Kathy Hammond

Customer loyalty and customer loyalty programs

Customer loyalty presents a paradox. Many see it as primarily an attitude‐based phenomenon that can be influenced significantly by customer relationship management initiatives such as the increasingly popular loyalty and affinity programs. However, empirical research shows that loyalty in competitive repeat‐purchase markets is shaped more by the passive acceptance of brands than by strongly‐held attitudes about them. From this perspective, the demand‐enhancing potential of loyalty programs is more limited than might be hoped. Reviews three different perspectives on loyalty, and relates these to a framework for understanding customer loyalty that encompasses customer brand commitment, customer brand acceptance and customer brand buying. Uses this framework to analyze the demand‐side potential of loyalty programs. Discusses where these programs might work and where they are unlikely to succeed on any large scale. Provides a checklist for marketers.

Internet usage: Predictors of active users and frequency of use

Abstract The factors that predict Internet usage patterns are explored through the use of consumer panel data. We look at two major aspects of usage behavior; active (current) versus lapsed usage and usage frequency among current users. We find that the main predictors of active or current use of the Internet are: • Time since first use of the Internet. Pioneers (very early adopters) are most likely to be active users. However, the relationship is not a linear one; middle adopters are more likely than other groups to have not used the Internet in the previous month. • Location of use. Social use at home, especially with two or more other people. • Specific services used. Personal communication is the most popular activity (used by just over half the sample), but the best predictors of active users are use of information services. The main predictors of frequent or heavy Internet use (20+ times per month) are: • Broad applications, e.g., business email followed by personal email. • Time since first Internet use. The relationship here is linear; the longer someone has used the Internet, the more likely they are to be a heavy user. • Location of use. Use at work and use at home with two or more other people are both strong predictors of heavy usage.

Consumer Loyalty: Singular, Additive or Interactive?

Abstract Consumer loyalty may be defined as a singular concept, usually as an attitude toward the loyalty object or as repeatpatronage behaviour; alternatively, the definition may combine attitude and behaviour in either an additive or an interactive expression. We argue that definitions of loyalty are useful if they predict phenomena such as recommendation, search and retention (loyalty outcomes). In three consumer fields, we find that combination measures of customer loyalty often perform poorly as predictors of loyalty outcomes compared with singular measures since recommendation is predicted by attitude but not by repeat patronage, whereas retention and search behaviour are predicted better by repeat patronage than by attitude. We also find that the prediction of loyalty outcomes is not improved by the inclusion of an interaction term in the model. On this evidence, we argue that combination concepts of loyalty are of limited value. Further, we find that there is no form of loyalty that consistently predicts all the different loyalty outcomes and, therefore, we should abandon the idea of a general concept of loyalty.

Market segmentation for competitive brands

Although market segmentation is widely described as a major marketing tool, questions whether brands which are broadly similar and competitive are bought by identifiably different consumer segments. Notes that few, if any, examples of marked brand segmentation are cited in the literature. Reports on a new international study of the characteristics of brand purchasers in over 20 grocery product categories using consumer panel data, which reveals that there is little brand segmentation. Finds that the consumer profiles of competitive brands differ little in terms of the commonly‐used classification measures such as socio‐demographic characteristics, and that brands in the same product category tend to be bought by similar kinds of people.

A replication study of two brand-loyalty measures

Abstract In a systematic check across 34 US product categories, two standard measures of brand-loyalty are found to be closely predictable from the Dirichlet model of buyer behaviour in most cases. This means that market share is generally the dominant factor, but that there are also certain submarkets and isolated deviations. The general role of replication studies is also briefly considered.

The Erosion of Repeat-Purchase Loyalty

A large-scale longitudinal analysis is used to study the repeat-purchase rates of brand buyers in stationary markets. The data cover the leading brands in a number of frequently purchased grocery categories in three countries. We find that, in the medium term, there is a systematic but limited loss of repeat-purchase loyalty; across nine markets, erosion (the proportionate fall in repeat-purchase loyalty) averages 15 percent in the first year for the brands studied. Erosion does not differ by weight of purchase: similar rates are found for light, medium, and heavy buyer-segments. Brand leaders are found to have a lower erosion than smaller brands.

Correlates of first‐brand loyalty

A mail survey of British supermarket customers shows that the factor most strongly associated with claimed brand loyalty is household income Brand loyal customers also claim to spend more, are more concerned about quality and less about price, are slightly more store loyal and make more use of large out‐of‐town stores Brand loyalty is also related to age; those aged under 25 years and 65 + years are less loyal There is little difference between those who are primarily loyal to store brands and those who are primarily loyal to manufacturer brands, and there is little evidence that store patronage is raised by loyalty to store brands

Grocery store patronage

Various aspects of how shoppers patronize grocery stores are regular and predictable, so much so that the pattern of buying at a particular store can be interpreted against known patterns at other stores, and against a very general model, the NBD-Dirichlet. For the grocery manager this means using scanner-panel records to assess patronage against a number of benchmark or norms. Both the substantive findings and the methodological considerations are discussed in the hope that this work will encourage further of the approach

Fact and Fallacy in Retention Marketing

We review the claims that have been made to justify an emphasis on customer retention in marketing. First, we show that, in many consumer markets, the available evidence gives little support to the argument that long-tenure customers are of more value than short-tenure customers. Second, we argue that it may be difficult to influence long-tenure customers profitably. Third, we consider the evidence that increases in customer satisfaction lead to increases in profit for a firm. The connection between satisfaction and profit has been explained as the result of increased customer retention but we find little evidence to support this claim. A counter view is that increases in customer satisfaction affect profit because they raise recommendation and, as a result, customer acquisition. For these reasons, we suggest that, in many categories, new customers may have been undervalued and that more attention should be given to customer acquisition

B2C e‐Commerce 2000 2010: What Experts Predict

This article reports on a series of annual surveys of how a panel of experts expect usage of online channels to develop between now and 2010 in Europe and North America. The bursting of the internet bubble is not expected to reduce consumer usage of the Web for e-commerce. Indeed, in the latest survey, the experts again revise upwards their earlier predictions of European online adoption and usage in the home. The survey covers the following: online access at home; consumer choice of access channels; volume of e-commerce and each channels relative importance; the impact of mobile; barriers to B2C e-commerce; and regional differences.