Customer Defection From Supermarkets

Robert East, Kingston Business School
Patricia Harris, Kingston Business School
Wendy Lomax, Kingston Business School
Gill Willson, Kathy Hammond, Kingston Business School, London Business School
ABSTRACT - Defection by customers from their primary stores is investigated and compared with first-store loyalty using two mail surveys of supermarket customers. Retention (opposite of defection) and first-store loyalty are both positively correlated with attitude to the store and with brand loyalty. Customer’s age is positively associated with retention but negatively associated with first-store loyalty, while other correlates are not shared.
[ to cite ]:
Robert East, Patricia Harris, Wendy Lomax, and Gill Willson, Kathy Hammond (1998) ,"Customer Defection From Supermarkets", in NA - Advances in Consumer Research Volume 25, eds. Joseph W. Alba & J. Wesley Hutchinson, Provo, UT : Association for Consumer Research, Pages: 507-512.

Advances in Consumer Research Volume 25, 1998      Pages 507-512

CUSTOMER DEFECTION FROM SUPERMARKETS

Robert East, Kingston Business School

Patricia Harris, Kingston Business School

Wendy Lomax, Kingston Business School

Gill Willson, Kingston Business School

Kathy Hammond, London Business School

ABSTRACT -

Defection by customers from their primary stores is investigated and compared with first-store loyalty using two mail surveys of supermarket customers. Retention (opposite of defection) and first-store loyalty are both positively correlated with attitude to the store and with brand loyalty. Customer’s age is positively associated with retention but negatively associated with first-store loyalty, while other correlates are not shared.

Further investigation by sociodemographic segments reveals complex relationships. Income raises the first-store loyalty of the under-45s and lowers it for the 65+ group while retention is highest in the middle-income group for all three age groups.

This work indicates that we use the term 'loyalty’ to cover different customer behaviors that may have little in common; these behaviors have separate impacts on retailer profit and need to be distinguished by researchers and practitioners if they are to use behavioral data effectively.

INTRODUCTION

Loyalty is widely researched but variously interpreted and this study is concerned with evidence on store loyalty measured in two different ways, either as the proportion of total grocery spendingin the customer’s primary supermarket (first-store loyalty) or as the customer’s continuing to use a store over long periods of time (retention).

Customer retention merits research because of its association with profits and because it helps us to understand the nature of loyalty. Researchers have examined the reasons for defections (Reichheld and Sasser, 1990; Waterhouse and Morgan, 1994; Reichheld, 1996a, 1996b), the impact of product quality and consumer satisfaction on defection (Rust and Zahorik, 1993; Rust, Zahorik and Keiningham, 1995; Jones and Sasser, 1995), the loss of profit when customers defect (Reichheld, 1996a) and repatronage following effective complaint handling (Hoffman, Kelley and Rotalsky, 1995; Swan, Powers and Hansen, 1995).

In this stream of research we can see two different managerial objectives: first, to discover the reasons for defection and to use this information to improve the product; second, to segment customers by loyalty and associated expenditure and to use appropriate methods to raise the return from target groups of customers. The work reported here is related more to the second objective: we do gather the reasons given for supermarket defection but these reasons and our other investigations are focused on the identification of the customer segments that are more likely to defect. Such work is timely; the growth of loyalty schemes and their associated databases (Ainslie and Pitt, 1992) now permits the identification and automatic targeting of customer segments with particular spending profiles, including those that indicate defection. We will be better placed to use such technology when more is known about the factors that are associated with defection in supermarkets; evidence on this issue is limited but Seiders and Tigert (1997), in the United States, found that the switching of primary supermarkets ranged from 10 to over 50 per cent per year as retail environments became more competitive. Seiders and Tigert also note that trade data show a mean switching rate of about 25 per cent per year across the United States.

Loyalty schemes could have direct influence on customers, by increasing the proportion of expenditure directed to the store group with a scheme and/or by reducing defection. Some doubts have been expressed about the effectiveness of loyalty schemes (Uncles, 1994; Dowling and Uncles, 1997) but there is now some public evidence on their sales outcome; East and Hogg (1997) found that one successful scheme appeared to have its main impact on reducing the defection of supermarket customers rather than by raising sales per customer.

MEASURES OF LOYALTY

Store loyalty is a propensity to use the store. This propensity may be expressed as an attitude to the store or as an intention to use the store when circumstances permit. Behaviorally, the propensity is seen as a proportion of visits or expenditure compared with other stores or, over time, as retention-the continued use of the store. Other behavioral measures commonly used are the number of different stores used (an inverse measure) and the patronage rate-the average number of visits to a specified store made by patrons in a period of time, or the repatronage rate-the average number of visits in a subsequent period of time made by those using the store in a reference period.

However the fact that all these methods of measuring loyalty can be described as propensities to use the store does not mean that they correlate closely or even at all. Semantic coherence does not imply an empirical relationship; and even when measures are related they may still be associated with different consumer characteristics.

Attitude-Inclusive Measures

Jacob

Jacoby and Chestnut (1978), Day (1969), Dick and Basu (1994), Mellens, Dekimpe and Steenkamp (1997), have agued that the idea of loyalty embodies positive feeling; without an attitude in favour of the brand or store the loyal behavior is spurious. Dick and Basu have constructed a typology that retains attitude as a requirement for loyalty; they claim that true loyalty occurs when the behavior is supported by a strong attitude relative to the attitudes to other competitive brands identified by the customer. When this occurs, loyal behavior will be high, provided that there is no situational constraint. When money, social influence or product accessibility constrain repeat purchase, Dick and Basu define this potential loyalty as latent loyalty; if there is repeat purchase without positive attitude, the loyalty is spurious.

We are cautious about a combinatorial approach to loyalty. Measures of the same concept may be combined additively to produce a stronger measure, but attitude to a store and use of the store are different concepts, though each may cause the other or be associated through a common cause. Interactive combinations of measures may be used to create segments but our first concern is nomological: what relationships can be established between variables? This question cannot be answered if the variables to be related are combined in one measure.

Behavioral Measures

Proportional loyalty. Consumers generally use more than one brand in a category, and more than one store in a retail division, i.e. they have a portfolio (Ehrenberg, 1988). This multibrand/multistore pattern leads to the measurement of loyalty as a proportion of the portfolio expenditure; this approach is widely accepted for frequently purchased products but is also appropriate in other fields such as the use of airline, hotel and restaurant services. First-store loyalty (Cunningham, 1961) is the proportion of expenditure in the shopper’s primary store; this measure has been used by Dunn and Wrigley (1984), Mason (1991, 1996) and by East, Harris, Willson and Lomax (1995). First-store loyalty indicates the shopper’s exclusiveness of store use and should be negatively correlated with the number of different stores used in a period (Dunn and Wrigley found a correlation of -0.4). First-store loyalty may be measured as the percentage of customer spending directed to the primary store group or to the specific primary store. Store-group loyalty is slightly greater than single store loyalty; Mason (1991) found differences varying from three to seven percentage points over periods ranging from four weeks to a year.

Retention. Retention is the concept used by those studying the relative costs of keeping old customers and recruiting new ones (Fornell and Wernerfelt, 1988; Reichheld and Sasser, 1990; Reichheld, 1993; Jones and Sasser, 1995; Reichheld, 1996a, 1966b). In different ways many researchers and textbook writers have subscribed to this concept of loyalty; for example, it is implied in the early work by Brown (1953) on runs of purchase of the same brand, and Howard’s (1994) definition of loyalty 'the extent to which consumers shift among brands; specifically, it is the inverse of the amount of shifting’. However, 'shifting between brands’ conflates movement within a portfolio with true defection. This distinction is recognised in Brown’s (1953) division between divided loyalty (portfolio buying) and unstable loyalty where the shift arises from defection.

DETERMINANTS OF FIRST-STORE LOYALTY AND RETENTION

It is quite possible for a person to devote a relatively small proportion of expenditure to a store but to continue to use that store over long periods of time, or for proportionally heavy purchasers to defect more frequently than others. Reichheld’s (1996a) studies suggest that defections may occur as a result of mishaps such as a fault in the product purchased or a omplaint badly handled, and these failures need not be connected with proportional loyalty.

One factor that is likely to have quite different effects is the accessibility of the store. Shoppers using very large stores may travel considerable distances and show high first-store loyalty. However, the retention of a distant store is at risk from the development of more conveniently located stores and it is likely therefore that retention declines with the distance of the store from the consumer.

A second factor that could have rather different effects on first-store loyalty and retention is age. Mason (1991) and East, Harris, Willson and Lomax (1995) found that the under-45 age group was more first-store loyal. The 65+ age group was the least loyal according to Mason (1996). But retention among the under-45s might be affected by more frequent house moves because of job changing. Also new stores may be targeted at higher spending groups with families and this could have most impact on the under-45s. Thus retention could be directly associated with age even though first-store loyalty is not.

There may also be determinants in common for both proportional loyalty and customer retention; possible determinants are attitude to the store, restricted store choice, work pattern and temperament. Temperament and lifestyle factors, which encourage routine patterns of behavior, may explain the association that is found between brand loyalty and first-store loyalty (Cunningham, 1961; Carman, 1970; Rao, 1969; Uncles and Ellis, 1989; East, Harris, Willson and Hammond, 1995), and this association may extend to store retention.

Income has not been related to first-store loyalty or retention in studies. It is possible that it has a complex effect in relation to age. Young people, busy with their jobs and families, may be inclined to be first-store loyal because this simplifies their lives but those on low incomes may have to use more stores to reduce costs. If so, we would see most loyalty among the wealthier under-45s. Consumers who are 65+ may reverse this effect; for these people who have more time, shopping may become more recreational and the combination of age and income may reduce loyalty.

Finally, there are two measurement problems that will raise measured defection among those with a low first-store loyalty. When customers are equally loyal to two or more supermarkets they could name different stores on two occasions without any real change of primary loyalty having occurred, thus falsely raising the defection rate. Another false inflation of defection could arise from random variation in usage that temporarily changed the order of store use, and this effect would be strongest among those with more equal allegiances who are found in the low first-store loyalty groups.

From this review we see that a positive link between proportional loyalty and retention may be found but that such evidence could arise from artifacts. It appears more useful to focus on the correlates of the two forms of behavioral loyalty.

OBJECTIVES OF THE RESEARCH

This initial research on supermarket loyalty is exploratory and empirical. The objectives are to:

1. Identify the factors that forecast defection and compare these with the factors that predict first-store loyalty.

2. Assemble the reasons given by customers for their defection.

3. Show how levels of loyalty vary in different age-income segments.

METHOD

Surveys

Respondents were drawn from the electoral registers of England and Wales; the first female name at an address was used but the addressee was instructed that the questionnaire was to be filled out by the principal shopper in the household. A two-wave mail survey of supermarket patronage in England and Wales was conducted in February, 1994; this gave a 53 per cent usable response rate. In November, 1995, after excluding those who had removed identification or who did not use supermarkets, respondents were re-contacted using a two-wave and intervening reminder card procedure which gave a 71 per cent usable response rate. The analysis was conducted on the 551 households that responded to both surveys; these were 35 per cent of the 1994 sample.

Measures

First-store loyalty measure. Respondents were asked to assign themselves to one of four levels of loyalty; the question was:

What proportion of your                 Less than 50 percent [1]

total supermarket spending             50-80 percent [2]

is in the store that you                     81-95 percent [3]

use most often?                              More than 95 percent [4]

Respondents were divided into those with low (less than 81 percent) and high (81 per cent or more) first-store loyalty. [Mason (1991) shows that the distribution of store loyalties is weakly bimodal, which favors a binary split.] With this division 52% of the sample were high first-store loyalty (HFSL).

Customer defection. In both surveys respondents were asked to record the supermarket group that they most used. A comparison between responses in the two surveys therefore showed defections over the 21-month interval. This measure, like that used by Seiders and Tigert (1997), covers two sorts of defection: ceasing to purchase at the primary store group entirely, and demotion of the primary store group to a secondary preference. In the second survey respondents were also asked directly whether they had changed their main store in the last twelve months and whether the change was to another branch of the same store group or not. Those who had switched were asked to give the main reason for their change from a list of reasons that had been established by preliminary research.

First-brand loyalty. Another set of questions measured claimed first-brand loyalties in four categories. The categories used were toilet soap, toothpaste, breakfast cereals and washing-up liquid. Respondents were asked about their proportional loyalty to their preferred brand in each category. The responses for the four categories showed a Cronbach alpha reliability of 0.77 and a single first-brand loyalty measure was constructed for each respondent using the categories that were bought. If respondents claimed to have no usual brand their response was treated as less than 50 per cent.

Attitude to the store group most used. Following Dick and Basu (1994), we constructed a measure of attitude that was relative to the attitude to other stores and focused on store use following Ajzen and Fishbein (1977). Respondents were asked which supermarket group they would use if all were equally easy to get to. Those who named the store group that they currently used for their primary store were deemed to have a more positive attitude than those who named another store group.

Store accessibility. In this study respondents were asked how long it took them to get to the store and were given four response levels. [The measure of access time was applied to the store used for the last main shopping trip and in 16% of the cases this store was not the store used more often. This weakens the measure when it is applied, as here, to the store used most often.]

Other measures. In addition to the measures above, the questionnaires contained items on shopping frequency, weekly supermarket expenditures, routine times of shopping, perceived free time and demographic measures. Also, we asked whether the second questionnaire was answered by the same person in the household as the first questionnaire.

RESULTS

Data checks

Respondents. Although questionnaires were addressed to the same respondent in both surveys, a preliminary analysis was used to test whether a change in respondent affected outcomes. Irrespective of whether the respondent in 1995 claimed to be the same, was uncertain, or stated that she/he was not the same as the respondent in 1994, there were similar continuities of store-group usage. This indicated that reported household shopping behavior was relatively unaffected by possible respondent change and questionnaires from all three groups of respondents were used.

Recall of store change. 79 per cent of the respondents who recalled having changed their store group in the last twelve months were found among the 21-month changers. Double changers who revert to their first store group would not appear in the 21-month measure and in these circumstances the 12-month recall measure appears well based.

Defections within the store group. The questions about defection in the last twelve months were used to establish that 7 per cent of store switches were to another branch of the same group. This indicates that little bias will arise from the treatment of store group switches as though they were store switches.

General Findings

Overall, 35 per cent of respondents changed their primary store group in the 21-month interval. A change of 35 per cent over 21 months implies a change of 20 per cent over a year if the incidence of defection is constant, or greater than this if we allow for the reduction of the base as shoppers defect. The inclusion of those who switch within a store group would raise the figure further.

Store switching was associated with lower first-store loyalty measured in the first survey (p=0.00001) and with the number of different stores used in last four weeks (p=0.00003).

By taking mid-points of response levels an approximate first-store loyalty of 75 per cent was indicated at the first survey, rising to 78 per cent at the second. Store defectors had an average loyalty of 71 rising to 74 and non-defectors of 78 rising to 80 per cent. Those who switched did not change their first-store loyalty significantly more than those who did not switch (p=0.6).

Multivariate Analyses

We conducted logistic regressions on the 551 respondents to explain first-store loyalty and retention using a common roll of predictor variables. Table 1 shows that two factors, attitude to the store group and brand loyalty are the only shared predictors that operate in the same direction. Age has reversed effects. The time to get to the store increases the likelihood of defection but has no effect on first-store loyalty. Weekly spend raises first-store loyalty; thus high loyalty customers not only place more of their supermarket spending with their primary store but spend more in total in supermarkets and this makes them more attractive customers. A separate calculation indicated that the HFSL customers spent 70 per cent more in their primary stores than the low loyalty customers. Finally, there are two factors which are positively elated to first-store loyalty that may indicate a more habitual approach to shopping: those who have a regular time of day for shopping, and those whose choice of shopping day is guided more by environmental constraints (e.g. day not working, or day when the pension is paid) tend to have higher first-store loyalty.

These findings indicate that first-store loyalty and retention are rather differently based.

Income and Age

A three-way cross-tabulation was used to show the two forms of loyalty by age/income segments.

There are opposed income effects on the percentage of HFSL respondents in the under-45 and 65+ age groups. First-store loyalty rises with income in the under-45 age group and falls with income in the 65+ age group case. In aggregate (bottom row, Table 2) there is no effect. An analysis of variance was conducted on the first-store loyalty data using a measure of respondent’s free time as a covariant. This showed a main effect for age (F value 7.1, df 2, sig. 0.001), an effect for the 2-way interaction of age and income (F value 2.4, df 4, sig. 0.035) and an effect of free time (F value 6.9, df 1, sig 0.009). These results fit assumptions that the wealthier under-45s buy time by one-stop shopping and therefore have high first-store loyalty, and that the wealthier 65+ shoppers use their spare time to engage in more varied recreational shopping which reduces their first-store loyalty.

TABLE 1

LOGISTIC REGRESSIONS: FACTORS PREDICTING FIRST-STORE LOYALTY AND RETENTION

TABLE 2

PERCENTAGES OF HFSL RESPONDENTS BY AGE AND INCOME LEVEL

Table 3 shows that defection is higher among the poorest and richest groups in all three age groups. This is a non-linear relationship and therefore income did not appear in the overall regression analysis predicting defection. All columns of Table 3 show that defection declines with age. There is a slight negative correlation (r=-0.36) between first-store loyalty and retention for corresponding cells in Table 2 and 3.

Reasons for Defection

In the second survey, respondents who stated that they had changed their primary store in the last 12 months were asked to give the main reason for the change. The respondents’ reasons were grouped into access-related and other reasons. Table 4 shows these reasons and we see that nearly half are access-related (new store openings dominant, followed by moving house). Cross-tabulation showed that the 65+ age group was little affected by access factors, except for lifts to the store, and this helps to explain the lower defection in this age group.

DISCUSSION

Defection and Accessibility

Our data indicate a substantial primary-store defection rate in the range 20-25 per cent per year. This corresponds with the US figure of about 25 per cent cited by Seiders and Tigert (1997). over a third of the reasons given for defection were either new store openings or moving home which therefore emerge as strong influences producing defection. Store openings lessened after the study had been completed and the defection rate may have reduced as a result.

This evidence puts emphasis on what is meant by accessibility. The important question is how much extra time or distance is required for the shopping trip and further research should focus on the incremental effort required for trips to different supermarkets.

Retention and Proportionate Loyalty

Earlier, we drew attention to the wide variety of conceptual and operational definitions of loyalty. We have focused on first-store loyalty and store retention (strictly, store-group retention). Overall, these two forms of loyalty were associated; a higher first-store loyalty implied betterretention but the presence of artifacts and the error in survey responses make quantification of this relationship uncertain. When correlates of these two forms of loyalty were examined, brand loyalty and store attitude were common. Age raised retention and lowered first-store loyalty and other factors such as time to get to the store and spending level were not common. Such evidence indicates that an individual’s score on one form of loyalty is likely to be a poor guide to her score on the other.

TABLE 3

DEFECTION RATE BY AGE AND INCOME LEVEL

TABLE 4

MAIN REASONS GIVEN FOR CHANGING STORES

We also showed the two forms of loyalty for nine age-income segments. The evidence suggests that high first-store loyalty occurs when busy people (prevalent in the under-45 age group) simplify their lives by restricting the number of stores used. By contrast the 65+ group, with time on their hands, visit more stores; for this group, supermarket shopping may have a recreational aspect. Income had a different effect on retention which was higher in the middle-income segment than for either lower or higher income groups, and this was true in all three age groups; this pattern may reflect the relative stability of the lives of those in the middle-income group. However, the main thrust of this work was empirical and the explanations offered remain speculative. If these explanations can be sustained in further work, they have important consequences for the design of the store offering and the targeting of specific social groups.

Applications

The findings in Tables 2 and 3 have some use in projecting the long-term value of different customer segments where account is taken of spending level, first-store loyalty, retention and the proportions of consumers of different ages in the population. For example, the under-45 medium and higher income groups score quite well across these criteria and much better than the 65-plus groups. Facilities for younger families (such as child play areas) may selectively attract such high value customers.

More generally we are cautious about the applicability of loyalty findings. Evidence that a segment has a low defection suggests that attempts to get shoppers in that segment to change stores are less likely to succeed; similarly, those who more readily change stores will also be harder to retain after they have been recruited.

These considerations lead to two sorts of emphasis. One is long-term; the store offering should be designed and, at times, modified to attract greater numbers of more profitable customers (as defined by spending, first-store loyalty and retention). A second emphasis is to search for keys that will change the retention of customers so that they are 'locked in’. Managers may hope to achieve this with loyalty schemes but such aspirations are little more than marketing mantras until evidence is produced of real change in factors associated with retention. An increase in first-store loyalty might signal better retention but East and Hogg (1997), when investigating a successful loyalty scheme, found small changes in proportionate loyalty which were no more than those that might have been expected as a result of the increase in market share of the successful store group. Thus there was no 'excess’ proportionate loyalty that could be used to explain the increase in retention that was observed.

A search for 'retention predictors’ requires methods that give more precise measurement of the factors than is possible in a survey. Consumer panel data could be used to increase the accuracy of measures and to test whether changes in first-store loyalty have a quantifiable relationship to changes in retention. Thus confirmation and extension of this work is possible using panel data.

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