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As is typical of academic research and testing, there is an extensive review of the results of other WOM Marketing studies all the way back to the 1970s upon which the hypothesis for this test was formulated.
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Analyst and marketing optimization expert Jim Novo s review of Firm-Created Word-of-Mouth Communication: Evidence from a Field Test, Marketing Science, Vol. 28, No. 4, by David Godes and Dina Mayzlin, 2009. Posted on the Web Analytics Association web site at www.webanalyticsassociation.org/en/art/712.
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As in every aspect of social media metrics, there are nascent tools offered that try to bring order out of the conversational chaos. FMS Advanced Systems Group s Sentinel Visualizer (Figure 3.4) is one example. The Sentinel Visualizer claims to answer questions like: How highly connected is an entity within a network What is an entity s overall importance in a network How central is an entity within a network How does information ow within a network It suggests that you can: Identify central players automatically. Locate organizational cut-points. Perform timeline analysis.
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Figure 3.4 The Sentinel Visualizer includes the faces of those talking about a speci c subject. Organize complex data relationships into cells and cliques. Find all paths, the shortest path, or the best paths between two entities. Further, Sentinel Visualizer offers a time slider control to see how networks form, change, and interact with each other over time down to the second. I suppose if you were
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in a legal battle about who said what to whom rst, secondby-second social graphing might just be considered useful. But the purpose of temporal conversation tracking is to spot patterns and predict behavior. It provides insight as to when to release information by day of week and time of day.
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Companies like Axiom (www.axiom.com), Rapleaf (www. rapleaf.com), and Unbound Technologies (www. unboundtech.com) are mapping the relationships in a different way. Rather than follow conversations, which is tricky at best, these companies scour the social networking sites and blogs for friends and blogrolls. This information is declarative rather than inferred. I am your friend. I include you in my blogroll to indicate that I think your posts are worth reading. This information is there for the taking it s public. With this connection information, Axiom can match their own database with yours and report back on which of your customers or prospects is linked to which others. You now know how your community is linked. That is, you know which of those in your database make up a sub-community. That s invaluable for sending targeted messages.
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Twitter is the current darling of the social media world. Yes, that statement dates this book as written before and were recognized as the game changers they are. Since I have no powers of clairvoyance, let s explore the variety of ways people are trying to measure in uencity with the game changer at hand.
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This one is simple, easy to understand, and already covered as useful to a point, but not indicative of success. It s also easy to accomplish. You can automatically nd and follow people who will automatically follow you in return. If all you want is more followers, you can ip that switch but with no residual value.
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If John is followed by 50,000 people who have no followers of their own, he is in a world of hurt compared with Jane, who is followed by 10,000 people who are each followed by 1,000 others. The guarantee of creating an opportunity to see for 50,000 pales next to the opportunity to generate an opportunity to see for 10 million. Even if you assume that only a fraction of them retweet say 10 percent you ve still reached 1.1 million. More important, that extra million received a retweet, which is more highly valued by the individual. If you boast about your new car, I absorb the fact of the launch. But if Jane retweets your message, it implies that she thinks it s worthy of my attention, rather than just being a promotion from the manufacturer.
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