Are Conversations Measurable
April 2nd, 2009Apparently YES. Those who attended Beyond The Buzz: On Measuring a Conversation at Web 2.0 Expo. The conversation was led by social scientist Marc Smith (Telligent Systems) and social psychologist Kate Niederhoffer (Dachis Corporation) captivated the audience with its eye opening data, methodology and very cool graphs and charts! The presentation slides should be posted here at some point should it not be available by the time this post goes live. Make sure to check back! To listen in on what people thought about this presentation the Twitter hashtag is #w2e #buzzzz.
As information sharing becomes more conversational, marketers are seeking ways to define the metric around the “noise” as it influences a call to action. Katie and Marc introduced the idea of conversation measurement based on the principles of social science and social psychology. The duo pointed out that the practice are not one and the same, yet in this instance are complementary metrics agents.
According to Katie, linguistic style offers rich insight and color into the multifaceted dimension of an individual. A conversation can be divided into four stratas: relevance, mindset, role and ecosystem. Traditional metrics measurement approach practices the black boxing of conversations therefore rich content and information is lost. She further elaborates that listening to micro conversations offers a layer of rich detail about your brand you may not have known before. What buzzwords do people associate with your brand? Marc chimes in that further metric detail can be viewed by looking at the network pattern of an individual. Individuals have roles to play in a network which Marc identified as follows:
- spammers (often times not real people)
- flame warriors
- answer people
- discussion people
For social media to work, a balance in the conversation spectrum must be achieved. He calls it “a collective spectrum that requires a balance of roles.” Marc demonstrated that by using NodeXL a tool that can analyze an individual’s social behaviour across multiple networks and weave the information into one digestible graph which helps determine their role pattern.
Why is this information valuable to marketers? Here are my thoughts:
- Allows a marketer to test multiple messages across individual roles and networks
- Specifically design based on a user profile’s degree of engagement
- Measure the influence of an individual role across multiple networks
- Determine the probable response of an individual type within a network to the brand. IF I do X, individual role X will respond negatively to this message
- It offers the opportunity to access predictive data versus reactionary data
- Identify probable brand ambassadors
- Associates the impact of the message based on the buzz created and response to call to action
- Metrics around conversations and number crunching of quantifiable data are useful ammunition to help support and/or correct engagement programs
Overall, I believe this type of data and insight is invaluable to marketers who are advocates for social media yet are finding it a challenge to implement within their organization. It also helps validate the impact of marketing and social media to the bottomline.
I’m pretty sure I missed a few points during the session, so please help add to this. Thank you!
Tags: Research, Social Media
