Exploring differences in product attribute preferences of private vs. manufacturer brand buyers

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1 University of Aarhus From the SelectedWorks of Polymeros Chrysochou 2011 Exploring differences in product attribute preferences of private vs. manufacturer brand buyers Athanasios Krystallis Polymeros Chrysochou, University of South Australia Simon Jödecke Inga Polster Available at:

2 Exploring differences in product attribute preferences of private vs. manufacturer brand buyers Extended Abstract Introduction Nowadays, in most of the developed countries around the globe private brands have witnessed considerable growth (Sethuraman, 2009). This growth can be attributed to increased consumer recognition and retailers capability to promote private brands (Dhar & Hoch, 1997). Although consumer decisions to purchase private brands may depend on the product category (Richardson, Jain & Dick, 1996), product characteristics may be important drivers of choice and differ between private and manufacturer brands (Kwon, Lee & Kwon, 2008). Kwon et al. (2008) postulated that perceived product characteristics may influence purchase intent towards private brands. More specific, in product categories that are characterised by low involvement and low switching costs there is higher intention to buy private brands. Moreover, low value-conscious consumers are more likely to buy private brands when the products are search goods rather than experience goods. These findings suggest that private brands, in comparison to manufacturer brands, are perceived differently by consumers. Moreover, consumers may place different importance weights to product attributes when choosing between private and manufacturer brands within the same product category. However, the literature still lacks comparative insights into the differences in preferences for specific attributes between private labels and manufacturer brand buyers across different product categories. In order to further explore this phenomenon, this paper aims to investigate differences in product attribute preferences between brand type buyer groups (i.e. private vs. manufacturer brand buyers) between two fast moving consumer goods categories. Material and Method For the purposes of this study, the Best-Worst Scaling (BWS) method was used to measure the importance that private and manufacturer brand buyers assign to product attributes (Marley and Louviere, 2005). There are many advantages in using BWS; for instance, BWS 1

3 is free from individual scale usage bias and infers a ratio level importance scale that allows for comparisons across consumer segments (Lee, Soutar & Louviere, 2008; Marley and Louviere, 2005). During a BWS task, participants are asked to indicate the most (best) and least (worst) important attribute from sub-sets of all attributes (Marley and Louviere, 2005). In the present study, participants were asked to choose the attribute that most and the attribute that least influenced their choice when purchasing private and manufacturer brands. In order to investigate differences across product categories, a non-edible (toothpaste) and an edible (orange juice) category were included. Attributes in each category to be evaluated were elicited and validated based on a pilot study. For each category, a final set of 13 attributes was drawn. Then, these 13 attributes were combined into 13 subsets of 4 attributes each, based on a balanced incomplete block design. This type of design ensures that each attribute appears the same number of times (i.e. 4 times) across all subsets and that within each subset each pair of attributes appears only once. For each attribute, the aggregated BWS score was estimated by subtracting the number of times that each attribute was chosen as least important from the number of times that it was chosen as most important. The results of these calculations are individual-level BWS scores for each attribute that are easily comparable across the entire sample. As explained above, in this study each attribute appeared a total of 4 times in the experiment, therefore the individual-level BWS scores for each attribute range between +4 and -4. Data were collected in the form of a web-based survey carried out in Germany during July Two versions of questionnaires were distributed, one for each product category. The questionnaire was structured into four sections. In the first section, participants were provided with brief definitions of private and manufacturer brands in order to ensure an accurate understanding of the terms. The second section included general shopping behaviour questions, such as preferred shopping location, volume per shopping trip and frequency of purchase from the categories selected. In this section, a question in relation to past purchase behavior (i.e. how many times out of 5 did you buy private label/manufacturer brands?) was asked to classify the sample into private and manufacturer brand buyers. The third section included the Best-Worst Scaling (BWS) method. Finally, the last section included questions related to consumer socio-demographics. 2

4 Results In total, 410 participants took part in the survey, from which 49.3% were private brand buyers. The average age of the sample was 35.7 years, 42.2% were male and 73.7% were non-married. Tables 1 and 2 present the scores from the BWS method. In order to derive with a standardized ratio scale of attribute importance, the square root of the ratio of best and worst counts was used (Lee, Soutar & Louviere, 2008). Standardisation of this ratio to 100 for the most important attributes allowed for comparisons of the importance of each attribute relative to the most important one. In addition, this approach provided the opportunity to compare the importance of each attribute between private and manufacturer brand buyers. For example, for orange juice the attribute pure was the most important attribute for the whole sample and the manufacturer brand buyers, whereas good value for money was the most important attribute for private brand buyers. Finally, independent sample t-tests reveal the differences in the individual-level BWS scores between private and manufacturer brand buyers. Table 1. Individual-level BWS scores and square root ratio scores for each attribute (Orange Juice) Attribute Whole Sample (N=210) Mean of individual-level BWS Private brand buyers (N=109) Manufacturer brand buyers (N=101) StdSQRT StdSQRT StdSQRT t-test (p value) Pure (0.061) Taste (0.812) Good value for money (0.000) Brand trust (0.000) Pulp (0.084) Vitamin C (0.405) Sales promotions (0.000) Corporate image (0.000) Long shelf life (0.009) Premium price (0.268) Paper carton packaging (0.000) Recyclable packaging (0.446) Calcium (0.000) 3

5 Table 2. Individual-level BWS scores and square root ratio scores for each attribute (Toothpaste) Attribute Whole Sample (N=200) Mean of Individuallevel BWS Private label buyers (N=93) Manufacturer brand buyers (N=107) StdSQRT StdSQRT StdSQRT t-test (p value) Good value for money (0.000) Tartar control/fluoride content (0.750) Breath freshening capabilities (0.184) Taste (0.656) Whitening capabilities (0.866) Brand trust (0.000) Dentist's approval (0.228) Corporate image (0.000) Texture (0.539) No additives (0.049) Stand-up packaging (0.008) Product innovations (0.344) Tube packaging (0.027) Discussion and implications The present work offers insights into the differences in preferences for specific attributes between private labels and manufacturer brand buyers in two different product categories. Such comparative insights are currently missing from the relevant literature, so the present work fills in an existing gap in this respect. Based on the results some general conclusions can be drawn. Between product categories, both private and manufacturer brand buyers assign importance to similar product attributes. For example, the attribute good value for money was among the most important ones, followed by health and quality related attributes. However, between buyer groups there were also significant differences within each product category. Brand trust and corporate image were more important for manufacturer brand buyers, whereas good value of money was more important for private brand buyers (especially in the orange juice category). On the opposite, physical product attributes (i.e. packaging-related) do not seem to differ between buyer 4

6 groups or, where different, the preference scores are among the lowest of all attributes examined. This study raises some broader implications for the marketing of private brands. Private label buyers care for functional performance of products (i.e. in the present case for hedonic and health-related attributes) as much as manufacturer brands buyers do. However, their preferences are led by good value for money. This suggests that this group should be provided with products that are good value for money and at the same time be similar in performance to manufacturer brands. On the other hand, branding is more important for manufacturer brand buyers. These two different approaches (i.e. private label buyers carrying for functional performance; and manufacturer brand buyers carrying for functional performance AND product/corporate branding) might lead us to conclude that the two buyer groups perceive the meaning of good value for money differently. The brand is part of the value experience for the manufacturer brand buyers, possibly irrespective of the category in which the brand belongs. In this respect, it can be concluded that a strong brand stands as independent contributor to customers perceived quality, comparable or even beyond the (expectedly high) product s functional quality performance. Besides functional quality, manufacturers should keep investing in strong brand building to retain their customer basis, induce loyalty and prevent their buyers from switching. 5

7 References Dhar, S. K., & Hoch, S. J. (1997). Why store brand penetration varies by retailer. Marketing Science, 16(3), Kwon, K. N., Lee, M. H., & Kwon, Y.J. (2008). The effect of perceived product characteristics on private brand purchases. Journal of Consumer Marketing, 25(2), Lee, J. A., Soutar, G., & Louviere, J. (2008). The Best-Worst scaling approach: An alternative to Schwartz s values survey. Journal of Personality Assessment, 90(4), Marley, A. A. J., & Louviere, J. J. (2005). Some probabilistic models of best, worst, and bestworst choices. Journal of Mathematical Psychology, 49(6), Richardson, P., Jain, A.K., & Dick, A. (1996). Household store brand proneness: A framework. Journal of Retailing, 72(2), Sethuraman, R. (2009). Assessing the external validity of analytical results from national brand and store brand competition models. Marketing Science, 28(4),