A longitudinal analysis of brand loyalty evolution

Transcription

1 A longitudinal analysis of brand loyalty evolution Gauthier Castéran * Doctorant IAE Toulouse, Center of Research in Management (UMR-CNRS 5303) Polymeros Chrysochou Associate Professor Department of Business Administration, Aarhus University, Aarhus Lars Meyer-Waarden Professor IAE Toulouse, Center of Research in Management (UMR-CNRS 5303) & EM Strasbourg Business School-HuManiS (EA 1347) * Corresponding author Address: IAE Toulouse 2, rue du Doyen Gabriel Marty, Toulouse Cédex 9 gauthier.casteran@gmail.com, Phone: Acknowledgment: The authors wish to thank GfK Denmark for granting access to the data used in this study and support of the HEALTHCOG project funded by the Danish Council for Strategic Research. 0

2 Une analyse longitudinale de la fidélité à la marque Résumé: Fidéliser la clientèle est un enjeu majeur pour les entreprises. Cependant, de nombreux chercheurs pensent que la fidélité décroît au fil du temps. Cet article s intéresse donc à l évolution de la fidélité à la marque en utilisant des données de panel GfK Danemark comprenant 55 catégories de produits sur une période de 6 ans ( ) et aux raisons pouvant expliquer ce (possible) déclin. Nous montrons que la fidélité à la marque à un niveau agrégé est stable dans le temps et ne décroît pas. Néanmoins, nous observons que cette évolution dépend de la catégorie de produit considérée. Mots-clés: Fidélité à la marque, marques de producteur et de distributeur, modèle Dirichlet. A longitudinal analysis of brand loyalty evolution Abstract: The ultimate goal of marketers is to achieve high loyalty towards their brands. However, there is a common anecdotal belief that loyalty towards brands declines over the years. In this paper we offer insight into this area by examining the evolution of brand loyalty and the reasons that lead to this (possible) decrease. We use purchase data from the GfK panel in Denmark and analyse loyalty evolution for 55 packaged good product categories over a period of six years ( ). We show that on an aggregate level, brand loyalty has not evolved. However, we observe that evolution is product category specific. Key-words: Brand loyalty, private labels and national brands, Dirichlet model. 1

3 A longitudinal analysis of brand loyalty evolution Introduction Brand loyalty is of major importance for firms and therefore marketers put excessive efforts in order to increase loyalty toward their brands. Among the benefits of brand loyalty is the higher profitability of loyal customers (Reinartz and Kumar, 2000). Given its importance, there is no reason to question why marketers are worried about recurring managerial statements that loyalty declines over the years (Kapferer, 2005). Until now, such concerns have brought limited attention to academic literature (Johnson, 1984; Dekimpe & al., 1996; East and Hammond 1996; Stern and Hammond, 2002; Dawes, Meyer-Waarden and Driesener, 2008, 2012), while their main findings do not indicate any significant decline of brand loyalty. These studies however have limitations that question the external validity of their findings. First, most of them are conducted with outdated data. Recent trends that are suggested as reasons of brand loyalty decline (e.g. increasing competition among brands, introduction of private labels, consumers becoming more price conscious due to economic recession) call for the need for up-to-date data. Second, the period of analysis in some of these studies is short, which does not allow capturing any potential trends. Finally, those studies that found a decline on brand loyalty did not investigate the reasons that led to this decline. In this study we therefore analyse the evolution of brand loyalty and reasons that lead to this evolution, by using recent, longitudinal panel data ( ) in a large number of packaged good categories (55). To do that, we first describe the rationale behind loyalty evolution and the reasons for potential decline. We follow by describing the data and methodology used to measure brand loyalty. We then present the results, and conclude with a discussion and directions for future research. 2

4 1. Literature review 1.1 Brand loyalty and rationale for decline Brand loyalty entails repeat purchasing behaviour, accompanied by an underlying positive attitude and a high degree of commitment (Dick and Basu, 1994), and is explained by different factors. First, high market share brands usually display higher loyalty due to distribution advantages which increases buying probabilities which is known as the double jeopardy phenomenon (Ehrenberg, 1988; Fader and Schmittlein, 1993). Second, highly differentiated niche brands display high degrees of loyalty, which is related to market partitions that appeal to certain buyer segments (Hauser and Wernerfelt 1990; Fader and Schmittlein, 1993; Uncles & al., 1994). Finally, marketing mix variables (e.g. product features; Bhattacharya, 1997; Jung, Gruca and Lopo, 2010). A potential brand loyalty decline could be attributed to different reasons. First, brand loyalty is often said to be replaced by price loyalty due to an excessive use of promotions (Mela, Jedidi, and Bowman, 1998), which could widen brand repertoires and decrease loyalty. Second, the introduction of a large number of national brands (NB) and private label brands (PLB) has changed the competitive sphere, with consumers showing higher levels of loyalty to PLB and consequently to the given stores (as their prices are often lower than those of national brands, whereas they are similar in terms of product quality; Sethuraman and Cole, 1999; Hyman, Kopf and Lee, 2008). Third, consequently, the number of brands and stock keeping units (SKU) increases (according to certain studies by 16% per year; Quelch and Kenny, 1994). This proliferation of brands might widen consumer repertoires (number of brands bought at least once in the time period) and thus decreases brand loyalty. Hence, Research Proposition: Evolution of brand loyalty is negatively affected by the total number of products and brands (including private label brands) and the repertoire size. 3

5 1.2 Studies about brand loyalty evolution Empirical evidence on long-term evolution of brand loyalty is scarce. Table 1 presents the principal findings of earlier research investigations. Study Number of FMCG categories Number of years studied Main finding Johnson (1984) 20 8 Slight decline East and Hammond (1996) 9 2 Stability Dekimpe & al (1997) 21 2 Stability Stern and Hammond (2004) 2 5 Slight decline Dawes, Meyer-Waarden and Driesener (2008 & 2012) Slight category-specific decline Table 1: Studies about loyalty evolution Most studies find some evidence of loyalty decline, but its magnitude is rather small and mostly category specific. East and Hammond (1996) as well as Stern and Hammond (2004) find that loyalty for consumer packaged goods stays stable. Johnson (1984) analyses 20 product categories in the US over a period of eight years and finds only a slight decline in loyalty. Dekimpe & al. (1997) report no evidence that loyalty declines by studying 21 product categories over a two-year period ( ). However, these studies were conducted almost two decades ago and recent trends are not evident in these datasets (e.g. increase of private label brands and overall repertoire size). Another weakness is the short span of time used in their analysis (i.e. two studies had only records for two consecutive years), which may not be enough to detect potential evolution of brand loyalty. The only recent study coming from longitudinal time periods between 1998 and 2012 is that of Dawes, Meyer-Waarden and Driesener (2008 and 2012) who find in 9 from 21 US and UK packaged good categories a very slight category-specific decline. However, the authors do not provide any explanations for this decline. 4

6 We thus investigate if product category characteristics play a role in the evolution of brand loyalty. More specifically we explore the impact of the total number of SKU and brands (including PLB and NB) and consumer brand repertoires on brand loyalty evolution. 2. Method 2.1 Data We use GfK consumer panel data from Denmark (2,500 households pooled across stores) geographically and demographically representative of the Danish population. We consider data that cover purchases for a period of 5 years (2006 to 2011) across 55 fast moving consumer good (FMCG) categories and analyse about 3,388 different brands. These data cover every purchase each household makes on a daily basis. 2.2 Data modelling method Our study focuses on behavioural loyalty, namely, repeat purchasing (even if literature considers that real loyalty is behavioural and attitudinal loyalty) which is less confounded by changes in category purchasing or market share shifts than other indicators (e.g. brand purchase frequency, repeat rates, share of requirements; see Ehrenberg, 1988). To control for the confounding factors such as category-level purchasing and changes in brand share, we use the Dirichlet multinomial model (Goodhardt, Ehrenberg and Chatfield, 1984). The Dirichlet model provides theoretical parameter for brands which are independent of the time frame of analysis, category purchasing or other issues that affect traditional behavioral loyalty metrics (Ehrenberg, Uncles and Goodhardt, 2004; Fader and Schmittlein 1993; Uncles & al. 1994). One such parameter is the switching parameter S which measures heterogeneity in the distribution of brand choice probabilities across the buyer population. The S parameter denotes that increased switching between all brands (not just between a subset) implies decreasing loyalty (to all brands) within that category. From the S we compute the 5

7 polarization index (φ) which captures changes in the heterogeneity in consumer choice as purchase incidence changes (φ = 1/(1+S)). Polarisation φ ranges between zero and one, where zero indicates pure homogeneity in consumer choice which signals more brand switching hence lower loyalty (i.e., all buyers have the same propensity to buy individual brands). When φ reaches one, there is maximum heterogeneity which implies decreased switching between brands and higher loyalty (i.e., each consumer buys only their favorite brand; Fader and Schmittlein, 1993; Sabavala and Morrison, 1977). Importantly, φ is an un-confounded, reliable and stable measure of behavioural loyalty, because the latent brand choice probabilities are not affected by changes in category purchasing, nor by the time period of analysis, though the observed behavior in each case would be (Corsi, Rungie and Casini, 2011). This makes it adequate for our investigation (Fader and Schmittlein, 1993). We estimate φ for the total number of brands in each product category, as well as for PLB and NB separately. Finally, to avoid bias caused by small brands, in the analysis we consider only brands with market share greater than one per cent. All remaining brands are grouped and included in the analysis as other brands (Ehrenberg, 1988). 3. Results Figure 1 presents the average polarisation φ values across all product categories per year. It presents φ values for the total brands in the category, as well as for the private label brands (PLB) and national brands (NB) irrespectively. As it can be seen, on an aggregate level, φ remains almost constant and close to 0.41 for the total brands, 0.60 for the PLB and 0.45 for the NB. Apparently for the PLB the average φ values are higher, and thus consumers are more loyal to PLB compared to NB. We distinguish product categories into groups with: a) increasing loyalty (φ increase 10%; b) decreasing loyalty (φ decrease 10%), c) no change (φ variation < 10%), between

8 and From the total product categories, 14 (25%) show increasing loyalty, 14 (25%) show decreasing loyalty and 27 (50%) show no change in loyalty (Table 2). In product categories with increasing loyalty, φ increased from 0.39 to 0.49, whereas in those with decreasing loyalty, φ decreased from 0.40 to 0.33 between 2006 and Figure 1: Average evolution of polarisation φ Increasing Loyalty Decreasing Loyalty No Change Biscuits; Bubble Bath; Chips Snack; Chocolate; Conditioners; Cosmetics; Diapers; Oils; Mustard; Skin Care; Soups; Tea; Toilet paper; WC blocks Asian & Mexican Food; Cheese; Coffee; Eggs; Frozen Pizza; Ice Cream; Liqueur; Liver Pate; Meat; Milk; Pate Bacon; Spaghetti; Sugar; Wheat bread Beer; Biscuits; Butter; Cereals; Cream; Deodorants; Detergents; Fruit Juices; Hand Soap; Instant Coffee; Jam; Juice; Ketchup; Poultry; Margarine; Honey; Pasta & Rice Dishes; Rye Bread; Sauces; Sausages; Shampoos; Soft Drinks; Sodas; Spices; Toothbrush; Toothpaste Table 2: Product categories and loyalty evolution groups (in-/decreasing, no change) Table 3 presents for each loyalty evolution group (i.e. in-/decreasing, stable loyalty) the evolution of category metrics. More specifically, we investigate the evolution of repertoire size, the number of brands and SKUs (according to national and private label brands). 7

9 Groups Year % Change 2006 & 2011 Average Repertoire Size No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of Total Brands No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of Private Label Brands (PLB) No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of National Brands (NB) No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of Total SKUs No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of SKUs for Private Label Brands (PLB) No Change % Increasing Loyalty % Decreasing Loyalty % Average Number of SKUs for National Brands (NB) No Change % Increasing Loyalty % Decreasing Loyalty % Table 3: Evolution of category measures For categories with decreasing loyalty the repertoire size is larger, whereas in categories with increasing loyalty the repertoire is smaller (Figure 2). Categories with decreasing loyalty show higher decline of the repertoire size (-20.3%) than those with increasing loyalty (-14%). 8

10 Figure 2: Evolution of repertoire size across product category groups For categories with decreasing loyalty the number of brands (PLB and NB) is higher compared to those where loyalty increases (Figure 3). For categories with decreasing loyalty the average number of brands increases (13.6% for NB, 3.0% for PLB), whereas in those with increasing loyalty the number of NB decreases (-2.4% for NB, 6.1% for PLB). Figure 3: Evolution of number of brands (total, PLB, NB) 9

11 For product categories (PLB and NB) with decreasing loyalty the average number of SKUs is higher compared to those where loyalty increases (Figure 4). We can thus confirm our research proposition. Both groups of categories with decreasing and increasing loyalty show a drop in the average number of SKUs (-5.1% and -6.8%). The distinction between PLB and NB shows that this decrease is somewhat stronger for PLB (-12.7% vs %) than for NB (-1.2% vs. -4.4%). Figure 4: Evolution of number of SKUs (total, PLB, NB) 4. Discussion This study makes a unique contribution by examining the longitudinal evolution of brand loyalty over multiple years in a large panel of product categories. At the aggregate level, our findings do not support the hypothesis that brand loyalty declines (Kapferer, 2005), and it 10

12 rather seems to be stable. However, a closer look at the individual product categories reveals that evolution of brand loyalty is a product category specific phenomenon. In fact, whereas for 50% of the product categories included in this study brand loyalty did not change, in 25% of them brand loyalty increased and the remaining 25% decreased. Regarding the consumer repertoire size, those product categories for which brand loyalty decreases consumers repertoire is higher. At the same time consumers repertoire declines, and this decline is even higher for product categories with decreasing loyalty. Regarding the number of brands and SKUs, product categories with decreasing brand loyalty have more brands and SKUs compared to categories on which brand loyalty increases, a finding that indicates variety seeking (Chintagunta, 1998). This observation is the same for private lables (PLB) and national brands (NB) as well, although in the case of categories with decreasing loyalty the number of PLB brands and SKUs is proportionally higher than in categories with increasing loyalty. Finally, for categories with decreasing loyalty the number of brands increases. This increase in number of brands is distinguished into an increase in the number of NB and a decrease of PLB. Thus the decrease of PLB seems to drive the decrease in overall brand loyalty. Actually, our data show that PLB exhibit higher loyalty than NB (Sethuraman and Cole 1999; Nenycz-Thiel & al., 2010), which explains why a change in the number of PLB affects also loyalty. 5. Theoretical, managerial and methodological implications Brand loyalty decline is more of a buzzword than a well-founded empirical fact. According to Ehrenberg (1988) marketers must work hard to stand still which suggests that changes in brand performance are hard to be achieved. In this paper we contribute to this notion by providing empirical evidence that brand loyalty is stable over time. Our results further indicate that marketing actions do not really lead to rapid changes in loyalty on the long run. 11

13 Loyalty decline appears to be category-specific, a result that suggests that marketers have to understand better the type of category they are operating in as same marketing actions may lead to different results and may not be equally efficient. For example, the negative link between number brand and SKUs in a category, and brand loyalty shows that the more competitive a market is (i.e. the higher the number of brands and SKUs) the less likely brands will increase their loyalty. This implication puts obstacles to product managers strategic actions to launch new brands and line extensions as loyalty levels might probably decrease. 6. Limitations and directions for future research This study has some limitations, which define avenues for future research. The Dirichlet model is zero-order which suggests that consumers do not have prior learning experiences and every purchase is independent from the previous one. Moreover, the model cannot take into consideration covariates (e.g. household/consumer characteristics) that also influence overall purchase behaviour. More sophisticated models (such as the explanatory BG/NBD or Pareto/NBD model with explanatory variables) could be used to get a better understanding of what causes difference in brand loyalty and further on its evolution (Fader and Hardie, 2006; Castéran, Meyer-Waarden and Benavent, 2007; Rungie, Uncles and Laurent, 2013). Our results are also specific to FMFG categories and Denmark. Existing literature proposes several other factors, such as competitive structure, and has argued that loyalty is higher in categories or sectors with higher customer involvement (Laurent and Kapferer, 1985). Several questions come into consideration that suggests future research. Is it easier to build loyalty in some product categories than in others and why? Does brand extension and increased repertoire size systematically lead to brand loyalty decline? Do certain categories succeed in disproportionately attracting brand-loyal consumers and why? Which marketing mix variables are most effective in building loyalty? What is the role of consumer characteristics? 12

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