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Factors affecting the consumer purchase for Private Label Apparel Brands in India
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Transcript of Factors affecting the consumer purchase for Private Label Apparel Brands in India
STUDYING THE FACTORS AFFECTING CONSUMER PURCHASE DECISIONS
FOR PRIVATE LABEL APPAREL BRANDS
Prepared & Presented By,Group No-01
Strong growth in the Indian Retail Industry
• The retail sector in India is emerging as one of the largest sectors in the economy• By 2015, the total market size is estimated to be around US$ 600 billion, thereby registering a CAGR of 7.45 per cent since 2000.• Retail industry is expected to grow to US$ 1.3 trillion by 2020, registering a CAGR of 9.7 per cent between 2000-2020
Organised retail in nascent stage
• The Indian retail market is in its nascent stage; unorganised players accounted for 92 per cent of the market during 2015• There are over 15 million mom-and-pop stores• Compound Annual Growth Rate (CAGR) of 16.7 per cent over 2015-20. • Organised retail is expected to account for 24 per cent of the overall retail market by 2020
Private Label Products are commonly referred to as name brand, store brand, own label, retailer brand or generics. These are brands
owned by the retailer rather than the producer or manufacturer.
Apparel Sector, it is the second largest segment in terms of its contribution to the retail market.
The overall size of the textile and apparel industry in India is currently estimated at $70bn and is expected to grow to $220bn by 2020 with a CAGR of 11%.
Currently, menswear is the biggest segment of the domestic apparel market with 43% share of the total pie while women’s wear constitutes 38%.
The private label market in India is currently estimated at
INR13 billion, which accounts for 10-12% of organised
retail in India. Retailers such as Pantaloon, Trent, Shoppers
Stop and Spencer’s have increased focus on private label
retailing. Private labels constitute 90% of Trent’s, 80% of
Reliance’s and 75% of Pantaloon’s overall sales.
Challenges Faced by Private Label Brand Apparels
The biggest challenge in building a private label brand is to establish credibility and aspiration for the brand. When consumers buy a brand,
they are aware about their expectations, but when they buy a new label they are bound to be a quite a few ‘doubters’.
Most consumers see private label apparel as ‘undifferentiated’. Private label are more popular among lower-income household as well
as larger families owning to the need to economize.
Some Challenges faced by Private Labels Apparel are as follows:• Higher risk of inventory.• Higher expense in Research and Development.• Markdown or return allowances will not be available.• Failure of the product will create a negative image about the
retailer.• More marketing expenses
Objectives of the Study
The Indian apparel industry in retail is growing rapidly, with an increasing focus on private labels (PLBs).
Recently, in a sharp contrast to earlier periods, consumers have started considering purchase of PLBs as smart shopping.
Considering these aspects, this research aims to analyse the association of PLBs with customers and retailers so as to gauge customer loyalty, consumer preferences, shopping behaviour and also to understand the marketing strategies and objectives of PLB retailers.
It provides an insight into the positioning of brands and PLBs in the minds of consumers and recommends suitable strategies to enhance the market share of private labels.
Problem Statement
To present a better understanding of the factors influencing consumer behaviour towards private labels in
apparel retailing.
To study the emergence, growth and future of private labels in India
To examine the respondents awareness about private label brand apparels
To bring out the major factors that affect the perception of consumers related to private label apparels
To identify major price related dimensions influencing the purchase of private label apparels
To determine the importance of quality related perceptions (extrinsic and intrinsic cues) influencing the purchase of private label apparels
To analyse whether there is any relation between price and quality dimensions related to private label apparels
To segment the consumers on the basis of factors affecting their perceptions towards private labels brought out from the study
To determine the relationship between customer loyalty and private label branding
25 Diverse Literature Review
Study
Visit to nearby Malls, Retail Stores to observe Buying
Pattern
Employees / Friends working in
Retail firms, Qualitative FGD
21 Factors-Initial Questionnaire
1. Brand Name2. Style3. Availability4. Quality5. Discount Offers6. Price7. Value for Money8. Location9. Return on Damage Policy10. Comfort/Fit/Size11. Lifestyle12. Reliability13. Referrals14. Shelf Position of Merchandize15. Store Popularity16. Loyalty Points17. Word of Mouth18. Online Shopping19. Supportive in-store personnel20. Advertisements on TV21. In-store Promotions
Sampling Method Used: Non Probability – Convenience Sampling
Simple Random Convenience sampling is used in Exploratory Research, where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample (304 Respondents) is selected because they are convenient.
This non probability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.
Research Plan
To study the emergence, growth and future of private label Brands in India
To examine the respondents awareness about private label brand apparels
To bring out the major factors that affect the perception of consumers related to private label apparels
To identify major price related dimensions influencing the purchase of private label apparels
To determine the importance of quality related perceptions (extrinsic and intrinsic cues) influencing the purchase of private label apparels
To analyse whether there is any relation between price and quality dimensions related to private label apparels
To segment the consumers on the basis of factors affecting their perceptions towards private labels brought out from the study
To determine the relationship between customer loyalty and private label branding
The main data collection methods that was used for the study is online & offline questionnaires, forms which are completed and returned by respondents. This method is useful & inexpensive, this method was implied as literacy
rates were high and respondents were cooperative.
DemographicsFactor
AnalysisLabelling the
07 FactorsData Analysis
DemographicsFactor
AnalysisLabelling the
07 FactorsData Analysis
Since the KMO Measure of Sampling Adequacy meets the minimum criteria, we do not have a problem in conducting a factor analysis.
The Sig. value for this analysis leads us to reject the null hypothesis and conclude that there are correlations in the data set that are appropriate for factor analysis.
Communalities
Initial Extraction
Brand name 1.000 .555
Private Label brand vs
National brands 1.000 .657
Style 1.000 .649
Quality 1.000 .649
Availability 1.000 .669
Discounts 1.000 .684
Price 1.000 .542
Value for money 1.000 .606
Location 1.000 .462
Return/damage policy 1.000 .672
Product fitting 1.000 .715
Lifestyle 1.000 .766
Reliability 1.000 .641
Referral from friends
and family 1.000 .635
Size flexibility 1.000 .536
Shelf position 1.000 .627
Store popularity 1.000 .761
Loyalty points 1.000 .732
Prefer online over
offline 1.000 .587
Word of mouth 1.000 .501
In store personnel
support 1.000 .249
Television
advertisements 1.000 .698
In store promotion 1.000 .626
Print media 1.000 .610
Outdoor media 1.000 .612
Satisfaction level 1.000 .621
Extraction Method: Principal Component
Analysis.
As highlighted, Lifestyle, Store Popularity, Loyalty points and Product fitting contributes to over 70% of variance. Whereas, In-store personnel support gives the least variance in the model of about 20%.
It must also be observed and noted that the total sum of communalities is 16.062 with an average of 0.617769. Which indicates that this model has about 61.78% of variance, and this can be confirmed from the ‘Total variance Explained’ results in the next table.
The Total Variance Table shows that total 26 factors were observed through the Principal Component Analysis. However only the 7 factors with Eigen value greater than 1 will be taken into consideration.
Factor - Not all 26 factors will be retained. Only the first seven factors will be retained.
Total Variance Explained
Componen
t
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of
Variance
Cumulative
%
Total % of
Variance
Cumulative
%
Total % of
Variance
Cumulative
%
1 6.833 26.282 26.282 6.833 26.282 26.282 3.311 12.735 12.735
2 2.398 9.221 35.504 2.398 9.221 35.504 3.310 12.732 25.467
3 1.678 6.453 41.956 1.678 6.453 41.956 2.735 10.519 35.986
4 1.617 6.217 48.174 1.617 6.217 48.174 2.303 8.858 44.844
5 1.314 5.053 53.227 1.314 5.053 53.227 1.472 5.663 50.507
6 1.182 4.547 57.774 1.182 4.547 57.774 1.469 5.649 56.156
7 1.039 3.998 61.772 1.039 3.998 61.772 1.460 5.616 61.772
8 .986 3.791 65.563
9 .958 3.685 69.248
10 .859 3.305 72.554
11 .801 3.082 75.636
12 .784 3.014 78.650
13 .673 2.588 81.237
14 .644 2.478 83.716
15 .580 2.231 85.947
16 .530 2.037 87.984
17 .476 1.832 89.815
18 .430 1.652 91.468
19 .369 1.418 92.886
20 .360 1.385 94.270
21 .332 1.278 95.548
22 .323 1.243 96.791
23 .248 .952 97.743
24 .214 .824 98.568
25 .211 .811 99.379
26 .161 .621 100.000
Extraction Method: Principal Component Analysis.
DemographicsFactor
AnalysisLabelling the
07 FactorsData Analysis
The Component Matrix table contains component loadings, which are the correlations between the variable and the component. Because these are correlations, possible values range from -1 to +1.
The Components are the columns under this heading are the principal components that have been extracted. As you can see by the footnote provided by SPSS (a.), 7 components were extracted (the 7 components that had an eigenvalue greater than 1).
Rotated Factor Matrix table contains the rotated factor loadings (factor pattern matrix), which represent both how the variables are weighted for each factor but also the correlation between the variables and the factor.
Because these are correlations, possible values range from -1 to +1.For orthogonal rotations, such as varimax, the factor pattern and factor structure matrices are the same.
Here also, 7 factors are extracted. From this table we will label the factors. The variable considered for this factors will have a minimum value of 0.6 (cut-off).
Component Matrixa
Component
1 2 3 4 5 6 7
Brand name .121 .181 .261 .375 .285 -.427 .185
Private Label brand vs National
brands .534 .119 .435 .124 .311 .211 .111
Style .440 .287 .397 .123 -.215 .372 -.125
Quality .401 .609 -.141 -.066 .192 .224 -.077
Availability .602 .354 .014 -.057 .366 -.171 .122
Discounts .634 .316 .135 -.202 .322 .032 -.033
Price .647 .270 .228 .057 .073 -.010 .082
Value for money .287 .441 .327 -.332 -.293 -.142 -.080
Location .570 -.250 .088 -.224 -.100 -.026 -.082
Return/damage policy .582 .426 -.250 -.044 -.144 .177 -.188
Product fitting .323 .207 -.210 .259 -.352 .202 .540
Lifestyle .496 .106 -.303 .470 -.124 -.076 -.418
Reliability .545 .352 -.258 -.071 -.325 -.196 -.067
Referral from friends and family .517 -.064 -.426 -.382 .184 .036 -.027
Size flexibility .440 .027 -.160 .413 .030 -.314 .215
Shelf position .567 -.260 -.187 .000 .410 -.054 -.179
Store popularity .680 -.409 -.163 -.222 -.075 -.140 .176
Loyalty points .556 -.111 -.228 -.503 -.105 -.125 .282
Prefer online over offline .148 -.275 -.123 .212 .227 .537 .299
Word of mouth .608 -.120 .091 .201 -.156 -.167 .128
In store personnel support .257 -.071 .307 .044 -.156 -.227 .074
Television advertisements .513 -.520 .325 -.160 .121 -.075 -.111
In store promotion .535 -.334 -.155 .316 .053 .045 -.315
Print media .548 -.314 .306 .157 -.279 -.008 -.119
Outdoor media .553 -.320 .280 -.161 -.152 .277 .010
Satisfaction level .660 -.232 -.228 .238 -.099 .100 .055
Extraction Method: Principal Component Analysis.
a. 7 components extracted.
Rotated Component Matrixa
Component
1 2 3 4 5 6 7
Brand name .136 .011 -.158 .004 -.039 -.043 .712
Private Label brand vs National
brands .597 .410 -.056 -.034 .253 -.021 .253
Style .546 .426 -.289 .118 -.062 .214 -.149
Quality .739 -.211 .108 .166 -.048 .118 -.052
Availability .619 .035 .338 .084 -.040 -.004 .402
Discounts .566 .186 .301 .053 -.036 -.098 .153
Price .722 .321 .107 .112 -.067 .144 .262
Value for money .412 .223 .018 -.154 -.592 .099 -.051
Location .139 .518 .381 .144 -.067 -.036 -.055
Return/damage policy .567 .010 .215 .415 -.185 .257 -.177
Product fitting .142 .041 .082 .082 .121 .810 .091
Lifestyle .177 .064 -.007 .840 -.089 .094 .094
Reliability .309 .049 .322 .366 -.439 .335 .026
Referral from friends and family .262 .005 .708 .198 .073 -.044 -.133
Size flexibility .059 .083 .166 .365 .036 .274 .537
Shelf position .217 .199 .455 .388 .264 -.294 .163
Store popularity -.008 .481 .687 .173 .057 .125 .091
Loyalty points .133 .239 .769 -.072 -.124 .210 -.028
Prefer online over offline .073 .095 .056 .026 .723 .199 -.082
Word of mouth .116 .470 .191 .274 -.036 .244 .307
In store personnel support .012 .390 -.002 -.022 -.188 .062 .238
Television advertisements .029 .697 .299 .054 .113 -.311 .092
In store promotion .043 .348 .153 .646 .223 -.097 .052
Print media .033 .720 .015 .282 -.041 .078 .058
Outdoor media .190 .692 .198 .024 .136 .066 -.184
Satisfaction level .111 .360 .317 .490 .229 .281 .080
Component Score Coefficient Matrix
Component
1 2 3 4 5 6 7
Brand name .006 -.030 -.070 -.051 -.026 -.049 .531
Private Label brand vs National
brands .247 .113 -.136 -.146 .229 -.053 .108
Style .209 .191 -.289 .020 .007 .093 -.218
Quality .305 -.174 -.006 .041 .057 -.013 -.107
Availability .188 -.115 .122 -.086 .021 -.082 .256
Discounts .157 -.033 .065 -.085 .028 -.162 .044
Price .262 .057 -.047 -.063 -.006 .036 .121
Value for money .101 .115 -.031 -.120 -.377 .019 -.067
Location -.026 .155 .093 -.004 -.083 -.066 -.089
Return/damage policy .162 -.085 -.003 .184 -.087 .069 -.221
Product fitting -.034 -.021 .012 -.111 .148 .619 .049
Lifestyle -.027 -.064 -.142 .506 -.110 -.072 -.032
Reliability -.018 -.058 .092 .144 -.301 .148 -.029
Referral from friends and family .057 -.136 .317 .020 .053 -.088 -.121
Size flexibility -.102 -.064 .040 .102 .006 .160 .374
Shelf position .051 -.061 .140 .155 .145 -.292 .065
Store popularity -.135 .086 .274 -.061 -.007 .079 .048
Loyalty points -.060 -.001 .373 -.206 -.083 .153 -.010
Prefer online over offline .089 -.009 -.013 -.084 .542 .194 -.089
Word of mouth -.086 .126 -.004 .032 -.054 .141 .176
In store personnel support -.074 .167 -.043 -.070 -.156 .041 .162
Television advertisements -.037 .240 .049 -.047 .013 -.244 .024
In store promotion -.046 .050 -.066 .351 .086 -.158 -.052
Print media -.085 .283 -.137 .096 -.086 .019 -.035
Outdoor media .036 .262 -.027 -.095 .084 .041 -.204
Satisfaction level -.061 .040 .035 .161 .132 .156 -.013
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Component Scores.
DemographicsFactor
AnalysisLabelling the
07 FactorsData Analysis
Column 1 2 3 4 5 6 7
Attributes Quality,
Price
Television
Advertisement,
Print Media,
Outdoor Media
Referral from
friends &
Family, Store
Popularity,
Loyalty
Points
Lifestyle
(Add some
income stats
here to
support)
Prefer
Online
over
Offline
Product
Fitting
Brand
Name
Factor
Formed
Perceived
Quality
with Price
Influence of
Advertisement
Trust Factor
in Shopping
Consumer
Lifestyle
Online
Shopping-
an
Emerging
Trend
Comfort
level
Brand
Consciou
sness
By collating the variables above 0.6 in each factors. These factors were given appropriate labels described in the 3rd row of the table above.
Scree Plot Analysis
The Scree Plot graphs the eigenvalue against the component number.From the seventh component on, you can see that the line is declining, meaning the each successive component is accounting for smaller and smaller amounts of the total variance. In general, we are
interested in keeping only those principal components whose eigenvalues are greater than 1.
The variables that played a vital role in contributing to the factors are :
a. Quality, Priceb. Television Advertisement, Print Media, Outdoor Mediac. Referral from friends & Family, Store Popularity, Loyalty Pointsd. Lifestylee. Prefer Online over Offlinef. Product Fittingg. Brand Name
Seven Factors were found to influence the buying decision of consumer in the purchase of Private Label Apparels.
a. Perceived Quality with Priceb. Influence of Advertisementc. Trust Factor in Shoppingd. Consumer Lifestylee. Online Shopping- an Emerging Trendf. Comfort levelg. Brand Consciousness
Conclusion
In Sync with the earlier findings
Limitations
Larger Sample Size would have given us more conclusive results.
Expanding the study to tier-1,2 cities & not only Bengaluru, Lack of Time & Resources.
Lack of Awareness for Private Label Brands, Awareness Programs were needed.
Celebrity Endorsement & similar factors couldn’t be included because of less awareness about PLB
Discriminant Analysis of consumers was needed
Managerial Implications
1. Private label brands should focus primarily on the quality of the fabric & add-ons (like button, laces) to ensure the primary concern of the consumers is satisfied.2. Pricing strategy should be reviewed with these concerns in mind. If higher quality is demanded, pricing points can be raised to eliminate the cause of concern.3. If a PLB is not allocating its budget to marketing/ATL activities, now is the time to re-consider. Advertising plays a huge amount of role in convincing the consumer about the credibility of the brand.4. PLB should focus on building a referral pipeline. They should collect and build a testimonial bank through campaigns (Online and Offline) to advertise about customer satisfaction with a particular product.5. PLB should focus on its marketing and product mix by clearly defining their target market. They should be able to display the accurate lifestyle their products reflect.6. Online vs Offline seems to play an important role. PLB should Venture in Omni Channel Sales.7. Product design and comfort is vital. PLBs should make sure they are competitive to national brands in terms of product fitting. Their R&D should come with innovative designs to satisfy consumer comfort