Sunday, June 26, 2005

Should Bloggers Disclose Financial Compensation?

In today's Sunday Boston Globe (pp. A1, A22), Jenn Abelson wrote an article citing concerns about bloggers who receive compensation to mention certain companies on their blogs. According to the article, a marketing firm -- USWeb -- enlisted 2,000 bloggers to mention USWeb's clients' products and services on their blogs, sometimes regardless of whether the blogger had direct experience with the company. (When more blogs mention, and link to, particular websites, those websites are rated higher in search engines like Google; this has led some in the advertising industry to interpret blog to mean "better listing on Google." Currently, there is no government regulation regarding such disclosure of compensation in the blogosphere.)

It seems like failure to disclose financial compensation on blogs represents yet another form of "undercover," "stealth," or "shill" marketing. Further, non-disclosure seems to violate the Word-of-Mouth Marketing Code of Ethics, which supports honest disclosure of identity and relationship with a marketing company.

The situation is complicated by the following example: a software marketing company mentioned in Abelson's article -- Marqui of Portland, Oregon -- discloses that they pay bloggers to have their clients' names mentioned on blogs. However, the blogger mentioned in the article didn't consistently disclose that she received compensation. Thus, Marqui would seem to be abiding by the WOMMA* Code because they disclose they pay bloggers. But should the blogger receiving compensation also abide by such a code? How much can, and/or should, a marketing company control the actions of the people they compensate for their participation in marketing campaigns?

To me, this issue of the most effective and ethical way to manage institutional identity and affiliation is of paramount importance to longevity of word-of-mouth, buzz, viral, and blog marketing. I am especially interested in this identity management in more interactive settings, especially interpersonal contexts. Stay tuned for upcoming reports from research projects on this and related topics.

* Disclosure: As mentioned in previous posts and in my bio, I am an Advisory Board member of the Word-of-Mouth Marketing Association which has developed a code of ethics surrounding the online and offline word-of-mouth marketing industry.


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Thursday, June 23, 2005

Wall Street Journal Article: "Marketers Scan Blogs for Brand Insights"

In today's Wall Street Journal Bill Bulkeley wrote an article about how companies are increasingly tracking brand-related conversations. In the article I was quoted as highlighting the lack of direct research on the similarities between online and offline WOM conversations. I've written about this in an earlier post (see second and third paragraphs) and think it's crucial for researchers to do a comparative study that investigates how similar (or different) the online discussions in blogs, chat rooms, etc. are to what takes place in face-to-face venues. One consequence, among many, is that if the online and offline conversations are similar then organizations can rely on the increasingly sophisticated tracking tools that are available and that Bulkeley describes in his article. If the conversations are different, however, then additional research into the world of offline conversations is necessary. I'm going to speak on this issue at the upcoming Word-of-Mouth Marketing Association conference on measuring word-of-mouth (e-mail me to receive a special discount for blog readers; in the interest of full disclosure, readers should be aware that I sit on the WOMMA Advisory Board).

Final thought: I know of many studies that look at online conversations, but none that directly compares the offline and online. A related study that needs to be done is on how offline conversations influence online ones and vice versa. If you know of research on these topics please post a comment or contact me via e-mail. And if you are interested in collaborating on a project let me know as I have some ideas in mind for a research design.


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Saturday, June 18, 2005

Haloscan commenting and trackback have been added to this blog.

Wednesday, June 15, 2005

Word-of-Mouth and Gender

Some colleagues and I were recently talking about WOM and effects of gender. In this post I provide a few published academic journal articles that address this topic and then also provide some findings from my own research on WOM communication practices of buzz marketing Agents and everyday people.

Quick note: Many people use “sex” and “gender” interchangeably, but we should distinguish between the two: sex refers to biological characteristics of males and females, while gender refers to the social and cultural meanings we attach to the biological characteristics. So, as a quick illustration, when a baby is born as a boy or girl, that’s sex; when a boy baby is given a blue blanket and a girl baby is given a pink blanket, that’s gender. Communication behaviors commonly associated with masculine styles include using talk instrumentally to "fix" a situation, using talk to assert one’s identity, and competing to hold the conversational floor, while feminine behaviors typically include cooperatively including others in the conversation, emotional expressiveness, and using talk to maintain social relationships and connectedness. Gender can be measured with certain scales (for example to assess the extent to which a person identifies with certain behaviors typically associated with males and females), but often researchers don’t make the effort to do so; thus, when research reports on gender differences based simply on whether people identify themselves as male or female, that research is really talking about sex differences rather than gender differences. Interestingly, when college students are assessed for gender styles they most commonly enact an androgynous style, meaning both masculine and feminine; however, generally people are more comfortable with one or another style, and also find one style more appropriate to use depending on the social circumstances. (1)

Another quick note: For whatever reason people like to focus on sex or gender differences rather than the overwhelming similarities (Wood, 2005). And even when there are sex differences be sure to check how large or small the differences are.

Market Mavens

One line of research that has taken up the issue of gender (or really, sex) and WOM concerns market mavens (Feick & Price, 1987; Higie, Feick, & Price, 1987). Market mavens tend to have information about a lot of different products, shopping venues, and general information about the marketplace. They also tend to start discussions about shopping or market-related information with other consumers and are also highly responsive to requests for this information. Market mavens have been distinguished from opinion leaders (who often have product-specific knowledge and experience) and early adopters. Market mavens are identified by their agreement or disagreement to six questions (for example, whether people ask them for information, whether they like introducing new products to friends, whether they are perceived as a good source of information for new products or sales, etc.). Based on their responses, people are classified into low, medium, or high market maven status. People who score in the “high” group are referred to as market mavens. Multiple studies have found that market mavens are more likely to be female but are not differentiated based on other demographic variables like age, education, income, race, household size, marital status, or number of children under 18. Market mavens do, however, have higher media consumption.


In part because early research found that market mavens are more likely to be female, a lot of attention has been paid to females. This has prompted researchers in Germany to search for male market mavens, which they dubbed “Mannmavens” (“Mann” being German for male; Wiedmann, Walsh, and Mitchell; 2001). They replicated the use of the Market Maven Scale and found it to be valid for German consumers. When they compared male and female market mavens based on other demographic variables the researchers found them to be very similar. Thus, they concluded that market maven trait is equally relevant to both men and women. They did, however, find differences between male and female market mavens in terms of their decision-making styles (see pp. 203-207 of their article for a discussion of these differences and practical implications for marketers to apply this knowledge).

Gender and Sports Marketing

Another study investigated gender differences for WOM behaviors surrounding sporting events (Swanson, Gwinner, Larson, and Janda, 2003). These researchers looked at different psychological motivations for attending sporting events and also their verbal recommendations made to others. The four motivations they considered were team identification (perception of connectedness to a team), eustress (the positive anxiety and emotional stimulation that leads people to invest in being a spectator), group affiliation (the desire to be included in a reference group and share the experience with others), and self-esteem enhancement (the desire to maintain or boost one’s self concept). The researchers found that the relationship between group affiliation and WOM behavior was stronger for women than for men, meaning that women were more likely to make a recommendation for others to attend the sporting event due to the group affiliation motivation. Men were more likely to engage in WOM behavior based on self-esteem enhancement; however, the researchers cautioned that this could be unique to the sports context (their explanation was that discussing sporting events might enhance men’s self-esteem more so than maintaining women’s self-esteem).

My Own Research on WOM and Buzz Marketing Communication

In my own research on WOM and buzz marketing communication practices, I found some interesting findings regarding sex differences and similarities (2). First, the majority of buzz marketing agents affiliated with the particular Agency I worked with were female, just over 80%. Most of my students are not surprised by this finding.

A second point concerns frequency of interactions Agents have over the course of a week, and the number of those interactions that include talk about an organization, brand, product, or service (aka, a WOM episode). The percentage of total interactions that include a WOM episode is called the E/I Ratio. Interestingly male Agents report slightly more interactions than females and more WOM episodes. My students are surprised by this. However these differences were so small that they were not statistically significant. Their E/I Ratios were very similar as well, both right around 26% of their total interactions including talk about an organization, brand, product, or service. Agents could not be differentiated based on all other available demographic variables, such as age, education, income, and race.

When presenting this information in class one astute student said that women may have had fewer conversations because their conversations tend to be longer than male’s conversations. Among Agents, though, the average length of interactions only differed by about a minute.

Thus, in terms of frequency issues, male and female buzz marketing Agents were very similar. But does this same pattern hold for non-Agents, or “everyday people”? To help compare non-Agents to Agents I have had university students complete the same surveys (see Carl, under review for details). With non-Agents, females report more interactions, more WOM episodes, but have about the same percentage of those interactions include talk about an organization, brand, product, or service. These differences are larger than for the Agents but still not statistically significant. One difference that is quite large for non-Agents is that females reported significantly longer conversations, in fact, twice as long as what the males reported.

When comparing Agents and non-Agents, Agents had about 30% more interactions, nearly twice as many WOM episodes, and more than double the E/I Ratio. These differences were all statistically significant.

What can we conclude from this? Among non-Agents the sex differences, although not statistically significant, are more in line with what is commonly assumed about communication differences between men and women in the U.S.: women talk more frequently, have longer interactions, and also have more WOM episodes. However, among buzz marketing Agents, the differences are less pronounced, and at times, counter to what many typically assume. This suggests that gender (again, more accurately, sex) may be less important than the fact people volunteer to be buzz marketing Agents. Thus, whether or not someone is a buzz marketing agent is more likely than sex to explain differences in the number of interactions, WOM episodes, and E/I Ratio.

In Closing

To sum up this posting, social constructions surrounding males and females shape our lives in powerful ways and deserve our attention. However, these constructions may not always be relevant in every situation and change over time, so it’s important to continually interrogate whether, how, and in what contexts gender differences and similarities are relevant.

By no means is this a comprehensive discussion of all the extant findings regarding gender and WOM practices so I invite people to add to the discussion here by including other research findings and insights from personal experience. More findings based on Sex of Respondent and Sex of Conversational Partners is forthcoming (Carl & Noland, in preparation).

References for this Post

Carl, W. J. (manuscript under review). What’s All The Buzz About? Everyday Communication and the Relational Basis of Word-of-Mouth and Buzz Marketing Practices.

Feick, L. & Price, L. (1987). The market maven: A diffuser of marketplace information. Journal of Marketing, 51, 83-97.

Higie, R. A., Feick, L. F., & Price, L. L. (1987). Types and amount of word-of-mouth communications about retailers. Journal of Retailing, 63(3), 260-278.

Swanson, S., Gwinner, K. Larson, B. V., & Janda, S. (2003). Motivations of college student game attendance and word-of-mouth behavior: The impact of gender differences. Sport Marketing Quarterly, 12(3), 151-162.

Wiedmann, K., Walsh, G., Mitchell, V. (2001). The Mannmaven: An agent for diffusing market information. Journal of Marketing Communications, 7, 195-212.

Wood, J. T. (2005). Gendered lives: Communication, gender, and culture (6th ed.). Belmont, CA: Wadsworth.

Notes for this Posting

(1) More critical approaches contend that even the distinction between “sex” and “gender” is a cultural construction. back

(2) In this particular buzz marketing Agency, all Agents voluntarily affiliate with the Agency are not employees of the Agency. back


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