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There is general agreement among researchers and practitioners that satisfaction is relative to competitive alternatives. Nonetheless, researchers and managers have not treated satisfaction as a relative construct. The result has been weak relationships between satisfaction and share of wallet in the literature, and challenges by managers as to whether satisfaction is a useful predictor of customer behavior and business outcomes. The purpose of this paper is to explore the best approach for linking satisfaction to share of wallet.

Using data from 79,543 consumers who provided 258,743 observations regarding the brands that they use (over 650 brands) covering 20 industries from 15 countries, various models such as the Wallet Allocation Rule (WAR), Zipf-AE, and Zipf-PM, truncated geometric model, generalization of the WAR and hierarchical regression models are compared to each other.

The results indicate that the relationship between satisfaction and share of wallet is primarily driven by the relative fulfillment customers perceive from the various brands that they use (as gauged by their relative ranked satisfaction level), and not the absolute level of satisfaction.

The findings provide practical insight into several easy-to-use approaches that researchers and managers can apply to improve the strength of the relationship between satisfaction and share of wallet.

This research provides support to the small number of studies that point to the superiority of using relative metrics, and encourages the adoption of relative satisfaction metrics by the academic community.

This study aims to provide the first longitudinal examination of the relationship between affective, calculative, normative commitment and customer loyalty by using longitudinal panel survey data.

Repeated measures for 269 customers of a large financial services provider are employed. Two types of segmentation methods are compared: predefined classes and latent class models and predictive power of different models contrasted.

The results reveal that the impact that different dimensions of commitment have on share development varies across segments. A two-segment latent class model and a managerially relevant predefined two-segment customer model are identified. In addition, the results demonstrate the benefits of using panel survey data in models that are designed to study how loyalty develops over time.

This study illustrates the benefits of including both baseline level information and changes in the dimensions of commitment in models that try to understand how loyalty unfolds over time. It also demonstrates how managers can be misled by assuming that everyone will react to commitment improvement efforts similarly. This study also shows how different segmentation schemes can be employed and reveals that the most sophisticated ones are not necessarily the best.

This research provides the first examination of models for change in customer loyalty by employing survey panel data on the three-component model of customer commitment (affective, calculative, and normative) and considers alternative segmentation methods.

This research aims to investigate the moderating influence of both multichannel and multicompany usage on the impact that customer satisfaction has on share of wallet (SOW).

The data used in the analyses were collected as part of both survey and transactional data of 802 households of a large financial services provider. Within class regression models were employed to test the moderating effects of different segments that were identified based on multichannel‐multicompany customer differences.

The findings confirm that using multiple channels has an overall positive moderating impact on the satisfaction‐SOW link and that customer satisfaction matters more when the customer adopts multiple channels; online channel usage in addition to offline usage. Furthermore, this effect is even more pronounced for customers that transact with multiple providers. That is, the group of customers that use both the company's and competitors' offline and online channels reveal a higher satisfaction‐SOW association than the group of customers that only adopted the offline channel with the company and competitor.

This study broadens the understanding of multichannel behavior by comparing single (offline) and multiple channels (offline and online) for customers of multiple companies (two competitors).

The purpose of this research is to examine changes in, and consistency of customer and employee satisfaction for asymmetry with regard to sales changes for a large US specialty goods retailer.

The data came from a 125 store US specialty goods retailer. Customer and employee data represent surveys administered by the firm in 2000 and 2001. Over 34,000 customer questionnaires and 3,900+ employee questionnaires were collected for the study. Pearson correlations and CHAID analyses were used to test the hypotheses.

For satisfaction (employee and customer) to impact changes in sales, perceived performance standards on some dimensions must be consistently delivered and changes in satisfaction levels must cross attribute‐specific threshold levels.

As the data comes from a single retailer, it is not possible to conclusively generalize these findings to all other retailers, or to other industries.

For managers, the typical reliance on simple mean employee or customer satisfaction scores or indexes is unlikely to adequately explain changes in sales. Managers must achieve satisfaction levels on those attributes where consistent performance is linked to sales. Additionally, given the threshold nature of the relationship, it is critical that managers be certain that efforts designed to improve satisfaction do so in sufficient force so as to reach levels that correspond with increasing sales.

While the literature has shown asymmetry in the relationship between customer satisfaction and customer behavior, to date no research has examined possible asymmetry in employee satisfaction data and business performance. Furthermore, analyses of asymmetry in customer satisfaction data have largely focused on cross‐sectional data and individual‐level customer data (as opposed to business performance indicators). Understanding the asymmetric nature of the examined relationships should result in better allocation and use of marketing resources.

The purpose of this research is to examine different customer satisfaction and loyalty metrics and test their relationship to customer retention, recommendation and share of wallet using micro (customer) level data.

The data for this study come from a two‐year longitudinal Internet panel of over 8,000 US customers of firms in one of three industries (retail banking, mass‐merchant retail, and Internet service providers (ISPs)). Correlation analysis, CHAID, and three types of regression analyses (best‐subsets, ordinal logistic, and latent class ordinal logistic regression) were used to test the hypotheses.

Contrary to Reichheld's assertions, the results indicate that recommend intention alone will not suffice as a single predictor of customers' future loyalty behavior. Use of a multiple indicator instead of a single predictor model performs better in predicting customer recommendations and retention.

The limitation of the paper is that it uses data from only three industries.

The presumption of managers when looking at recommend intention as the primary, even sole gauge of customer loyalty appears to be erroneous. The consequence is potential misallocations of resources due to myopic focus on customers' recommend intentions.

This is the first scientific study that examines recommend intentions and its impact on retention and recommendation on the micro (customer) level.

This paper aims to examine call center satisfaction in an escalated call center context where callers are organization members of the primary/leveraged brand and have purchased additional co‐branded services as part of their membership. It also aims to examine the relationship between call center satisfaction and actual retention of both the co‐branded service offered and the primary brand (call center operated by the membership organization).

The survey data used in the analyses involve a sample size of 88 respondents, all members of a large, national nonprofit organization in the USA. Factor analysis and logistic regression were used to test the propositions.

The results indicate that caller satisfaction has four dimensions similar to those found in SERVQUAL. Although call center satisfaction dimensions are not significant for co‐branded service retention, the empathy dimension is most important to primary/leveraged brand retention.

One of the limitations of this research is that it tests the propositions within a single firm regarding calls concerning a single category (insurance). Future research should attempt to replicate these findings in other call center contexts.

Caller perceptions of service quality (specifically empathy) in the wake of a perceived service failure, while not very helpful to co‐branded service retention, actually mitigate primary/leveraged brand membership loss.

This study addresses the lack of research tying escalated call center satisfaction and both retention of the co‐branded service in addition to retention of the primary leveraged brand using actual retention data.