Monday, January 29, 2007

A Penny For Your Thoughts: Referral Reward Programs and Referral Likelihood

The January 2007 issue of the Journal of Marketing contains an article that will be of interest to those seeking to understand WOM and referral reward programs. Researchers Gangseog Ryu and Lawrence Feick wrote the article entitled "A Penny For Your Thoughts: Referral Reward Programs and Referral Likelihood."

Here's the abstract (an executive summary of the study can be found here):

Because referral reward programs reward existing customers and build the customer base, firms use them to encourage customers to make recommendations to others. The authors report on four experiments in which they find that rewards increase referral likelihood. More specifically, they find that rewards are particularly effective in increasing referral to weak ties and for weaker brands. It is also important who receives the reward. Overall, for weak ties and weaker brands, giving a reward to the provider of the recommendation is important. For strong ties and stronger brands, providing at least some of the reward to the receiver of the referral seems to be more effective. The authors discuss the implications of the results for the design of reward programs.
This is a very neat article so I'll go into some detail summarizing it. NOTE: This is not a comprehensive summary of the article, so please refer to the entire article for all of the details. If you're more interested in the practical/so what? implications, skip down to the section entitled "Practical Implications for Managers".

Goals of the Study (pp. 84-85)

The researchers set up four experiments where they examined the effects of the following on referral likelihood:

- the presence or absence of a reward;
- the size of the reward;
- who receives the reward (the existing customer, the new customer, or both);
- the impact of the relationship between the two parties (strong or weak tie [roughly speaking, this measures the closeness of the relationship: strong ties are well-known others while weak ties are less well-known acquaintances]);
- brand strength (strong or weak; a "strong brand" is one that has high brand awareness and well-established brand associations (see p. 86)

Theoretical Background (p. 85)

The researchers used exchange theory which, in this context, suggests that people make decisions to engage in WOM based on their perceptions of the costs and benefits associated with doing so (for example, benefits of WOM include reducing anxiety after the purchase, to be seen in a positive light by others, and expressing concern or helping another person out; costs might include the time and effort while communicating and the possibility that their conversational partner isn't happy about the recommendation they received from the other person which could damage the relationship). They add, though, that referral programs carry additional complexity when it comes the cost-benefit analysis. For example, when a referral is rewarded the conversational partner might perceive that their friend is making the referral to get the reward rather than for the intrinsic motivation of helping another friend out.

ROI of Referral Programs

For a referral program to be deemed effective, a company needs to obtain results beyond what would have otherwise occurred naturally. In the WOMMA Terminology Framework terms, the marginal gain from the "amplified" program needs to be able to cover its costs and go beyond the "organic" WOM that would have happened without the program.

Study 1: Presence/Absence of Rewards and Reward Size on Satisfied Customer's Referral Likelihood; Strength of Ties and Brands

The research method for the first study involved 275 undergraduate students at a university in Singapore completing surveys. The students were randomly assigned to different experimental conditions (whether a reward was used at all, the size of the reward, close friend versus casual acquaintance) and then asked to imagine they were wanting to buy an MP3 player and then which of two brands they would prefer (Brand A versus Brand B; brands were described as having higher/lower quality and higher/lower reputation to indicate brand strength; no actual brand names were used to avoid effects of prior brand beliefs). The size of the reward, if present at all, was 10% of the sales price (small reward condition) or 20% (large reward condition). Participants then indicated how likely they were to refer on a scale of 0% ("certain not to tell this person) to 100% ("certain to tell this person"). See the study for additional details and other variables.

Results indicated that referral likelihood was greater with strong ties than weak ties and that offering a reward significantly increased referral likelihood (however, the size of the reward didn't make a significant difference in increasing referral likelihood). When you take into account the relationship between the parties the researchers found that the presence of a reward did not affect referral likelihood with strong ties. With weak ties, though, offering the reward increased consumers' likelihood to refer. Further, the rewards were more likely to increase referral likelihood for weak brands (by 20%) but less likely for strong brands (only 10% increase).

Study 2: Trying to Understand the Mechanisms Underlying the Effects from Study 1 by Looking at the Perceived Social-Psychological Costs and Benefits of a Referral

Without describing the procedures, I'll summarize the results by stating that the researchers found support for the principles of exchange theory: consumers can and do evaluate the social and psychological costs and benefits differently when a reward is involved (p. 89). In general, any potential social benefits of a referral are perceived as lower, and the costs are perceived as higher, when a reward if offered versus when one isn't offered. But again, tie strength matters here. There are more perceived social and psychological costs and benefits between strong ties and when a reward is present. However, when engaging in WOM with weak ties, consumers are more likely to recognize the economic benefits of the reward and not worry as much about the potential social and psychological costs and benefits.

Study 3: Does It Matter To Whom the Reward Is Given? "Reward Me" (Existing Customer), "Reward You" (New Customer), and "Reward Both"

Again, cutting to the chase here, the researchers found it does make a difference who gets the reward based on the relationship of the parties to each other. With strong ties, it's not as important who receives the reward (the existing customer, the new customer, or both), though the trend indicates it's probably better to err on the side of rewarding the new customer or rewarding both people. With weak ties, however, rewarding the existing customer had the most impact on increasing referral likelihood.

Study 4: Seeking To Generalize Findings Beyond Hypothetical Scenario with MP3 Players to Actual Experiences with Mobile Phone Service

In this study, the researchers wanted to see if the same findings would apply to a service (rather than a good) and whose attributes are based on actual experience (rather than search characteristics). This study was done in South Korea and the following results of previous studies were replicated:

- Offering a reward to an existing customer increased referral likelihood between weak ties, but not strong ties;
- Referral likelihood was greater when a reward was offered for a weaker brand;
- For weak ties, there was little difference between the "Reward Both" and "Reward Me" reward schemes. For strong ties, referral likelihood was higher with "Reward Both" rather than "Reward Me."

They also found an interesting interaction effect between brand strength and the reward scheme. For a stronger brand, the "Reward Both" scheme performed a lot better than the "Reward Me" scheme. But for a weaker brand, the "Reward Me" performed just a little better than the "Reward Both" scheme. The researchers think that the underlying mechanism here is similar as for tie strength. That is, since people have a high level of commitment to a strong brand and a strong intrinsic motivation to refer, the "Reward Me" scheme leads people to think of themselves and their motives in a negative way (for example, feelings of guilt). A "Reward Both" scheme, however, may reduce the psychological costs involved with getting a reward since it's shared with the other person. Further, consumers of a strong brand tend to be less price sensitive and so the higher economic gain in the "Reward Me" scheme is probably perceived as less important.

Theoretical Contributions

From a theoretical perspective it expands social exchange theory from just the relationship between two parties, to include three parties: the existing customer, the new customer, and the brand. It also shows the utility of using exchange theory to understand WOM.

Practical Implications for Managers

Here's a quick summary of the implications the researchers identify:

Result: Offering rewards can increase referral likelihood, but there wasn't a difference in effect between smaller and larger rewards (in this study, 10% versus 20% of the purchase price).
Implication: Calibrate reward size carefully by calculating the revenue impact of the size of reward with how much additional referral likelihood is likely to occur (see the detailed results in the article for specific percentages of how much the referral likelihood might increase using different reward sizes). Then compare this calculation with the cost of other reward programs. (p. 92)

Result: Among strong ties, rewarding the existing customer (Reward Me) didn't increase the likelihood to refer. But rewarding the new customer (Reward You) or both (Reward Both) can slightly increase referral likelihood among strong ties.
Implication: Since most referral reward programs tend to involve strong ties, either explicitly (as in the case of "friends and family programs") or just end up that way (because people are more likely to interact with strong ties and more likely to know what is relevant and important to them, thus leading to higher recommendation behavior), its probably best to use the Reward You or Reward Both condition, rather than the Reward Me condition.

Result: Rewards increase referral likelihood to weak ties. Further, in weak tie recommendations, the recommender needs to receive a reward in return for the recommendation.
Implication: Since weak ties play an important role in "bridging" one social network to another social network, they are important to involve in the referral program in order to increase the spread of WOM. However, the trick is in devising programs that involve weak ties. Referrals to strong ties are likely to happen without the reward program and are likely to happen first. The researchers suggest that weak tie referrals is what really need to be encouraged and are likely to happen after the strong tie referrals.

One option suggested by the researchers is a segmentation approach based on reward size and reward scheme. First, increase the size of the reward as the number of referrals increase. This recommendation is based on the assumption that strong tie referrals are more likely to occur before weak tie referrals. The referral reward program would thus pay the least for strong tie referrals that would presumably occur naturally and pay the most for those weak ties that would be least likely to occur organically. Second, the reward scheme would shift from "Reward Both" or "Reward You" for strong ties (and presumably earlier referrals) to "Reward Me" for weak ties (and presumably later referrals). Shifting the rewards to the recommender should naturally switch the emphasis to weak tie referrals based on the social-psychological mechanisms discussed earlier.

Result: Distributing a reward to increase referral likelihood is more important for consumers who perceive a weaker brand.
Implication: The researchers suggest that weaker brands can benefit from rewards programs, even if the long-term goal may be to increase brand strength. In the shorter term, the brand may want to use a rewards program to increase trial and/or referral likelihood. Practitioners should use the Reward Me scheme for a weaker brand and the Reward Both scheme for stronger brands.

Limitations of the Study

The researchers point out a few limitations to their study:

- Future research needs to add in receiver receptivity as an important variable. Some receivers may be more receptive to a referral than others and the researchers suggest it's important to understand more about the dyadic relationship between the parties to understand this aspect of receptivity.

- Referral likelihood, rather than actual referral behavior, was studied. Since referral likelihood may not lead to actual referrals, future research needs to collect behavioral data.

- Different types of rewards should be considered beyond just monetary rewards. One option I thought of might be to grant access to exclusive information not provided to other consumers. This may reduce negative self-perceptions associated with receiving a monetary reward. Or, perhaps give the option of donating the reward to a charity or other "good cause."

- Future research should look at the effects of rewarding referrals on the recommender. For example, might rewarding the referral actually lead the recommender to feel less satisfied with the brand, less loyal, or otherwise change the attitude toward the brand? Might the referrer start to feel more like a "mercenary" and could this affect how they view the brand?

- Future research needs to look at the differences between knowledge of the program before purchase and after purchase. This study focused exclusively on post-purchase knowledge of the reward program.

- Cultural differences may play a role in the results. All of the participants were from Asia where other research suggests that Asians are more likely to see themselves as more interdependent rather than independent. This may affect how the social and psychological costs of the rewards are perceived. But the researchers ultimately suggest that because the findings about tie strength are consistent with earlier studies that involved U.S. participants, they feel that similar results would hold when using a sample of Western participants. (Of course, the distinction between Asian and Western in the study is very broad and might not take into account important differences based on national or regional variation).

- I would also add a couple other limitations that weren't discussed in the limitations section. One, rewards might have other effects besides stimulating referral behavior (such as serving as a reminder to talk about the brand; in fairness, the researchers acknowledge this on page 92). Two, exchange theory emphasizes a rational, cost-benefit analysis of consumer decision-making, and while the researchers show some support for this approach, it would be instructive to look at other frameworks that don't assume a rational actor.

OK, that's the summary with a bit of added commentary. I'll probably write more about this later on. In the meantime, feel free to contribute your thoughts in a comment.

Citation: Ryu, G. & Feick, L. (2007). A Penny For Your Thoughts: Referral Reward Programs and Referral Likelihood. Journal of Marketing, 71, 84-94.


Friday, January 19, 2007

Response to Justin Kirby's Comments About To Tell Or Not To Tell? Report

Recently Justin Kirby of Viralmeister posted on his blog, and left a comment on my blog post, regarding concerns he had about the methodology of my research report "To Tell Or Not To Tell?" So that other interested readers could follow along I wanted to "promote" his comment to its own blog post and respond. I apologize in advance for this being a long post but I think it's important to address each concern in detail (and besides, it's an occupational hazard for me to provide verbose explanations -- ask my students, they'll tell you).

Justin was responding to my post on a recent study by Alain Samson at the London School of Economics (I pull excerpts for the sake of space; see Justin's full post):

... To his credit Dr Carl does point out that not everyone is cheer leading the Net Promoter Score and makes some valid points about the need to see the methods and results used in the analysis in order to assess the merits of this latest research from the London School of Economics. ... Anyway, I was mildly amused about Dr Carl’s stance on methodology because I felt the same way about his research on Bzzagent’s model (To Tell or Not to Tell), which by his own admission was based on Bzzagent’s internal analysis of the 270,000 word-of-mouth reports from their own agents. I’d love to see how Dr Carl adjusted for bias of not only Bzzagent’s internal analysis of the reports, which is far from objective, but also the bias of the reports from a ‘trained’ group who are both directed and incentivised to spread the word.

I just wonder where the control group was because I’m dubious about solely using a panel which has been designed to leverage the Hawthorn[e] Effect rather than a more conventional research panel that tries to adjust for this kind of bias. Maybe Dr Carl could put me right on this because I can’t help thinking that facts were fitted to theories about disclosure which fly in the face of Attribution Theory.

I'd like to take the opportunity to respond to Justin's comments to clarify his valid points from apparent misunderstandings of my research. For a quick overview of the main findings of the To Tell Or Not To Tell? report please read here (the full report can be downloaded as well).

First, the To Tell Or Not To Tell? (TTONTT) report was not based on "BzzAgent's internal analysis of the 270,000 word-of-mouth reports from their own agents." This was mistakenly reported in a ClickZ article entitled "BzzAgent to Agents: Spill the Beans, Or Else." I wrote a blog post to clarify the mistake in that article, which Justin linked to, so I would encourage Justin and other interested readers to re-read that post. As I wrote in that post, BzzAgent prepared their own white paper citing internal reports of their agents; none of the findings from TTONTT relied on those reports so there was no bias to adjust for regarding a separate analysis conducted by BzzAgent.

Second, Justin was concerned about the "bias of the reports from a ‘trained’ group who are both directed and incentivised to spread the word." Here again, this is a misunderstanding of the TTONTT methodology. I employed a dyadic methodology that relied on surveys completed by BzzAgents (not the internal reporting done by BzzAgents as part of a campaign, but surveys completed as part of this specific TTONTT research project) and their conversational partners (the people they talked with about the brand, product, or service). To account for any potential bias in the BzzAgent's responses to the TTONTT survey we validated their responses with their conversational partners' responses. So, for example, if a BzzAgent said they disclosed but the Conversational Partner said they didn't disclose, this was noted as a discrepancy, and the discrepancy results were fully reported and accounted for in the analysis on pages 10-11 of the report.

Third, Justin wondered where the control group was because he is:
dubious about solely using a panel which has been designed to leverage the Hawthorn[e] Effect rather than a more conventional research panel that tries to adjust for this kind of bias. Maybe Dr Carl could put me right on this because I can’t help thinking that facts were fitted to theories about disclosure which fly in the face of Attribution Theory.
Justin's point about a control group is valid and I appreciate the opportunity to respond. The TTONTT report was part of a larger project where we were trying to understand multiple perspectives on the same interaction -- the BzzAgent's and the Conversational Partners' (many studies rely on just one person's perspective) -- and also to determine how Conversational Partners were affected by talking with a participant in a word-of-mouth marketing program. And then, in addition, the study was to look at what role disclosure of the agent's affiliation with a WOM marketing company might be.

The study did not employ a control group where we gave instructions to some agents to disclose their identity, other agents to not disclose their identity, and then another group where no instructions regarding disclosure were given (the third group here could be used as a control group). The reason for not doing this was because it would have violated BzzAgent's policy surrounding disclosure, which required agents to disclose their identity (see page 8 of report). Instead, what we did was to conduct the analysis by comparing two groups after we collected the data: 1) Conversational Partners who knew they were talking with someone affiliated with a word-of-mouth marketing company and 2) Conversational Partners who did not know the agent's affiliation. NOTE: I relied on the Conversational Partners' responses (that is, non-Agents) for most of the analyses, except when I conducted the discrepancy analyses where I matched the BzzAgent's survey response to the Conversational Partners' survey responses.

By doing this post-hoc analysis, rather than using a field-based quasi-experimental design, or a laboratory-based experiment, this study has limitations, as all studies do (and there are other limitations to the study as well, all discussed in the report on pages 20-21). For example, we found that there was no difference between the outcome variables between the two groups (no difference in a conversational partner's likelihood to inquire further, to use the product/service, to buy the product/service, or to tell others about the product/service). But we did find that people who knew of the agent's affiliation told more people about the product/service. Because we didn't use an experimental design we can't conclude that disclosing agent affiliation led to higher pass-along or relay rates (more people being told). We can only say that conversational partners reported higher pass-along rates in conversations where they knew they were talking with someone affiliated with a WOM marketing program. However, while noting this limitation there are a number of important results that are, as Justin rightly points out, at odds with what we would expect from attribution theory (see my blog post responding to some of these counter-intuitive results; for readers unfamiliar with attribution theory as it relates to WOM, see Greg Nyilasi's chapter in the Connected Marketing book that Justin edited with Paul Marsden).

I was surprised myself by a number of results from this study -- this is the great thing about conducting original research -- so it would be inaccurate to say "that facts were fitted to theories about disclosure which fly in the face of Attribution Theory." But when you dig deeper into the analysis you find something that's pretty interesting and it's that attribution theory may still apply, as long as you take into account the relationship between the BzzAgent and the Conversational Partner. Here's what I mean...

If you're talking with a stranger or acquaintance -- people you don't know particularly well, or at all -- and the only thing you know about them is that they're part of a particular kind of WOM marketing campaign, then you might be more likely to question the person's credibility to give an unbiased opinion or an opinion that may not be in your best interest (in fact, some of the data I had about interactions with strangers actually trended in this direction; however since most BzzAgents speak with friends and family members (see page 6), rather than going up to strangers, we didn't have enough strangers to make valid statistical comparisons). However, if you know a person in a range of different contexts and have talked with them before, and know from those interactions that they generally have your best interests at heart, you're much less likely to question their sincerity when they share their opinion about the brand, product, or service. I think that because there was a high number of "stong-tie" relationships between the BzzAgents and Conversational Partners, this explains a good bit about why the results turned out the way they did (both BzzAgent's internal research and my own research partnering with them shows that the majority of the conversations are with already-known others).

Finally, Justin also expressed concern about a using a business model that's designed to leverage the Hawthorne Effect (meaning that people's behaviors will be affected by the act of giving people attention and making people feel more involved, which is what many WOM markting programs seek to do in order to stimulate WOM; interested readers should see Paul Marsden's chapter on product seeding programs in Connected Marketing). Here, again, I would reiterate that I surveyed Conversational Partners, in addition to the BzzAgents, who were not affiliated with the WOM marketing company. I would also offer that the study should be repeated with a wide range of different models and techniques of WOM marketing programs.

I hope that there are still a few readers who have made it to this point of the blog post! :-) I apologize for the length of this, but I appreciate the opportunity to clarify the study and I invite others to challenge the results and engage with the study so that we can achieve a better understanding of the role of disclosure in WOM marketing programs.

Justin, does this address all of your concerns?

Download the full version of the To Tell Or Not To Tell? report, as well as other papers I've written, for free at my download page

UPDATE (01/22/2007): Justin Kirby has posted a response to my response.


Sunday, January 14, 2007

Understanding the Buzz That Matters: Negative vs Positive Word of Mouth

There's a new article* out about the relationship between positive WOM (PWOM), negative WOM (NWOM), and revenue growth, following in the tradition of research about the Net Promoter Score. The article is by Alain Samson, from the London School of Economics and Political Science, and was published in the International Journal of Market Research.

Here's the abstract:

This article discusses negative and positive consumer word of mouth (NWOM and PWOM) in a mostly quantitative context. Based on the correlations between WOM and business growth found in Marsden, Samson and Upton’s (2005) ‘Advocacy Drives Growth’ study, possible explanations for the superior predictive power of NWOM are presented. It is suggested that, similar to the Net Promoter® Score (NPS), NWOM is a good measure to capture both loyalty and advocacy among existing customers, while negative information may also have a strong effect on purchase decisions by potential customers. The number of brand choices and brand commitment are addressed across industries. It is proposed that brands (particularly services) in high-commitment/low-choice sectors have to be more sensitive to NWOM, while PWOM may be a better predictor for business growth in low-commitment/high-choice industries. Finally, using data from ‘Advocacy Drives Growth’, a new WOM measure in the form of a ‘Net Advocacy Score’ is presented.
The article is interesting for a couple reasons. First, Samson argues that the impact and utility of PWOM and NWOM depends on two factors: a) the industry (high/low choice and high/low commitment) and b) whether you analyze WOM from the perspective of customer retention (loyalty) or customer acquisition (advocacy).

The second reason it's interesting is because it seeks to extend the utility of the Net Promoter Score (the number of people who would be highly likely to promote or recommend a brand to a friend minus the number of people who would detract from the brand) by incorporating actual WOM behavior rather than just behavioral intentions (i.e., the likelihood of a recommendation, which is what the NPS measures). The new metric is called the "LSE Net Advocacy Score." In short, it combines the Net Promoter Score with reported NWOM, and is calculated as follows:
Net Advocacy Score = NPS - NWOM
(NWOM refers to the percentage of customers reporting making very negative comments in the past 12 months.)

According to Samson, a two-point increase in the Net Advocacy Score roughly corresponds to a 1% increase in revenue growth, at least for industries where there is relatively low-choice and high-commitment brands (in this case, mobile phone networks, retail banks, and supermarkets).

A couple limitations to keep in mind when reading this article. First, it was published as part of a Forum in this journal so it doesn't have a full-blown presentation of the methods and results used in the analysis. Greater detail will be important to validate the evidence presented in this article by other researchers. Also, the relationship between NPS and revenue growth has recently been called in to question by other academic researchers. Since the Net Advocacy Score (proposed in the present study) relies on the NPS in its calculations (NAS = NPS - NWOM), then additional research on the Net Advocacy Score should address the recent critiques of the NPS.

Here's my blog post about the "Advocacy Drives Growth" study.

Here's a link to the "Advocacy Drives Growth" study (PDF).

Be sure to read my other blog posts about the role of negative and positive WOM.

* Samson, A. (2006). Understanding the buzz that matters: Negative vs positive word of mouth. International Journal of Market Research, 48, 647-657.


Monday, January 08, 2007

Ad Age's Article on the "Consumer" As Agency of the Year

Via e-mail correspondence Jim Nail encouraged me to check out an AdAge article that named the "consumer" as Agency of the Year. In his blog post, Jim was critical of the piece saying that it missed the point of consumer control. In response to the following line that appears in the AdAge article...

The question for 2007 will be whether marketers and agencies find ways to harness that consumer-bred creativity...and deploy it to the service of brands.
... Jim writes that...

In other words, big corporations and brands still have the power, they only let the consumer have the illusion they have the power. The marketer may not be able to give the consumer a creative brief and tell them what to do, but if they are wiley enough, they can still manipulate, cajole, fool, and bribe the consumer to do what they want.

... and continued by saying:
The lesson Ad Age missed -- and that marketers should focus on -- is how to harness consumer-bred creativity and deploy it to the service of those consumers, by listening and learning what the consumer says makes for a great brand, then delivering it in real, differentiated, meaningful features and benefits.
I feel Jim has a valid point. All along the AdAge article is ostensibly talking about the power of the consumer and not the agency, but then seems to switch gears and talk about how consumer content can be assimilated into the brand, which the article suggests is ultimately controlled by the agency. The article reminds me of a classic process of hegemony whereby a dominant institution seeks to co-opt ideas and practices in ways to maintain its position of dominance. There seems little emphasis at all in the article about the process of listening, dialogue, and understanding to meet mutual needs, which would suggest a more equitable, dialogic, and mutually beneficial relationship between companies and customers.

I've really enjoyed AdAge over the past year as it has given a lot of wonderful coverage to word-of-mouth marketing and consumer generated media, especially in articles by Matthew Creamer and Jonah Bloom. But I think this article in particular fell prey to the title of the publication in which it appeared. As much as the article sought to escape from assumptions bound up in the age of advertising, it seemed unable to wrest itself from its grip.

One area where I do agree with the AdAge article is in the following point about the agency being dislpaced from its center:
What it does mean, however, is that big agencies -- great companies that once cast long shadows over corporate America -- are losing more of their control within a marketing process that for decades they have dominated. They're already being squeezed by procurement departments and jostled by media companies and nibbled at by a host of other kinds of agencies that grew in importance as TV ceased to be the only game in town.
For other views on the AdAge article see Peter Kim's and Jaffee Juice's blog posts on the same topic.

Wednesday, January 03, 2007

Citizen Marketers: When People Are the Message

Ben McConnell and Jackie Huba have done it again! I really enjoyed their first book, Creating Customer Evangelists, and now I am happy to report that I can say the same about their latest, Citizen Marketers: When People Are the Message. In fact, I plan to use it in my class this term at Northeastern on WOM marketing communication. I was fortunate to receive an advance copy of the book from them and wanted to comment on my decision to include it in my class. (By the way, I'm very late in the game here as a number of others have provided reviews of their book as well and it has been attracting quite a bit of attention).

I decided to adopt the book for my class because I think it's essential for students to understand the processes that lead people to generate their own content and advocacy for and about companies (what Ben and Jackie call "citizen marketers"), and how companies can best organize themselves to participate in conversations with citizen marketers.

In the book they explain four different kinds of citizen marketers: filters (people who collect info from a variety of sources and then package it for others to consume), fanatics (big-time fans and evangelists), facilitators (those who help to coordinate and build communities), and firecrackers (one-hit wonders who post something that attracts considerable attention and then interest subsequently wanes).

They also discuss the thesis of the "one percent rule" which states that in any community, only about 1% of the community is actually responsible for contributing the content that others in the community consume. Later in the book there's a great quote from Yahoo's Bradley Horowitz that adds another layer to this 1% rule. He's quoted as saying how the "act of consumption is itself becoming an act of production" (p. 134; in reference to how people's consumption and voting behavior creates content for others who subsequently consume the content).

I really like how Ben and Jackie discuss a number of case studies of communities that have been built by citizen marketers and the principles that led to their success. For example, they describe six factors that led to YouTube's success. Later on in the book they also describe why other attempts at creating community have failed, which is equally, if not more powerfully, instructive.

The motivations for citizen marketers are also discussed: altruism, personal relevance, common good, and status. They draw on the work of a cultural historian (Professor Steven Gelber) to argue that citizen marketers are hobbyists at their core, and that their activity is a kind of "productive leisure". Here is actually a place I would like to have seen Ben and Jackie explore in more detail: on p. 108 they quote Professor Gelber's explanation of how hobbies, during industrialization, "gained wide acceptance because they could condemn depersonalized factory and office work by compensating for its deficits while simultaneously replicating both the skills and the values of the workplace," a process that Gelber calls "disguised affirmation." That is, hobbies allow the participant to consider their activity as a form of "recreation" while subconsciously re-creating a certain ideology about work and their place in society. If we applied this analysis to citizen marketers, then, what kind of ideology is being re-created when people create content about companies, brands, products, and services? And what are the implications of this form of ideology re-creation to a democratic society? I hope to explore this a bit more with my students this term.

Another area I would like to see explored is how much the media form itself plays into the definition of being a citizen marketer. For example, if people created a great deal of advocacy in primarily face-to-face settings or over land-line phones, are they considered citizen marketers (or maybe we would call them evangelists?). Or is there something about broadcasting to a larger audience that's inherent in the definition? But then we'd need to consider the case of McChronicles (a blog maintained by a man in New York who chronicles his experience with McDonald's and described in the book) with Supersize Me! (a documentary film by Morgan Spurlock about his experiment eating only fast food from McDonald's for a month, but not discussed in the book). Do we also consider Morgan Spurlock to be a citizen marketer? Clearly one of the points Ben and Jackie make is that the more important thing is that people are the medium, giving a nod to Canadian media theorist Marshall McLuhan, and that "social media" technologies like blogs, podcasts, video sharing sites, etc. have democratized the ability to reach large amounts of people very efficiently. I think they would say that being a citizen marketer is really about people a feeling of a certain kind of ownership and participation in companies, brands, products, and services, and that this disrupts more traditional understandings of who filters information and promotes or undermines advocacy in a society.

Another thing I like is their chapter on "How To Democratize Your Business" which details through mini case-studies three primary ways companies have thus far worked with citizen marketers: through contests, through co-creation of the brand or product, and through community facilitation. The number of examples provided give the reader a glimpse of the possibilities for companies. Figuring out ways to engage citizen marketers is definitely a high priority.

They conclude their book with a cautionary note of how NOT to work with citizen marketers -- for example, not to engage in stealth marketing because it doesn't come from a place of authenticity that is prized by citizen marketers. One quotation I really found intriguing is this: "Social media is the antidote to campaign-based thinking." I'll be encouraging my students to reflect on what this means for how a company envisions their relationships with citizen marketers and their WOM marketing efforts. The quotation alludes to different philosophies of WOM marketing that my class discussed the first time I taught the class last summer.

To conclude this post I want to say thanks to Ben and Jackie for all their diligent efforts doing the research for this book and for sharing their knowledge of citizen marketers.

Disclosure: Ben and Jackie are members of the Word of Mouth Marketing Association (Jackie is on the Board of Directors) and I am on the advisory board of WOMMA. As mentioned above, I received an advance copy of the book and didn't have to pay a penny for it (my students won't be so lucky however).


WOMBP: January 2007 Update

Happy new year!

The latest version of the WOM Marketing Communication Bibliography Project (WOMBP) is now uploaded. You can access it at my download page.

Here's the background of the project and details of the contributors.

Below are new entries in this version (these aren't necessarily new studies, they just weren't included in the last update):

Bowman, D. and D. Narayandas (2001). "Managing Customer-Initiated Contacts with Manufacturers: The Impact on Share of Category Requirements and Word-of-Mouth Behaviour." Journal of Marketing Research 43: 281-297.

Danaher, P. J., I. W. Wilson, et al. (2003). "A Comparison of Online and Offline Consumer Brand Loyalty." Marketing Science 22(4): 461-476.

Dellarocas, C., N. F. Awad, et al. "Exploring the Value of Online Product Ratings in Revenue Forecasting: The Case of Motion Pictures." Working Paper.

Dellarocas, C. and R. Narayan (2006). "A Statistical Measure of a Population's Propensity to Engage in Post-Purchase Online Word-of-Mouth." Statistical Science 21(2): 277-285.

East, R., K. Hammond, et al. (2005). "What is the Effect of a Recommendation." The Marketing Review 5: 145-157.

Granovetter, M. (1973). "The Strength of Weak Ties." American Journal of Sociology 78: 1360-1380.

Jin, Y., P. Bloch, et al. "A Comparative Study: Does the Word-of-mouth Communications and Opinion Leadership Model Fit Epinions on the Internet." 1-31.

Noyes, J. (2006). "BzzAgent tries to keep 'agents' part of 'hive'." The Boston Herald.

Nyilasy, G. (2006). "Word of mouth: what we really know - and what we don't." Connected Marketing: 161-184.

Samson, A. (2006). "Understanding the buzz that matters: negative vs positive word of mouth." Internation Journal of Market Research 48(6): 647-657.

Shin, A. (2006). "FTC Moves to Unmast Word-of-Mouth Marketing." Washington Post Online.

Wirtz, J. and P. Chew (2002). "The effects of incentives, deal proneness, satisfaction and tie strength on word-of-mouth behaviour." International Journal of Service Industry Management 13(2): 141-162.