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


4.2.3 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


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

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.


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


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.


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

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.


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.


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.


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 correl ated

• 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

Washing Machine

Appropriateness

.805


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

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





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


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.


(Premium-ness)

Brand

Recall

Basic Features

Brand

Recall





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

Appropriateness

.837 .085 -.016


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.


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


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

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


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).


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.


5.1 Two Factor Solution:

Communalities

Extraction

Wash Quality .737

Fragrance .881

Packaging .610

Washing Machine

Appropriateness

.583


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

Washing Machine

Appropriateness

.583


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

Appropriateness

.611 .458 -.013



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

Appropriateness

.527 .425 .353



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.



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


5.2.3 Promax rotation

Pattern Matrix

The significant factors have been highlighted.



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 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.

analytical marketing report

Documents

representation

dip stick

washing machine

factor analysis

factor promax

wash quality

perceptual

1 perceptual