There has been a surge in companies and products in the blog measurement and monitoring space. While the two are necessarily linked (you really can’t measure what you can’t see) there is a clear need for monitoring services that aggregate content from across participatory media – including ecosystems such as MySpace, ITConversations and Wikis. In these spaces we aren’t just interested in what is being said but also what is being done – links created, lists joined, podcasts delivered…
The BBC reports today that more and more firms are paying greater attention to what blogs are saying about them – and even trying to meet the bloggers halfway.
Sooner, rather than later, I hope we will also see non-rules-based tools emerge. I can monitor what I need to monitor – but what about emerging conversations, brands and people? How do I know about them as they are emerging? Measurement systems tend to be only useful in the context of what we tell them to measure.
Hugh touches on this in the BBC pieice when he speaks to “micro-brands” –
“What I’m interested in is what I call the global micro-brand,” says Mr Macleod.
“Now with the internet, creating global micro-brands is cheaper and easier than ever before. You can start off and have a product and market it on a global level much more easily than even 10 years ago.”
Micro-brands are going to have an increasing impact on “macro-barnds” – so tracking them and then correlating their impact on business and marketing outcomes will be crtical. This is where we move from monitoring to measurement and on to correlation. Correlation of buzz and impact will be one of the new fronteirs in measurement.
Thanks to Steve for the link to the BBC story.
Great points Andy. What we find is that there is a HUGE misunderstanding about blog measurement and monitoring. It’s one thing to monitor i.e. scrape all the postings you can get your hands on. It’s a very different process to actually measure the impact on your conversations and your brand, partiuclarly when none of these automated tools even look at comments or the type of qualitative analysis that you’re talking about. So far, we still have to do it the old-fashioned way — we actually read them, analyze them and figure out what it all means.