The sparse previous emplace research on the multi-channel experience focuses on consumer markets and does to explicitly measure multi-channel integration. Our research design involved a survey of 579 small and medium-sized business customers of a large high-technology service provider and takes into account both the web channel and the sales force, with sub-samples for companies served directly and those served via an intermediary. This research concludes that multi-channel consistency has a strong Impact on customer satisfaction.
Choice among channels, satisfaction with those individual channels, product satisfaction and payment equity are also factors that influence overall satisfaction. These findings hold both for direct customers served by the provider’s own sales force and for indirect customers, where consistency between the intermediary’s sales force and the supplier’s website is equally important. We suggest that practitioners should therefore track and optimism both the individual channel experience and multi-channel Integration.
We call for further research replicating this work In other Industry contexts Including consumer markets to assess the generality of our findings. KEY WORDS : marketing Customer satisfaction, multi-channel marketing, channel Integration, Industrial Introduction With the progressive development of information technologies, customers are being offered multiple channels through which to engage with suppliers. Payne & Frown (2005) have identified 21 common modes of contact between companies and customers, from the sales force to text messaging.
It has been asserted (Payne & Frown, 2004; Souse & Voss, 2006) that companies must therefore achieve multi-channel customer relationship. To test this assertion, this study set out to ascertain the impact of channel satisfaction Correspondence Address: Hugh Wilson, Cornfield School of Management, Cornfield, Bedford MAKE AOL, I-J. Email: Hugh. wilson@cranfield. C. UK 1478-3363 pant/1478-3371 online/07/08091 5-11 # 2007 Taylor & Francis DOE 10. 1080/14783360701350938 916 R. Madeline et al. And multi-channel integration on relationship quality, as measured by overall customer satisfaction, within a multi-channel BIB environment.
Multi-channel integration involves ‘providing an integrated system capable of handling multiple channels of operation for an enterprise’ (Ganges, 2004: 142). A multi-channel integrated strategy requires decisions about the number of channels to adopt, the nature of the interactions between them and what channels will be offered to customers for what purposes (Inclines et al. 2006), and the assurance that the customers experience positive and consistent interactions with all of them (Payne & Frown, 2005). Wallace et al. 2004) argue that having channel choice enhances customer satisfaction, whilst Payne & Frown (2004: 533) assert that the absence of a consistent experience across channels can Jeopardize business relationships: Any incoherence or conflict between channels will confuse the customer who may misinterpret the offering, potentially diminishing the customer’s view of the company. The literature dealing with multi-channel integration in CRM is, however, limited in OTOH volume and scope (Astrakhan & Sanchez, 1998; Friedman & Furry, 1999; Kraft, 2000; Wagner, 2000; Funk, 2002). Moreover, this literature is largely conceptual in nature.
There is a need for empirical research into the experience of customers in dealing with multiple channels and how, if at all, channel choice and channel consistency influence customer satisfaction. Some work has been done within the retailer- consumer relationship, although mainly focusing only on the web channel on, or in Juxtaposition to, a single offline channel such as retail stores (Montana-Weiss et al. , 2003; Shank et al. , 2003). Montana-Weiss et al. 2003), for example, found that service quality both online and offline was associated with overall customer satisfaction.
These studies provide useful methodological precedents, but there is a need to extend this work to establish whether or not BIB relationships follow similar dynamics, and to examine specifically the issue of multi-channel consistency – or multi-channel integration quality as it is termed in a conceptual paper by Souse & Voss (2006: 356): . . Customer experience is formed across all moments of contact with the customer across several channels. Integration Quality is identified as a key new service impotent. Customer satisfaction within a BIB context.
More specifically, it examines the effect that the perceived choice of channels and consistency of the multi-channel experience has on overall satisfaction. Satisfaction with the individual channels, product satisfaction and payment equity are also factors that are considered as influences on overall satisfaction. Conceptual Model and Hypotheses Our conceptual model is shown in Figure 1. The dependent variable of customer satisfaction is conceptualized as overall satisfaction of the customer with the supplier based on the total purchase and consumption experience
Customer Satisfaction in a Multi-channel BIB Environment 917 Figure 1. Determinants of customer satisfaction in a multi-channel BIB environment with a good or service over time (Foretell, 1992; Shank et al. , 2003). This, as Figure 1 illustrates, is regarded as a product of multi-channel integration, product satisfaction and payment equity, which we will discuss below. Channel satisfaction is the customer satisfaction with the experience of dealing with any given channel individually; the relevant channels in this study are described in the next section.
This construct draws upon Montana-Weiss et al. (2003), whose study e extend to the BIB context: Channel satisfaction with individual channels impacts positively on customer satisfaction. The first aspect of multi-channel integration which we consider is cross-channel consistency. Payne & Frown (2005) argue that giving customers a positive and consistent service experience across channels is essential to the quality of the customer relationship. However, there has been very little empirical research to verify this contention. A recent contribution was made by Stuart-Eminent et al. 2005), who measured service quality across several BBC channels and the impact on the consumer relationship. They concluded that the quality and consistency of experience across multiple channels affects customer satisfaction and the longevity of supplier- consumer relationships. Whilst these results are of great interest, the authors reported some significant limitations: the sample comprised only 61 respondents; no specific measure of consistency was used; and it was not known whether these results would apply to the BIB context.
Hence: H2O A consistent experience across channels impacts positively on customer satisfaction. 918 Channel choice concerns customers’ awareness of the options they have in dealing tit a supplier. Several authors argue that customers wish to exercise a choice over alternative channels offered by a given supplier (Friedman & Furry, 1999; Nines & Speeds, 2003; Myers et al. , 2004). Wallace et al. (2004) found consumers to believe that retailers offering multiple channels were better able to satisfy their needs and thereby increase customer loyalty.
Their study concluded that customers using three or more channels of communication with a company feel 66% more committed than those using only a single channel. Moreover, these customers believe the service delivered is 34% better. The multi-channel customers’ expectations are also higher: the more they deal with the company, the more they expect the company to know about them and give them individual service (Hassock, 2001). Channel choice, then, may influence customer satisfaction levels in several ways, but again the pool of literature is small and focused on supplier- consumer relationships.
There is a need to extend the literature and specifically to establish whether or not channel choice is as influential in the BIB context as it seems to be in BBC: HE Perceived channel choice impacts positively on customer satisfaction. Product satisfaction – the customer’s satisfaction with the product or service being purchased itself – is unsurprisingly hypothesized to be part of the overall customer experience, which contributes to overall satisfaction (Stuart-Eminent et al. 2005), as is payment equity, or the extent to which customers believe that the price paid for the firm’s products or services is fair (Bolton & Lemon, 1999; Overshoe, 2003). These authors have empirically shown that customers’ perceptions of the fairness of a given supplier’s prices are formed relative to both the level of prices charged by interiors and the modus operandi of the pricing mechanisms used by these alternative suppliers. Therefore: HE Product satisfaction impacts positively on customer satisfaction. Payment equity impacts positively on customer satisfaction.
Method The empirical work was carried out with the cooperation of a large high-technology company providing services and physical products to I-J Seems, with the majority of revenue coming from services. For two consecutive months, around 15,000 of its small to medium-sized business customers were contacted by telephone with a request to respond to a survey. The first month resulted in 1194 firms responding whilst the second yielded 1052 completed questionnaires. However, not all of these respondents were multinational customers: of the respondents, 579 had sufficient these formed the basis for the regression analysis reported below.
All of the company’s SEEM customers can use its website. In addition, they can deal with a sales force which, depending predominantly on the size of the customer, is either a direct sales force or one owned by an intermediary. These intermediaries in turn divide into two categories: agents, who operate under the company’s brand and ell only its products; and resellers, who are independent companies that sell products and services from several 919 suppliers, including the company studied.
The survey therefore included subleases in each of three categories: direct sales force customers; agent customers; and customers of resellers. The company’s SEEM customers are also able to make use of a recently added third channel, a central call centre; however, insufficient customers in the sample had made use of this channel for the responses to be included in the study, so this variable was dropped from the analysis. Measures All items were on seven-point Liker scales. Product satisfaction was measured with a single item derived from Stuart-Eminent et al. (2005).
A two-item scale for payment equity was adapted from Overshoe (2003). Overall customer satisfaction was measured by a ten-item scale adapted from Montana-Weiss et al. (2003). Standard procedures were followed to construct multi-item scales for the two constructs for which measures were not available from previous studies: channel choice and crosshatches consistency. Channel choice was measured by two items: ‘l can choose among a range of channels when dealing with [company]’; and ‘Regardless of the sales Handel I use to purchase from [company], I can use other channels to get information or help’.
Cross-channel consistency was measured by three items inspired by Payne & Frown (2005): ‘Regardless of the channel I use, people are informed about my past interactions with [company]’; ‘The information I get from [company] is consistent across all channels’; and ‘l have a consistent impression of [company] regardless of the channel I use’. The reliability of those variables whose measures were the product of a multi-item scale was tested using Cockroach’s Alpha. Thus this test was applied to the variables channel choice, channel consistency, moment equity and customer satisfaction.
In the case of customer satisfaction, reliability analysis indicated that Cockroach’s Alpha scale could be further improved if one of the items were deleted: this was done. Factor analysis was also conducted using principal components analysis with Bavaria rotation, and verified that the scales designed to measure those constructs did indeed correspond to the same factors. Inter-variable correlations are shown in Table 1, while Cockroach’s Alpha scores are shown in Table 2. The associations between channel satisfaction, multi-channel integration, product efficient.
Multiple regression was then conducted involving variables that showed a correlation that was significant at the 5% level. NOVA was employed to test the significance of the overall regression equation. The model’s F-statistic, and an indication of its attendant significance level are displayed in Table 2. Where the significance of a regression model was established, the partial correlation coefficients for the individual variables comprising that model were studied. Since all of the variables relate to measures on a 7-point interval scale, the unsubstantiated coefficients were used.
Where the t-values of these partial correlates are significant then they become indicators of the relative importance of particular variables to the customers. Four models were created. The first of these involves all types of customer irrespective of whether they dealt directly with the supplier or through agents or resellers. The second model focused solely on those customers who primarily dealt with the company directly. The third and fourth models were constructed around customers who deal through an agent 920 Table 1 . Correlation coefficients for each of the variables in the conceptual model Standard Mean deviation
