Recently a friend asked me for some pointers on the measurement of social media, such as blogs.
I have found that Jeremiah Owyang has a lot of interesting things to say on this topic, as exemplified by has article What should we measure and the document Tracking the Influence of Conversations: A Roundtable Discussion on Social Media Metrics and Measurement.
Yet it isn’t sufficient that we measure conversation on the web, we must also consider potential traps hidden in the data – we need to interpret it.
Consider the case of a blog post. The extent that a post has been read and has involved a blog’s readers might be deduced from the number of comments the post has generated. Two potential problems arise using this metric.
In the first place, the number of comments may be low despite a high number of visitors to the post, particularly for a well written post devoid of any controversial statements. Or perhaps the post contains a call to action, such as following a link, which if successful, would lead visitors away from the post before considering whether to add a comment or not. My companion SEO Blog in Italian is running a SEO quiz. The post in question has had over 900 visits at the time of this writing, yet it is devoid of comments (there is a call to action to visit the SEO quiz). To the extent that we have access to data on visits and page views, the isn’t any significant problem, we are in a position to cross-check data before reaching any conclusion. Such checks do become more complicated when we do competitive market analysis.
A second problem is that the measurement of the quantity of comments can not quantify the value of each comment. Are there comments that have added something to post? Or are they similar to “I’m a fan boy” or “Me too, I agree”?
Moral of the story: approach social media metrics with a critical spirit and avoid hasty judgments.
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- IKEA Italy: what not to do when facing a social media crisis
- Links and Algorithms behind Blog Statistics: BlogBabel reopens.