Exploring linkages between socio-demographic factors and customer loyalty in India

Abstract

Customer loyalty for specific brands has been an important point in marketing planning. In recent years many organizations have identified the need to become more customer oriented with increased global competition. Marketers have realized the importance of building long-term and sustainable customer relationships that add value both for the customer and the company. This paper attempts to understand linkages between consumers' brand loyalty with respect to various product categories and socio demographic variables in order to appreciate customer relationship marketing (CRM) strategies in the changing Indian context. Survey results have shown eight product categories for which customers indicated high loyalty: personal care, automobiles, cleanliness and hygiene, high-end technology gadgets, perfumes, alcohol, health and fitness and beverages, almost all of which are used for personal consumption. Further, results indicated that education followed by residence type, family size has a significant correlation with customer loyalty (significant in case of five product categories out of eight). The purport of this study will have a deep impact on CRM investments and will help redefine and refocus current customer loyalty strategies and investments. [PUBLICATION ABSTRACT]

Headnote

Abstract: Customer loyalty for specific brands has been an important point in marketing planning. In recent years many organizations have identified the need to become more customer oriented with increased global competition. Marketers have realized the importance of building long-term and sustainable customer relationships that add value both for the customer and the company. This paper attempts to understand linkages between consumers' brand loyalty with respect to various product categories and socio demographic variables in order to appreciate customer relationship marketing (CRM) strategies in the changing Indian context. Survey results have shown eight product categories for which customers indicated high loyalty: personal care, automobiles, cleanliness and hygiene, high-end technology gadgets, perfumes, alcohol, health and fitness and beverages, almost all of which are used for personal consumption. Further, results indicated that education followed by residence type, family size has a significant correlation with customer loyalty (significant in case of five product categories out of eight). The purport of this study will have a deep impact on CRM investments and will help redefine and refocus current customer loyalty strategies and investments.

Keywords: loyalty, customer, socio-demographic Factors, Brand, CRM, Relationship.

Please cite this article as following: Mishra, S. and Prasad, S. (2014), "Exploring linkages between socio-demographic factors and customer loyalty in India", Management & Marketing. Challenges for the Knowledge Society, Vol. 9, No. 1, pp. 13-26.

Introduction

India is an emerging economic powerhouse, and its middle class rising to prosperity. With more money power and multiple product offerings, today India is becoming a truly customer ]driven market. Marketers are hastily discarding old habits and adopting new notions of customer behaviour. The current marketplace is flooded with products and services, competing for mindshare and market share. Consumers face multiple options, and get to choose from a wide array of branded and unbranded products and services. What drives consumers to purchase a particular brand or product has always remained a point of debate with marketers. At the same time marketers are also realizing that it is becoming increasingly difficult to differentiate products and services from one another (Clark, 2006) in order to distinctly appeal to consumers.

It is in this scenario that Relationship Marketing entered the stage promising the newest passageway to the "holy grail" of marketing - customer loyalty (Shugan, 2005). Customer loyalty has become a vital strategy especially in the times of myriads of offers, where buyers have a tendency to move from one brand to the other. Loyalty is a measured capacity of how much a purchaser can be emotionally involved in a brand (Aaker, 1991). Whether repeat purchase is a result of a customer's loyalty to a brand (termed as brand loyalty) has always remained an unanswered question (Jacoby and Kyner, 1973). Researchers have been unable to conclude definitely whether repeat purchase is an unassuming habit or is simply a result of circumstantial convenience. Nevertheless in order to use an available customer retention strategy that is somewhat scientific and based on customer data, brands and their managers' focus on CRM.

Brand managers, product specialists and marketers concede that outcomes of CRM efforts are usually not commensurate with the quantum of resources they invest in the efforts. Of the four Ps in marketing consumers in general are more conscious of price (Anselmsson et al., 2007). Given the value-driven nature of Indian consumers, who are extremely price-sensitive and tend to shiftbrand loyalties easily if competitive pricing strategies are followed by products, the relationship between brand loyalty and competitive factors becomes important. Though the brand-price association is a vital ingredient in retaining the loyalty of customers (Kumar, 2008), over the years it is not just the price but a whole range of demographic factors that have influenced loyalty. This is despite the fact that currently purchase decisions are taken rather based on pricing than on loyalties, as is evident in today's plethora of retail promotions seen in the media every day.

The question in the intensely competitive market is: "Is the brand-price paradigm sufficient to understand loyalty?" The answer is no. The more obvious answer is to understand changing-like-never-before socio-demographic factors of customers across all Socio Economic Classifications (SECs). Rubera and Eisingerich (2010) acknowledge that more affluent and better educated customers are less likely to be committed to a specific brand. Commitment of less affluent consumers to the brands they use is often unusually strong, possibly because they cannot afford to take the risk of trying a brand that might not suit them as well. However younger consumers are less committed to brands than older consumers (Clark, 2006). This implies that consumer demographics play a large role in determining loyalty. In addition, nowadays consumers have more disposable income than they had earlier, prompting them to explore multiple avenues to spend, or buy newer products. The axiom seems to be: buy more rather than buy better. This has spawned offan entirely new generation of consumers for whom loyalty is merely a word, not an attitude. The way to understand this conundrum is to perhaps take the socio psychological route which offers glimpses of customers' evolving behaviour patterns, based on the multimedia stimuli they are exposed to everyday.

Customers have changed - or, to be more precise - are constantly changing their buying habits, preferences and, above all, the products and services they use. There seems to be more factors at play than just one of loyalty to work out CRM strategies. These multiple factors in turn produce multiple results, and these outcomes do not necessarily and clearly point to the success or failure of a strategy. Living patterns across urban India and changing work-life balances have had nowadays a profound impact on consumers. This has led to increased time and effort in understanding customers better. Each socio-demographic factor (age, income, family, dependencies, education, job, etc.) has to be analysed and understood thoroughly in the context of a purchase.

All this prompts researchers and CRM practitioners to answer the question: Is customer loyalty a myth? Do CRM strategies have an impact on customers? What is brand loyalty directly proportional to? This study therefore involves understanding the consumer behaviour of average Indian customers' demographics and brand preferences.

Literature Review

We reviewed existing literature, vast and comprehensive, in the areas of customer loyalty, relationship marketing, consumer behaviour, buyer decisions, loyalty determinants and CRM strategies in order to understand the consumer behaviour, their brand loyalty and CRM strategies.

Consumer behavior and CRM

One of the key areas in marketing is consumer behaviour without which any marketing strategy or CRM would be incomplete or imperfect. Relationship marketing has as starting-point the recognition that customers exist in complex dynamic systems in which they enact multiple roles (Mitussis et al., 2006). In the present context, increased competition and multiple product offerings, loyalty is described as the customer's willingness to patronize a brand over a fairly long period of time (Leone et al., 2006). Such customers are even likely to recommend the brand to others, resulting in word-of-mouth promotion.

However brands are finding it increasingly difficult to retain the loyalty of their customers in a changing market scenario (Chattopadhyay et al., 2009). Companies also recognize that what drives almost two-thirds of customer purchases, impacting nearly every functional area within the organization is the brand's relationship with customers, and that building and preserving this relationship is a crucial strategy in marketing (Davis and Halligan, 2001). In fact, according to Shankar et al. (2003), customer loyalty has also been shown to be important both in the offline as well as in the online marketing environment. And, as Kotler (1997) reiterates customer loyalty is the bedrock of all strategic marketing planning.

It is not known exactly whether consumers remain loyal within specific product categories, and what influences this loyalty (Krystallis et al., 2009). Researchers have also examined the attitudinal aspect of brand loyalty (Bowen and Shoemaker, 1998; Iwasaki and Havitz, 1998; McCleary and Weaver, 1992), which focuses not only on transactional strategies, such as frequent-user programs and gifts for repeat customers but also on attitudinal variables, such as commitment and trust. Back and Parks (2003) also suggest that customer satisfaction does not guarantee true brand loyalty. This is of vital importance in CRM investments. It simply means that customer satisfaction does not imply repeat purchases.

In a highly competitive scenario where multiple products, with reducing differentiators, are chasing them, a more complex model is needed to understand customer behaviour and predict loyalty (Helkkula and Kelleher, 2010). Several studies have shown a relationship between demographics of consumers and brand loyalty. However the findings about the nature of this relationship are very inconsistent. Cole et al. (2008) suggested higher brand loyalty among older age groups because of deeper relationships with brands over a period of time. But findings from some other researchers' (Setlow, 2002; Chi et al., 2009) studies contradict this and explain that loyalty is not influenced by age, rather, over a period of time, experience affects more as an influential factor. Moisescu (2009) concluded that in the case of non-durables, education level does not have any influence on brand loyalty. Mokhlis and Salleh (2009) have concluded that cultural and demographic factors play a more pivotal role in customer decision-making, and have a significant impact on brand loyalties. Further, Beneke (2010) has suggested that consumer perceptions of a brand vary with promotional efforts. According to Reichheld (1996) and Lee and Cunningham (2001), perception of the customer based on demographics affects her judgment of brands and in turn it impacts brand loyalty.

Brand loyalty of Indian consumers and their changing demographics

Biedenback and Marell (2010) have stated that customer experience is paramount in ensuring brand loyalty. And experience is an outcome of multiple cultural and demographic factors. Basic factors such as trust and commitment which Morgan and Hunt (1994) had emphasized as the bedrock of any relationship marketing effort, are now directly influenced by the local or regional marketing environment of a country (du Plessis and Roberts-Lombard, 2012). Thus, anything from a simple buying experience to the experience of usage and product performance has today become in itself a huge business process considering local factors better than just theoretical or general frameworks.

As an extension of several decades of study, John (2011) reiterates that brand loyalty in the Indian context is heavily dependent on customer satisfaction, though Shugan (2005) had questioned the logic behind loyalty programmes almost going to the extent of suggesting that brand loyalty is non-existent. Muthuvelayudham and Subburaj (2012) in a study of brand loyalty towards FMCG products have concluded that customers get influenced on by a wide range of demographic factors such as age, sex, family and society. This has been substantiated by Singh and Negi (2012) who described that an analysis and understanding of prospective customers based on their demographic characteristics and geographical regions is important in order to offer the right products and services.

Saha et al. (2008) have discussed loyalty patterns and brand relationships with age ]groups, concluding that the higher the range of brands, the lower the loyalty of customers towards a specific brand. In the context of demographics, generally, Ali et al. (2012) have found the family and the number of children in the family as influencers of consumer behaviour. Tahir and Zulkifli (2012) imply in their study that customers f perceptions of CRM practices among banks are similar regardless of gender, age group, education level, employment, and that these demographic factors have no relationship whatsoever to customer loyalty. However none of the previous studies has attempted to explore a relationship between various product categories and each demographic factor individually as the present study has attempted.

Significantly, browsing through the published literature, there has not shown up sufficiently enough definite linkages between loyalty and the buying habits of consumers. While on the one hand companies are spending heavily on brand ]related communication and making efforts to shore up loyalty, on the other hand they are launching multiple choices of products which reduce the loyalty of consumers towards a brand. Are these strategies working at crosspurposes? Or is competition overriding relationship efforts? It is in this context that the current study has been undertaken. Research methodology

Formulation of hypotheses

Based on the literature survey the following eight null hypotheses were formulated:

Hypothesis 1: There is no relationship between monthly income and brand loyalty across product categories.

Hypothesis 2: There is no relationship between educational qualification and brand loyalty across product categories.

Hypothesis 3: There is no relationship between the number of family members and brand loyalty across product categories.

Hypothesis 4: There is no relationship between profession and brand loyalty across product categories.

Hypothesis 5: There is no relationship between age and brand loyalty across product categories.

Hypothesis 6: There is no relationship between residence type and brand loyalty across product categories.

Hypothesis 7: There is no relationship between leisure and lifestyle habits and brand loyalty across product categories.

Hypothesis 8: There is no relationship between customers exhibited social personality and brand loyalty across product categories.

Questionnaire

The questionnaire was designed on the basis of literature review as well as based on structured and unstructured interviews with CRM practitioners, product specialists, brand managers, retail managers, sociologists and psychologists. An online survey was carried out with a cross ]section of consumers to determine purchase behaviour, and explore whether relationships existed between personal demographic factors such as age, income, family, education, occupation etc. and brand loyalty.

The questionnaire was hosted on the researcher fs email and sent to 1,031 persons, that is to all the contacts on the email list of the researcher. The consumers sampled were literate and Internet users but were not confined to any geography or demography. From 1,031 the researcher received 384 responses of which 213 were found valid and error ]free. SPSS was used as a tool to analyse the survey results of the 213 responses.

The questionnaire was divided into two broad sections. The first section highlighted a person fs personal and social demographic profile while the second section highlighted respondents f profile as a consumer, based on shopping habits and purchase pattern. The pilot study was carried out with 15 respondents and the number of questions was reduced to 16 from 24, by removing overlapping questions and eliminating redundancies.

Customers f brand loyalty was assessed across various product categories individually to determine which product categories commanded high loyalties and which product categories did not have high loyalties, and whether these had any relationships with various socio ]demographic variables. Brand loyalty was measured through a single question that had multiple product categories on which respondents had to make a self ]evaluation. Self ]evaluation statements, simple and direct, were provided to aid the respondents to assess their loyalty. The meaning of high, medium, low and no loyalty was explained as follows: High Loyalty means the customer is addicted to the brand; Medium loyalty implies that the customer changes the brand occasionally; Low loyalty implies that they change brands often, and No loyalty implies that the brand does not matter to the customer at all.

Testing the hypotheses

The ANOVA technique was used to test the hypotheses, and accept or reject them. The threshold for the p value was taken as 0.05. The ANOVA table was created and the findings were explained for individual demographic factors.

Findings and discussions

A detailed analysis of the survey was carried out. Table 1 shows sociodemographic description of respondents.

In order to understand the list of the top most loyal product categories, we have asked respondents to indicate their loyalty towards various categories. Table 2 depicts respondents' loyalty scores. Values closer to 1 indicate very high loyalty, closer to 2 indicate medium loyalty status. Categories where customers have indicated moderate loyalty (score of 2 and above) or low or no loyalty (score of 3 or 4) have not been considered for this analysis keeping in mind the objective of attempting to establish a relationship between high loyalty and demographic factors. Conversely, if no relatedness is established between high loyalty product categories and demographic factors, then it automatically implies low or statistically insignificant loyalty. These scores also highlight the extent of loyalty customers have with respect to each product category. This could be an important input when decisions are made about: marketing, promotion and CRM investments, especially in large multi ]brand companies or at multi ]brand retailers.

Mean scores from Table 2 broadly indicate that customers are highly loyal when it comes to products they use personally. In this context Jain and Sharma (2012) have suggested that customers tend to be more loyal with products they use more often and more closely. The survey has highlighted that personal care products have highest customer loyalty at a mean score of 1.27 (against an ideal score of 1.00 for highest loyalty). The eight product categories where customers have indicated high loyalty are automobiles, cleanliness and hygiene, high ]end technology gadgets, perfumes, alcohol, health and fitness and beverages, almost all of which are used for personal consumption, including the categories of personal transport and high technology gadgets.

Analysis of the relationship between socio-demographic factors and product categories

Further, a comprehensive relationship analysis was made using the topmost categories obtained earlier and with socio demographic factors. Pearson's correlation factor was used to study the extent and strength of relationships. Table 3 depicts this correlation value.

Data analysis indicates the highest negative relationship value of -.452 is seen between income and loyalty for personal care products implying fair relationship strength. The negative relationship means the lower the income levels, the higher the loyalty to a brand. Almost all other values indicate a weak relationship between income and loyalty. However this loyalty could be limited to the extent of the amount the customer pays for the brand. Culturally, Indian customers love to save money on every purchase; their focus is value shopping. Peterson (1995) described consumers enter into a marketing relationship only because they expect to receive positive value from their participation. And, monetary value is one of them.

The highest relationship value of .496 between education and loyalty indicates a fair relationship strength and its positive value implies that the higher the level of education, the greater the loyalty of customers to a brand of personal care products and vice versa. Williams et al. (1990) have concluded that in any marketing or sales situation the most important factor that decides the outcome is the communication strategy, and a good message strategy makes the customers more informed on their choices. This implies that when customers make an informed choice of a product or service brand they tend to stick to their decision through a period of time, resulting in repeated purchases, as they are sure of their choice. This also implies that they are not much swayed by tempting promotions of competitive brands. Though loyalty for all the other product categories is insignificant, just alcoholic drinks, beverages and supplements, and health and fitness categories is just around .3 indicating a very weak relationship.

There is a high correlation value of .605 and .623 indicating a moderately strong relationship between the number of members of a family with personal care products and high technology personal use gadgets loyalties respectively. The positive value in both cases indicates that the higher the number of family members, the higher the loyalty factor for these categories. The result here suggests that in these two categories of products the family prefers to buy the same product or brand than to opt for variety. All other correlations are insignificant indicating a weak relationship.

The results indicate that the correlation between age and all product categories is virtually nonexistent, with just personal hygiene products having a borderline relationship value of .396 indicating that the older the customer grows the more loyal the customer is in this category. This could indicate a reluctance to shiftloyalty when it comes to products of personal hygiene, and that they prefer to buy products and brands they have always been buying. A lower age group is indicative of shifting loyalties, and possibly the impulse to try something new all the time. This factor alone could be a very important indicator of choices and preferences of the youth customer market.

Though there is fairly strong correlation between loyalty and type of residence of a customer with respect to personal care products (.553) and high technology gadgets (.504), there is little or no strength in relationships with any other product category, barring personal hygiene products on the borderline (.306). However the study does not indicate conclusively (because it was not designed for this purpose) whether the correlation is positive or negative and if the alteration in the strength of the relationship is depending on nature of accommodation.

There is no significant relationship between the profession of a customer and his or her loyalty in a product category. All relationships are extremely weak irrespective of a positive or negative value. Equally significantly there is no relationship between the professional hierarchy of a customer and his or her loyalty in a product category. All relationships are extremely weak irrespective of a positive or negative value, except for health and fitness (.332), perhaps suggesting that the higher people go up the management ladder the more they think of health and fitness options as valuable to their living.

However, there is no relationship between the lifestyle habits of a customer and his or her loyalty in a product category. All relationships are extremely weak irrespective of a positive or negative value, except in the personal hygiene category (.384) and the health and fitness category (.404). However the study does not indicate conclusively (because it was not intended to do so) whether the correlation is positive or negative with respect to each lifestyle habit and what the alteration in the strength of the relationship could be.

There is no significant relationship between the social personality of a customer and his or her loyalty in a product category. All relationships are extremely weak irrespective of a positive or negative value, except in the personal hygiene category (-.433) and the high technology gadgets category (-.509), both of which are fairly strong. However there is a negative correlation indicating that highly analytical customers are less loyal and expressive customers are more loyal. This is an interesting and important indicator of a customer's personality and how CRM strategies can be tuned taking the personality profile into account.

Several past studies also echo the findings of the current study. Roberts (2012) has categorically proven that no significant correlation exists between customer loyalty and demographic and socio-economic variables, in the context of banking services. In an IBM report, customer experience was identified as a key for companies to use in building loyalty to brands, channels and services (Badgett et al., 2007), rather than socio-economic factors. Roberts-Lombard and du Plessis (2012) have also stressed on the two main factors that impact CRM, namely behaviour and attitude. They, however, do not highlight the demographic factors as being directly responsible for customer responses to CRM efforts. In another study Corbishley and Mason (2011) have also corroborated the fact that demographic factors such as age, education, income and family do not have a significant impact on loyalty or CRM.

Using ANOVA to determine the F and p values to accept or reject the hypotheses, we found that in nine cases the p values were greater than 0.05, indicating that the null hypotheses should be accepted and that there was no relationship between the specific demographic variable and brand loyalty.

Conclusions

Managerial implications: The present study is significant for marketing and CRM managers, as it discusses the fact that no product category attracts very high brand loyalty as evident in the relationship values shown in the study. The three most vital factors that marketers consider while formulating their STP (segmentation, targeting and positioning) strategies and subsequent customer communications are age, income and profession. With respect to all these demographic factors the values indicate at best fair if not poor strength of the relationship, implying insignificant relationship between loyalty and each of those factors. Even direct or inverse relations were insignificant.

We would like to state that this is perhaps in tune with the latest tendency of consumers who care more about themselves and their own welfare, and are highly brand conscious when it comes to self-usage of products. The fickle nature of customers, especially in the younger age group highlights that loyalty is not permanent, and their choices tend to keep shifting based on other market stimuli.

Limitations and scope for future research: The present study is not without its limitations. In fact, though the questionnaire is vast and attempts to cover the entire gamut of customer socio-demographics and establish a relationship with loyalty, it has not attempted to answer the question of why customers display individual loyalty to product categories. The reasons for this could be many, and this line of study has not been covered in the present case. Though the questionnaire included factors such as 'Number of family members living with customer', and 'Residence type of the customer', it did not make an attempt to explore whether individual characteristics of each of the options provided had an impact on loyalty. Similarly though the questionnaire contained questions on shopping and spending habits of customers, we decided to leave the responses outside the purview of the present study as it was seen to be diluting and deviating from the core objective of customer loyalty and demographic factors. This could be taken up as a separate study in the future.

This study considers only demographic factors as determinants of customer loyalty and does not take into account the relevance of demographic factors compared to price and other marketing factors. While the researchers understand that brand loyalty may play a minor role in buying decisions due to similarities of brands, other factors were not considered for the present study as it would have been outside its stated scope. The fact whether there is or there is not a transfer of brand loyalty from parents to children in the case of household products has not been investigated as it was considered to be outside the present purview. Similarly, brand loyalty with respect to the country of origin of a brand has not been considered.

The current study also does not consider customer loyalty towards single brands or umbrella brands. This distinction can be taken up as a separate study.

Moreover, though the objective is to study whether customer loyalty is a myth or reality, according to the analysis it appears as though customers do not have strong or intense loyalty towards any category (also determined based on the strength of the relationship represented by the correlation coefficient), but this does not mean that customer loyalty as a marketing objective is flawed. Another aspect that can be taken up for future research is the relationship between CRM efforts in individual product categories. The present study has triggered a debate: Does lack of loyalty mean more CRM spending or less? If yes, then in which product categories?

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