E-zines silence the brand detractors.
Loyalty is a person's willingness to make an investment or personal sacrifice in order to strengthen a relationship (Reichheld, 2001). For a customer, this can mean sticking to a supermarket that offers him good quality even if this supermarket is on the other side of town, but it can also mean putting one's reputation at stake in recommending a product to colleagues (Reichheld, 2001). Managers as well as researchers know that loyalty in general and positive product recommendation in particular increase profitability. According to Reichheld and Sasser (1990), companies can boost profits by almost 100 percent by retaining just 5 percent more of their customers. Satisfied customers talk up a company to their friends, family, and colleagues. Customers continue to purchase those products that satisfy them and influence the brand perceptions of those with whom they communicate (Richins, 1983). In this article, we explore to what extent electronic permission marketing can influence a customer's inclination to recommend a product to others. We do recognize that the relation between loyalty on the one hand and satisfaction or recommendation on the other hand is asymmetric (Oliver, 1999): although loyal consumers are most typically satisfied (or will recommend the product to others), satisfaction (or recommendation) does not universally translate into loyalty. For the remainder of this article, however, we will use Reichheld's recommendation factor (2001) as a proxy for consumers' loyalty. Reichheld (2001) stated that recommendation is one of the best indicators of loyalty because of the customer's sacrifice in making the recommendation.
Spontaneous product recommendation among customer networks is an important marker of company success (Creamer, 2006). Reichheld identified the difference between the percentage of brand promoters and the percentage of brand detractors as a strong predictor of long-term company success. The brand promoters are the customers who are enthusiastic enough to refer a friend or colleague. The brand detractors are the customers who are dissatisfied enough to spread negative word-of-mouth (WOM). Reichheld called this difference a company's recommendation factor. Because the recommendation factor is a compound measure (i.e., the difference between brand promoters and brand detractors), we next focus on the two parts of the recommendation factor separately.
The recommendation factor is positively influenced by the percentage of brand promoters. Brand advocates put their reputation on the line and will do so only if they feel intensely loyal. As "recommending" customers can bring in new customers at no charge to the company, a convenient path to profitable growth may lie in a company's ability to get its loyal customers to become its marketing department.
The recommendation factor is negatively influenced by the percentage of brand detractors. Detractors' responses include (a) switching brands or refusing to repatronize the offending store, (b) making a complaint to the seller or to a third party, and (c) telling others about the unsatisfactory product or retailer (Richins, 1983). Indeed the flip side of promoters' recommendations to friends or family is that detractors can spread negative WOM about a company's performance. Prior literature has shown that negative WOM can have detrimental effects on a business (e.g., Weinberger, Allen, and Dillon, 1981). The high credibility of the source (e.g., peer reference groups; Richins, 1983) seems to increase the impact of (negative) WOM in comparison with information received through commercial sources (e.g., advertising; Herr, Kardes, and Kim, 1991). In addition, this influence appears to be asymmetric because consumers seem to place more weight on negative WOM as opposed to positive WOM (e.g., Laczniak, DeCarlo, and Ramaswami, 2001; Wright, 1974). In sum, we conclude that the recommendation factor can be enhanced by increasing the percentage of promoters and by decreasing the number of detractors. In this article, we investigate the potential of permission marketing in turning nonpromoters into promoters or in turning detractors into nondetractors.
Countering a damaged reputation requires a company to seek growth through expensive shortcuts such as massive price cuts or other appealing incentives that will persuade skeptical customers to repurchase a product. Besides price cuts and appealing incentives, a company might reach out for diverse communication techniques to restore one's reputation. Mass communication and the proliferation of advertisements cause consumers to avoid advertisements in traditional media and on the internet. The so-called cluster-bomb approach of advertisements on the internet has been cited as an important cause of the trend toward declining consumer responsiveness to internet advertisements (Cho and Cheon, 2004). There is a potential for information overload in the information-rich and sometimes poorly organized environment (Dholakia and Bagozzi, 2001). A customer-related marketing strategy might be more efficient in convincing skeptical customers to remain loyal and repurchase a product or service. Particularly permission marketing, which allows the prospect to control and shape the communication received from marketers, might cause less resistance among detractors. According to Soars (2001), consumers are increasingly looking for personalization and for e-tailers to remember past interactions. On the other hand, consumers also desire the opportunity to have control over the information they receive and want the chance to exercise an opt-out privilege.
THE PRESENT STUDY
The effect of e-zines on the recommendation factor
A wide variety of e-commerce marketers are already implementing permission-based electronic newsletters or so-called e-zines as a way to inform customers about promotions or special services, to acquire new customers, to increase sales, and most importantly, to develop a "loyal" long-term relationship with their customers that might increase positive recommendation or decrease negative WOM. Nevertheless, to date, little research has been done that measures the impact of these e-zines on customer recommendation behavior. In this article, we want to investigate whether sending e-zines can enhance a company's recommendation factor.
We obtained the recommendation factor according to Reichheld's (2001) guidelines. Reichheld proposed to substitute a single question, "How likely is it that you would recommend company X to a friend or colleague?," for the complex box of the typical customer satisfaction survey. Reichheld developed a scale for this question where 10 = "extremely likely to recommend," 5 = "neutral," and 0 = "not at all likely to recommend." Working with this scale, Reichheld obtained three empirically defined clusters based on customer referral and repurchase behaviors: "(Brand) promoters," the customers with the highest rates of repurchase and referral, gave ratings of 9 or 10 to the question; the "passively satisfied" logged a 7 or an 8; and the "(Brand) detractors" scored from 0 to 6. In our research, Reichheld's recommendation index was measured twice to capture the effect of e-zines on customers' loyalty.
Volunteers could "opt in" by offering their email addresses to a market researcher after a short interview on the train. Some of them received e-zines and others did not. Each e-zine consisted of two business relevant articles and one lifestyle article. We investigated whether these e-zines had an impact on customers' inclination to recommend the product to others in light of their initial recommendation index. Our central hypothesis is that the application of e-zines will increase Reichheld's recommendation factor. Further, we will look at the four possible drivers of this expected e-zine effect: (1) Brand promoters receiving e-newsletters might be less likely to turn into passively satisfied customers. (2) Passively satisfied customers receiving e-newsletters might be more likely to turn into brand promoters, or (3) less likely to turn into brand detractors. And finally, (4) brand detractors receiving e-newsletters might be more likely to turn into passively satisfied customers. These four possible effects have in common that they would increase the overall recommendation factor.
The effect of "personalization" on the recommendation factor
In addition, we wanted to examine whether adjusting the content of the newsletters to the receiver's lifestyle could bring about additional effects on the recommendation factor. Hence in this research, we personalize the newsletter by including one article in line with the receivers' lifestyle and not in line with the receivers' interest in the product or service of the company.
Prior literature is equivocal with respect to the effect that we should predict. Although targeting and personalization strategies result in higher customer response and retention rates, permission marketers also must produce appealing and, above all, relevant communications to gain and keep loyal consumers (DuFrene, Engelland, Lehman, and Pearson, 2005; Tezinde, Smith, and Murphy, 2002). Customers tend to sign up for more services than they are interested in, which creates the need to cut back in the numbers of emails they receive. Because of this competition, message relevance is extremely important in promoting effective email marketing (Krishnamurthy, 2001). A strongly (lifestyle) personalized e-zine therefore may be perceived as being less relevant with respect to the company's business. As Fletcher and Peters (1997) point out: "The frustration experienced by consumers in providing personal information to a firm when this information appears to be disregarded and/or unrelated to the product/service offerings made by the firm, is a potential threat to relationship development which must not be overlooked or treated lightly" (p. 537). In sum, because of the inconsistencies in the literature, we keep this hypothesis exploratory.
Initially, 817 railway travelers (56 percent men versus 44 percent women, of which 81 percent were between 23 and 40 years old) answered Reichheld's recommendation index during a brief interview on the train (i.e., phase 1). Respondents were invited to "opt in" to receive further emails by providing the market researcher with their email addresses. Sixty-eight percent of the initial respondents gave permission to use their email addresses. Of the remaining 555 respondents, 137 were randomly assigned to the control condition and did not receive any newsletters; the other 418 participants were assigned to the experimental condition and received three e-zines in the following six weeks. The newsletters contained three topics. Two topics were related to the railway, and the third topic was a lifestyle topic that was either personalized in line with the respondent's lifestyle or not. After this period, the total sample received a closing email with the second measurement of Reichheld's recommendation index (i.e., phase 2).
In phase 1, railway passengers traveling to or from Brussels were approached to complete a written questionnaire. This questionnaire included Reichheld's recommendation index and questions concerning the respondent's traveling behavior, personal attitudes, and demographics. The traveling behavior questions probed (1) the specific train ticket, (2) the reason for traveling, and (3) the frequency of traveling by train. The personal attitudes section latched onto (1) the respondent's favorite radio channel, (2) favorite TV channel, (3) favorite movie genre, (4) favorite sports, and (5) the respondent's hobby. Each question had five possible response categories. The attitudes were used to personalize the e-zines, as described below.
Throughout the six-week campaign, three e-zines were sent every fortnight in the name of the Belgian railway company NMBS. A professional online advertising agency created the e-zines. Every newsletter contained three teasers with a link to an article. The first article described new or less known services of the railway company. A second article discussed investment projects in the area of Brussels. The third and final article dealt with lifestyle issues (see Table 1).
Within the experimental condition (i.e., those who received three e-zines), we manipulated the degree of personalization of the lifestyle issues. For each of the three e-zines, the experimental sample was divided in three groups based on their attitudes measured in phase 1. An article was prepared for the two most popular reply options (high personalization). For the remaining respondents who had not checked one of the two most popular options, a more general article in the same general domain was prepared (low personalization). This was done for each e-zine. As a consequence the composition of these three groups varied from newsletter to newsletter. The number of times each respondent received an e-zine with a highly personalized third article served as our manipulation of personalization (four levels: from 0 to 3).
The receiver could open the articles by clicking on a link. All online actions were registered. In every email participants were given the chance to opt out for receiving further emails. In total 30 respondents opted out, leaving 525 respondents for phase 2.
After the campaign, phase 2 began, in which all respondents received an email with the second measurement of Reichheld's recommendation index. The response rate to this closing mail was rather low: of the 525 emails we sent, only 221 (42 percent) were filled in: 148 (38 percent) in the experimental condition and 73 (53 percent) in the control condition.
Campaign feedback. The opening rate is defined as the proportion of respondents opening the e-zine (see Table 2). The click rate is the proportion of receivers clicking on a particular article. As the respondents could "opt out" in every newsletter, the number of emails sent off gradually decreases. The opening and click rates in the third e-zine are remarkably lower than in the first and second newsletter. This can be due to the fact that the data registration for this third e-zine was canceled after six days, while for the first two e-zines action data were registered for more than two weeks. Moreover, this third e-zine was sent off immediately after a national holiday. The proportion of readers in the first two e-zines gradually decreases from the first article until the third one. Because click rates strongly depend on the specific topics, we further ignore these differences.
Reichheld's recommendation factor. According to their answer on the initial recommendation question (phase 1), participants were divided in three recommendation categories, labeled as "promoters" (score 9-10), "passively satisfied" (score 7-8), and "detractors" (score 1-6). For the remainder of this article, we will refer to this variable as initial recommendation category.
The initial recommendation factor (RF: difference between the brand promoters and the brand detractors) of respondents in phase 1 was -1.4 percent. As top firms with enthusiastic clients reach an RF of up to 80 percent (Reichheld, 2001), the Belgian railway company NMBS is doing a bad job when it comes to customers' tendency to recommend the NMBS to others. Further, the test sample (N = 555), which "opts in" for further contact, had a slightly higher initial RF than those people who did not opt in. It seems reasonable that customers with a higher RF are more likely to volunteer for receiving future email.
Most importantly and in line with our hypothesis, e-zines yielded a significant increase of the RF (see Table 3). Before the experimental manipulation, there was no significant difference between the RF of the control and the experimental conditions [for [alpha] = .05, Z = .38 < Z (critical) = 1.64]; whereas in phase 2, after the campaign, the RF of the experimental condition was significantly higher than the RF of the control condition [for a = .05, Z = 3.95 > Z(critical) = 1.64]. Table 3 suggests that the decrease of the percentage of brand detractors seems to be responsible for the higher RF of the experimental condition in phase 2. This pattern is consistent with two of the four possible drivers of the e-zines effect as outlined above. E-zines could either turn detractors into passively satisfied or prevent passively satisfied from becoming detractors. To gain more insights in the four possible drivers of this effect, we examined the effect of the e-zines in each initial recommendation category separately.
The effect of e-zines as a function of initial recommendation category. To analyze the effect of e-zines on recommendation shift, we calculated the difference in the recommendation category between phase 1 and phase 2 (see Table 3). Among the passively satisfied customers, this shift variable has three levels: (1) customers who make a positive shift in recommendation category (e.g., from initial passively satisfied to promoter after the campaign), (0) customers who make no shift at all, and (-1) customers who make a negative shift in recommendation (e.g., from initial passively satisfied to detractor after the campaign). Among the detractors and the promoters, this shift variable has only two levels because detractors cannot shift downward and promoters cannot shift upward.
Among the detractors, the experimental manipulation had a significant effect on the shift in recommendation, [chi square](2) = 4.53, p = .033. In phase 2, there were fewer detractors in the experimental condition than in the control condition. Hence, the detractors who received the e-zines were more likely to shift upward to become passively satisfied or brand promoters than did the detractors in the control condition. Among the initially passively satisfied and the brand promoters, the e-zines had no effect on the shift in recommendation, [chi square](2) < 1, ns. We can conclude therefore that the e-zines have an effect on customers' recommendation and thus increase the RF, and that this improvement is due to a decrease in the number of brand detractors (see Table 4).
The effect of opening the newsletters.
The proportion of customers opening the newsletters is lower for the third e-zine (see Table 5). Again, this may be due to the fact that online registrations were closed early. In addition, the frequency of sending the e-zines might also have been higher than optimal.
We found no significant correlation between initial recommendation category and the number of newsletters actually opened (ranging from 0 to 3). This means that the e-zines could equally well reach brand detractors, passively satisfied customers, and brand promoters. We believe that this is an interesting finding because detractors are usually considered as the skeptical, negative WOM-spreading customers who are difficult to reach. Further, actually having opened the newsletters (from 0 to 3) did not have an effect on customer recommendation changes (from -1 to 1), [chi square](6) = 3.62, ns. Combined, these findings imply that merely receiving e-zines seems to be enough for detractors to shift upward in recommendation. Whether the newsletters are actually opened or not does not seem to influence customers' recommendation.
The effect of personalization. We found a significant negative correlation (r = -.23, p = .0045) between the degree of lifestyle personalization over the three e-zines (ranging from 0 to 3) and the shift in recommendation (from -1 to 1). This finding suggests that one should be careful in personalizing e-zines according to the receivers' lifestyle. As pointed out before, message relevance might be extremely important in promoting effective email marketing (Krishnamurthy, 2001). Perhaps consumers indeed experienced the (lifestyle) personalized e-zine as being irrelevant with respect to the company's business.
Permission marketing: Who sticks until the end? Of the 555 respondents in phase 1 who gave permission to use their email addresses for further contact, only 221 responded to the second measure of Reichheld's recommendation index after the campaign (i.e., closing mail). The initial recommendation (category) does not influence this response rate, [chi square](2) = 2.05, ns. The initial detractors, the passively satisfied, and the promoters stick equally well until the end of the campaign. We do find a strong but unexpected association, however, between the experimental manipulation and response rate, [chi square](1) = 13.76, p = .0002. Customers in the control condition are more likely to respond to the closing mail than customers in the experimental condition (see Table 6). The most likely interpretation is the difference in time that had elapsed since the previous email from the company. In the control condition, the closing mail was the first email in two months that these customers could respond to; whereas in the experimental condition, the closing email was the fourth email in two months sent by the same company. In the end, this latter procedure might have been perceived more as "spamming" than as "opt-in" newsletters.
The research examined the influence of e-zines on customers' tendency to recommend a product to others. We found that sending off e-zines increased Reichheld's recommendation factor due to a decrease in the number of brand detractors. The proportion of detractors was significantly lower among respondents who received three e-zines during a six-week campaign compared to respondents in the control condition who did not receive e-zines. In other words, the detractors who received the e-zines were more likely to shift upward to become passively satisfied customers or brand promoters than did the detractors in the control condition. Among the initially passively satisfied and the brand promoters, the e-zines had no effect on recommendation changes after six weeks. Therefore, e-zines seem appropriate as a strategic tool to increase customers' collective recommendation.
At first sight, these results suggest that the e-zines attenuate the negative attitude toward the business, which results in a reduced inclination to spread negative WOM. However, further analyses strongly suggest that the process underlying this shift is not as straightforward as it seems at first sight. First of all, there was no effect of opening the newsletters on customers' shift in recommendation. Apparently, merely receiving e-zines suffices for detractors to shift upward in recommendation; whether the newsletters are actually opened or not does not influence customer recommendation shifts. We interpret this surprising finding from a signaling perspective. Nelson (1974) showed that an advertisement's existence rather than its content matters for consumers. Similarly, the e-zine's existence rather than its content seems to suffice to produce the effect.
A second finding that does not fit with the straightforward interpretation is the fact that customers' recommendation was negatively affected by the degree of personalization of the lifestyle article included in each e-zine. The fewer "personal" articles customers received, the more likely they were to shift upward in customer recommendation. This is all the more remarkable in light of the fact that almost half of the respondents did not open the newsletters and because the two first articles dealt with topics that were highly relevant with respect to the company's business. Our data cannot inform us whether the presence of a lifestyle article in itself reduces the positive effects of e-zines. We only know that lifestyle articles reduce the positive effect of e-zines to the extent that they are personalized in line with the respondents' lifestyle. Moreover, in the context of persuasion knowledge (Friestad and Wright, 1994), we suggest that (lifestyle) personalization might activate the customers' persuasion knowledge in that it makes customers aware of the marketer's persuasion attempt and thus leads to a decrease of customer recommendation. High levels of personalization of the third article might also have drawn the attention to the irrelevance of the lifestyle article, which resulted in lower e-zine efficiency. In that sense "relevance" still might play a role here. We do have to note that personalization in function of the respondents' product use or interests in the services of the railway company might have entailed different findings.
Finally, there is a substantial negative effect of sending out e-zines on customers' final response rate. Customers in the control condition, who received only the closing email two months after the initial contact, were more likely to respond to the closing email than customers in the experimental condition, who received four emails over two months. A growing problem with permission email is that prospects gradually become overwhelmed with an increasing number of emails. Perhaps eventually they may perceive permission email to be spam.
The data suggest that e-zines can be an effective tool in increasing customers' recommendation for companies with a high percentage of detractors. This situation probably applies to monopoly organizations because in monopolies detractors cannot substitute suppliers. For this reason, their inclination to show their dissatisfaction by means of negative WOM might persist longer and do more harm (Fornell, 1992). Our data suggest that for monopolists, e-zines might be an appropriate instrument to restrict the spread of negative WOM by detractors.
In addition, the converging evidence in our data that our relatively simple campaign was already beyond the optimum in terms of complexity (and possibly also frequency) strongly suggests that the use of e-zines should be used with measure. The "less is more" rule seems to apply. Since lifestyle personalization of permission e-zines has a negative effect on customers' recommendation, our data suggest that e-zines' content should be kept general and relevant with respect to the company's business. In addition, we propose that one should be careful when deciding on the frequency of sending e-zines. Permission email seemingly produces much better results than unsolicited mailings. However, as already mentioned earlier, a growing problem with permission e-zines is that many people are signing up for too many services and are finding it necessary to cut back (DuFrene, Engelland, Lehman, and Pearson, 2005).
LIMITATIONS AND FUTURE RESEARCH
A limitation of our research is the type of business used (i.e., public transportation) to test our hypotheses. The railway company NMBS is partly subsidized by the government and is the only railway company in Belgium. This makes it difficult to generalize our findings to other private businesses that are not subsidized and that are not monopolies. Although the Belgium railway market is a monopoly, to a certain extent any unsatisfied travelers do have the opportunity to switch transportation commodities (e.g., car or bus). Of course in a highly competitive market, consumers have all the freedom to change suppliers if a current product does not live up to their expectations (Pindyck and Rubinfeld, 2001). Thus, when competition is harsh, we might think of detractors as having more power to (1) switch brands or refuse to repatronize the offending store, (2) make a complaint to the seller or to a third party, and most importantly (3) spread negative WOM to others about the unsatisfactory product or retailer (Richins, 1983). Accordingly, in a highly competitive market, detractors might be extremely "dangerous," and sending out e-zines might turn out to be an even more important tool in the management of defecting customers than in a monopoly situation (see e.g., Reichheld and Sasser, 1990). However, if all competitors in the market adopt e-zines, the "strategy" might easily be perceived as spamming and persuasion knowledge might "hover in readiness" to control for the persuasion attempts of pushy agents (Friestad and Wright, 1994). In summary, we call for future research that investigates the generalizability of our findings to other (more competitive) businesses.
Several of our findings call for additional research in the effectiveness of e-zines. We found a negative effect of e-zines on response rate but we did not manipulate the frequency of e-zines in our experiment. Further research may give more insight into the optimal frequency of forwarding emails. We also found a negative effect of the level of lifestyle personalization but we did not manipulate the number of articles per e-zine or the presence of lifestyle issues. A more systematic manipulation of these factors would certainly give us a better understanding of how and when e-zines are an effective tool for marketers to work on customer recommendation. Finally, we found that e-zines had a positive effect although many did not open the mail, let alone the articles. An interesting question is how e-zines are processed, and which factors do and do not add to the recommendation shift that we observed.
This research showed no effects on recommendation among the passively satisfied and the brand promoters. However, it would be premature to conclude that e-zines do not have an effect at all on these groups. For example, we expect factors such as consumers' prior expectations about a firm to be part of the process. Dawar and Pillutla (2000) found that consumers with positive expectations may provide firms with a form of insurance against the potentially devastating impact of crises; while for consumers with weak expectations about a firm, any crisis can be devastating. In that sense, we suggest that e-zines might increase positive expectations about the firm. In normal circumstances (as in our study), the increase in expectations may not be easily observable, at least not among promoters and the passively satisfied. However, the effect of e-zines might only show up in times of crises. It might be the case that promoters are more likely to remain promoters in times of crises when they have received e-zines before the crisis than when they have not. Although this question is more difficult to investigate experimentally, it certainly deserves attention. Also with respect to consumers' expectations, we might have to make a distinction between, on the one hand, "real" detractors who already know the firm and have negative expectations, and on the other hand, customers who are "labeled" as detractors because they do not know the firm (and therefore would not recommend it to their friends or family), but still have positive expectations. Perhaps e-zines work especially well for people unfamiliar with the company, as e-zines have the potential to introduce the company's business in a positive light. We do recognize the danger of increasing consumers' expectations about a firm because high expectations also yield the risk of disappointment upon the next experience. Therefore, creating high expectations may be too risky for low-quality firms. In that sense, we note that sending out e-zines might turn out to be a costly signal through which a firm can honestly signal an unobservable quality to an audience (see e.g., Rao, Qu, and Ruekert, 1999) in a similar way as a warranty does (Kirmani and Rao, 2000).
An interesting and related avenue for future research would also be to investigate how permission emails can be implemented in crisis management and how companies can use this strategy to counter negative publicity. For companies handling a crisis, e-zines might be functional to respond quickly and effectively to maintain consumer confidence in the brand. A study of 2,645 consumers by the advertising agency DDB Needham showed that a company's handling of a crisis ranked as the third most important purchase influence (after product quality and handling of complaints) and was mentioned by 73 percent of the consumers (Marketing News, 1995). Corporate response to a crisis also appears to be a critical determinant of the impact of the crisis on consumer beliefs that constitute brand equity (Aaker, 1991; Keller, 1993).
To conclude, we think that this research on permission marketing is still in an early stage and that knowledge about its effects is limited. The results are promising as they suggest that (1) e-zines silence brand detractors and (2) e-zines should be used with measure. Future research is called for that investigates (1) the role of other factors, such as the relevance of the topics, and e-zine frequency, (2) the generalizability to other market types, and (3) the effect on other dependent variables, such as resistance to attitude change in times of crises.
BARBARA BRIERS is an assistant professor of marketing at the HEC School of Management, Paris.
SIEGFRIED DEWITTE is an assistant professor of marketing at the Department of Marketing and Organization, K.U.Leuven, Belgium.
JAN VAN DEN BERGH is CEO of i-Merge (www.i-merge.net).
The authors thank Nancy Geyskens, market research director of the NMBS (Belgian Railway Company), for her support in collecting the data and the students in marketing of the Katholieke Universiteit Leuven (2003-2004) for their valuable help in collecting the data and creating the e-zines. We thank i-Merge for the valued help in editing the e-zines and managing the data. We thank the reviewers and Kobe Millet for valuable comments on an earlier version of this manuscript.
The first author acknowledges financial support by the Flemish Science Foundation (FWO) under grant G.0260.02 and by the Belgian Science Policy grant CP01/151. The second author acknowledges financial support by the Flemish Science foundation under grant G.0391.03 and by the OT (university grant OT 03/07). The first and second authors gratefully acknowledge financial support by Censydiam-Synovate.
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HEC School of Management
JAN VAN DEN BERGH
TABLE 1 Content of the Three E-zines Article 1: Article 2: Services of Projects Article 3: E-zine the Company in Brussels Lifestyle Personalization E-zine 1 Train ticket Modernization Sports Soccer, EC 2004, purchase on of Brussels' Portugal Olympic the internet central station Games, Greece 2004 Tennis: Justine Henin E-zine 2 Electronic Express trains Movies Thrillers moneybox for in the Brussels Blockbusters tickets district Comedies E-zine 3 Traveling Traffic problems Going out Amusement parks vouchers in Brussels The Passion of Christ Lille (France), cultural capital 2004 TABLE 2 Opening Rate and Click Rate as a Function of E-zine Click Rate, Click Rate, Click Rate, E-zine Opening Rate Article 1 Article 2 Article 3 E-zine 1 238/418 = 56.9% 44% 34% 10% E-zine 2 232/405 = 57.3% 59% 31% 14% E-zine 3 189/393 = 48.1% 15% 15% 16% TABLE 3 Percentage Promoters, Percentage Detractors, Reichheld Factor, and Sample Size as a Function of Phase and Experimental Condition Promoters Detractors Sample Phase/Condition (%) (%) RF Size Phase 1 24.1 25.5 -1.4 817 No Approval 27.1 33.2 -6.1 262 Approval 22.7 21.8 0.9 555 Control* 26 20.5 5.5 73 Experimental* 25 18.9 6.1 148 Phase 2 Control 30.1 23.3 6.8 73 Experimental 33.1 17.6 15.5 148 *The respondents of phase 1 who also responded in phase 2. TABLE 4 Shift in Customers' Recommendation among the Detractors as a Function of Condition Status Upward Condition Quo (0) Shift (1) N Control 73% 27% 15 Experimental 39% 61% 28 TABLE 5 Number of Customers Opening the Newsletters (Experimental Condition) Experimental Condition E-zine 1 E-zine 2 E-zine 3 N = 148 117 118 106 TABLE 6 Proportion of Customers Responding to the Closizng Mail as a Function of Condition Condition Proportion Respondents in Phase 2 Control 73/137 = 53.3% Experimental 148/388 = 38.1%
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|Title Annotation:||customer loyalty|
|Author:||Briers, Barbara; Dewitte, Siegfried; Van Den Bergh, Jan|
|Publication:||Journal of Advertising Research|
|Date:||Jun 1, 2006|
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