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

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
4.2.3 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
5.2.3 Promax rotation.....................................................................................................................................28
6 Recommendation and Conclusions.....................................................................................................31

Indian Institute of Management, Bangalore 2|Page

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


• 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

Brand
S.No. Proposition/Positioning Advertising Imagery*
Name

Specific emphasis on school kids
.Mothers now have the freedom to
Stain Removal, Less Water, let their kids experience life without
Special offering for Washing worrying about stains. An
1 Surf Excel
Machine, Extra Bright Clothes. association with colour BLUE to
Middle and premium segment. imply a whitening characteristic,
though the new offerings have white
color detergent.


Middle class woman going to a bank
"Best clean with less effort", For
to send money order to his old
heavty duty laundry. Mass
2 Wheel father. Clear focus on savings.
market consumers.
Economy brand. Empowerment of
Lower & medium-price segment.
women.

Typical rainy season problems
Whiteness, Value proposition
associated with wearing white
when offering some smaller
clothes. Humorous ad. "White ho to
packs at Rs. 11/- motivating
Tide ho” is a nice way to rhyme the
intention to buy aspect, reaching
3 Tide word and make it easy to recall.
both lower & upper class
Trying to create transaction utility by
segment consumers through
crossing out 43 and promoting the
these introductory packings.
price as Rs. 23/- . Significantly above
For mid-priced segment
the JND.

Celebrity(Juhi Chawla) used along
with a person in a doctor's apprin -
Stain Removal, Oxygen power, shining WHITE. Use of oxygen
Kills germs. washing machine baloon to attract attention. Trying to
4 Henko
portay country of origin (Germany)
Middle and premium segment. to highlight quality, but not stated
that explicitly. Boring informational
ad.

Whiteness benefit. Lime and College going guy and housewife
indigo ingredient. Mass market emphasizing on whiteness of clothes
5 Mr White
consumers. Monotonous, Boring ad with not
Lower & medium-price segment. much audio video for quick recall.

The flash of light is synonymous with
the brand Rin The characters used in
Whiteness, Superior cleaning.
6 Rin a regular day to day environment so
Lower price segment
that people can relate with them,
middle class environment


Stain removal, fragrance, washing Technology focus. Packaging with
7 Ariel machine. Medium and premium celebrity – Zaheer khan. No audio
segment. oxygen-oxyblue, oxyrich video repetition, jingle etc.

"Washing powder Nirma" a popular
jingle etched in consumer's mind.
Whiteness. Lower price
Dancing girl imagery. Same audio /
8 Nirma segment.No special benefits of
visual identity since many years.
the powder mentioned.
Good brand recall. "sabki pasand
nirma"- mass market appeal.


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.


Correlation Matrix

Washing Gentle
Wash Machine on Brand
Quality Fragrance Packaging Appropriateness hands Recall Price
Correlation 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 0.693 0.681 0.631 1 0.591 0.467 0.651
Machine
Appropriateness

Gentle on 0.589 0.612 0.521 0.591 1 0.427 0.445
hands
Brand Recall 0.595 0.481 0.497 0.467 0.427 1 0.335

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 .908
of Sampling Adequacy.

Bartlett's Test of Sphericity Approx. Chi-Square 1549.372

df 21

Sig. .000

KMO value of 0.908 indicates suitability of factor analysis. Bartlett’s test is also significant.


4.1 Two Factor Solution:

Communalities

Extraction

Wash Quality .739

Fragrance .689

Packaging .586

Washing Machine .793
Appropriateness

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.


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


In fact the second factor explains only 3.772% of the variance.

Indian Institute of Management, Bangalore 10 | 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


4.1.2 Varimax rotation

Factor 1 Factor 2
Fragrance .671 .488
Packaging .610 .462
Washing Machine Appropriateness .473 .755
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.


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.


4.1.3 Promax rotation (allow the factors to be correlated)

Pattern Matrix

Factor 1 Factor 2


Fragrance .638 .223

Packaging .567 .230



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 correlated

• As discussed earlier, a 3-Factor solution might be more appropriate


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

Appropriateness


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.


Total % of Variance Cumulative %

4.056 57.945 57.945

.366 5.234 63.179

.262 3.742 66.921


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 .842 -.083 .300
Appropriateness
Gentle on hands .696 -.014 .009
Brand Recall .631 .552 -.061
Price .647 -.098 .325
Three Factor Analysis with No Rotation



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

Factor-1: Price, Washing machine appropriateness
Factor-2: Wash Quality, Packaging, Gentle to hand
Factor-3: Brand Recall

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.

Basic Features

Washing Machine
Appropriateness (Premium-ness)


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.

Brand

Recall

Washing Machine Appropriateness
(Premium-ness)

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>

Brand

Recall

Basic Features
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.





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


The rotation spreads the variance across these factors which might make the perceptual map more relevant.


4.2.3 Promax rotation


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.



Fragrance -.059 1.046 -.095

Packaging .235 .435 .151

Washing Machine .837 .085 -.016
Appropriateness


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.


Factor-1: Washing Machine Appropriateness (and/or price)
(Premium-ness)

Factor-2: Fragrance

Factor-3: Brand Recall

4.2.3.1 Perceptual Map- Three factor promax rotation
The axes are shown orthogonal just for the sake of representation


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.


5 Analysis with Surf Excel, Ariel and Henko
Correlation Matrix

Washing Gentle
Wash Machine on Brand
Quality Fragrance Packaging Appropriateness hands 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 0.666 0.608 0.603 1 0.492 0.631 0.483
Machine
Appropriateness

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).


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 .891
of Sampling Adequacy.

Bartlett's Test of Sphericity Approx. Chi-Square 936.039

df 21

Sig. .000

KMO value of 0.891 indicates suitability of factor analysis. Bartlett’s test is also significant.


5.1 Two Factor Solution:

Communalities

Extraction

Wash Quality .737

Fragrance .881

Packaging .610

Appropriateness


Brand Recall .804

Price .390

As can be seen in the communalities output, the “Gentle on Hands” and “Price” attributes are not explained
significantly


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.


Factor 1 Factor 2

Fragrance .854 -.390

Packaging .771 .124




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

Appropriateness


Brand Recall .776

Price .514

All the variables have more than 50% of their variance explained which can be termed satisfactory.


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.


Fragrance .999 -.005 .000

Packaging .621 .472 -.124

Washing Machine .611 .458 -.013
Appropriateness


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.




Fragrance .267 .355 .895

Packaging .605 .346 .373

Washing Machine .527 .425 .353
Appropriateness



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.
Factor-1: Price, brand recall, packaging
Factor-2: Gentle on hands, brand recall, wash quality
Factor-3: Fragrance



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”


5.2.3 Promax rotation

Pattern Matrix

The significant factors have been highlighted.



Fragrance -.028 .030 .995

Packaging .589 .062 .207

Washing Machine .420 .254 .163
Appropriateness

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 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


5.2.3.1 Perceptual Map- Three factor promax rotation

The axes are shown orthogonal just for the sake of representation


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.


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