting to note that as soon as we remove the brands Nirma and Rin, the washing
machine appropriateness as a driving factor is no longer there. Probably, that is what defines this particular
segment.
So, the obvious thing as expected would be to build its brand through better advertising, marketing reach and
channel reach to reach its target segment.