Conversations that influence


With the ever increasing volume of data flowing through the blogosphere, we constantly hear from clients about the challenges of sorting through conversations that will have an impact on their interest graph and those that are just casually commenting about a topic or brand.  In other words, can we isolate only those conversations and individuals that will influence a brand, so that we’re not listening, analyzing and responding to a lot of random chatter?

Many of the leading  tools in the market have already begun to assign influence through a combination of variables including: conversation volume, keywords and high level scores partnering with companies like Klout and ComScore.   Focusing on the conversations of the more influential people can often provide better insight towards trends.  And it can also make the process of engagement more efficient.  As we think about how this relates to Social CRM, a true determination of influence helps to provide an additional layer of knowledge around customer and vendor relationships.  The next step will be mapping the relationships and similarities among the most influential voices to determine how people are interconnected and what that can mean to the business.

One vendor who is working on this today is a company called eCairn.  I sat down with Dominique Lahaix, eCairn’s CEO, a few days ago to go through a quick demo of the product.  Rather than having to find influencers from scratch, eCairn has already identified over 300,000 bloggers who belong to some 300 different “tribes”.  These tribes include everything from people who talk about nails to bloggers interested in healthcare.  Looking at specific topics and conversations within these tribes, a company can listen and quickly put together an influencer map that identifies connections between groups and uncovers relationships that may not be obvious at first glance.  Over the years, I have seen the painstaking process of building similar influencer maps, and the option of having a head start on this type of work is something that should help many strategists.

As we move forward, the need to filter social media conversations based on influence, urgency and impact will become more important to social business.  The more that we can automate the ability to do this, the easier it will be for organizations to develop strategies and processes for business units to take advantage of this additional layer of data.

If you use other vendor technologies that help look at influence, I would love to hear about them, so please comment below.

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