Teaching SMM #5 – METRICS Monitoring and Listening

Note: This is a continuing excerpt from what I teach my social media marketing classes on introduction to metrics and measurement…

Monitoring and Listening to Online Conversations

There is an incredible amount of information, discussion, and “content” being created and posted on the web every day. Former Google CEO Eric Schmidt was quoted in 2010: “There was five exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days, and the pace is increasing.” Even though Schmidt may have exaggerated a bit—the exact figures are subject to some debate (Finley 2011), there is no doubt that we are living through an information and knowledge explosion. As noted several times, social media marketing is commonly referred to as “word of mouth on steriods.” Key metrics of social media efforts should logically include what is being said about an organization in social media or other online conversations.

Monitoring the Conversation

One measure of a social media campaign is the buzz, quantity of online conversations involving an organization or its services. By using Google, Google Blog, and Google alerts, a participant or organization can regularly monitor the conversations online and detect how often an organization or its products or services are mentioned. A key question is, of course, whether “buzz” seems to be increasing in line with SMM efforts and whether it changes based on new social media marketing campaigns.

Word of mouth does not follow the old Hollywood public relations dictate that all publicity is good publicity. Certainly all word of mouth is not good. It would be useful to track positive word of mouth separately from negative WOM. Again by using Google, Google Blog, Google alerts, and the social media search engines, or the paid services to identify the comments, an organization can regularly monitor the conversations online, collect and store all comments and mention of the organization, and then periodically rate comments as positive, neutral, or negative. Metrics related to positive/negative buzz include:

•     Daily or weekly levels of positive and negative buzz

•     Percentage of an organizaton’s buzz that is positive (percentage positive buzz)

•     Percentage negative buzz

•     Share of buzz by an organization

•     Trends in all of these levels

Share of buzz is a common goal of social media efforts as an increasing share of the total conversation within the defined market space or topics is seen as winning the WOM battle. A firm may wish to compare its share of buzz to its market share of products or services within the same competitor group.

How does an organization collect and analyze the data and compute the share of buzz? Small businesses or specialized B2B business may be able to simply find the comments using Google, Google Blog, and other search engines, copy and check for relevancy, classify and compute the numbers, ratios and trends. There also are services that specialize in tracking SM and online conversations. One free service to track the total numbers of conversations is SocialMention™. For a fee there are numerous tools such as Radian6™, BuzzLogic™, TNS Cymfony™, Sysomos™, Cision™, and Buzzmetrics™ that will collect the data from online conversation and compute some of the analysis including share of buzz, computing the number of comments about an organization to the total number of comments about the organization and its competitors. Buzz, share of buzz, and trend of buzz are all interesting ways to view the WOM effect of social media efforts. Some organizations view “share of buzz” as the key measure to judge their social media efforts. Some monitoring services employ algorithms to classify negative and positive buzz or even perform basic ethnographic analysis such as combined comments of similar themes or looking for trends.

Listening to the Conversation

An article in the Journal of Marketing reported research showing that good ideas for product innovations on automobiles were developed from observing the actions of an auto maker’s online community of customers and prospects, when looking at options for cars.[i] The customers were limited to alternative choices on the site: imagine how much richer the data would be if they were freely conversing and had more choice of options to discuss. In the blogs, forums, on the website, FB, Twitter, and LinkedIn, customers may be conversing about their thoughts, opinions, and feelings of an organization, its products and customer service, and its competitors. The possibilities for useful market research are endless—think of a 24/7 focus group without the observer and group effects that so limit new ideas in a group[ii].

Consumer products firms, such as P&G, Nokia, Coca-Cola, and Nike, have for years hired trained anthropologists to watch and listen to users to find out their deep thoughts, feelings, impressions, and creative uses of their products. Ethnography is a deep study of a cultural phenomenon without limited preconceived ideas using observation, interviews, and other primary data. Marketers have used ethnography to help understand how to sell cell phones in poor villages in China and India, what urban youths value in sneakers, why some insect spray customers wanted to see the pests die, and many other valuable product and marketing insights. The insights are often surprises, which is why the observer or researcher seeks to limit preconceived notions. Now an organization may not have to send researchers into the field to observe interactions and conversation: Similar rich data may now be available simply by listening online. Someone in an organization can be observing prospects and customers having detailed technical discussions on forums or groups; venting anger on Twitter or blogs; or sharing short Facebook comments.

The observer effect, the change of the phenomenon being measured because of interaction with the researcher/observer may be eliminated in online data. However an issue with the researcher being invisible is the application of the principle of informed consent, the basis of ethical research for qualitative research and human subjects. Subjects of human research and ethnographic research have the right to know that they are the subject of research, what the research is about, and to freely choose whether or not to participate. It may seem reasonable to consider Tweets as public data not subject to requirements of informed consent (an argument can occur even here) but what about other networks where there is at least some pretense of membership or privacy? The ethics of such research will be an area of concern and attention as online qualitative research grows. An organization should adopt a policy for online qualitative research that considers this issue of informed consent.

Kozinets (1999) uses the term Netnography to describe ethnography using online data, although other social scientists prefer to simply refer to online ethnography[iii]. Kozinets advocates gathering and analyzing the data with the same care that anthropologists or sociologists use in studying offline phenomenon: in fact, using trained social scientists to do the analysis if possible. If a firm does not current have the budget or priority to hire an expert analysis of the online information, it can still be valuable to have a knowledgeable insider monitor the data, looking for trends or insights.

Key Takeaways

•      Buzz should be monitored in a variety of ways: number of daily comments about your organization, trend in the number of those comments, changes with different SM campaigns, positive versus negative buzz, and share of buzz.

•      Beyond simply counting mentions there is rich content and information online about an organization, its customers, competitors, and marketplace in blog posts, forums, comments, as well as SM conversations in the data available online.

•      Organizations should both “monitor” and “listen” to online conversations.

•      Internet ethnography is challenging and may need to be done by algorithms for consumer brands and large firms, but many organizations, such as B2B firms, small companies, and local nonprofits can benefit by studying information in-house.

This is part #5 of an excerpt about “Metrics” from an early draft of a text for teaching Social Media Marketing. Please do not copy without the approval of Flatworld Knowledge and Gary Schirr. I welcome thoughts on omissions, additions and corrections!!!

Other articles:

Teaching SMM: METRICS #1 Importance of Measurement

Teaching SMM – METRICS #2 Activity Measures

Teaching SMM – METRICS #3 Measuring Influence: Art or Science?

Teaching SMM – METRICS #4 Influence Scores

Teaching SMM – METRICS #6 ROI of Social Media Marketing

Teaching Social Media Metrics – The Hangout (Video)


[i] Urban, Glen L. and John R. Hauser (2004), ““Listening In” to Find and Explore New Combinations of Customer Needs,” Journal of Marketing, 68 (2), 72–87.

[ii] Schirr, Gary R. (2012) “Flawed Tools: The Efficacy of Group Research Methods to Generate Customer Ideas.” Journal of Product Innovation Management 29(3): 473–488.

[iii] Kozinets, Robert V. (2009) Netnography Thousand Oaks, CA, Sage Publications, 232 pages.

This entry was posted in Klout, Social influence, Social Media, social media marketing. Bookmark the permalink.

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