I got a peek look at PeekYou’s PeekAnalytics platform over the last few days and thought I’d share are comparision report between me and @Collectual (Jennifer Roberts over at Collective Intellect, since we just had a Point/CounterPoint exchange last week at AllAnalytics.com in Social Media Measurements Don’t Always Add Up ).

PeekYou, as an social aggregation service, has been available for several years, but you could not get this level of analytics drill down, using their platform, till now.

You can download the report I created today, here, while BL Ochman published a more extensive collection of PeekAnalytics Reports on Scribd.

I was thinking to compare myself with someone similar in my space for this post, rather than a celebrity who had way more followers than I have, etc.

I haven’t had a chance to live with these reports yet, but I do want to point out they are based on information collected from many sites, in fact, at least 60 sources are used to construct the information breakdowns, which is quite different, and more accurate (because it’s based on much more information) than you can get in any other single platform on the market today, for information about an individual and their interests/followers, etc.

The other thing I want to point out is that I’m on PeekYou’s Advisory Board, and I get to look at the neat stuff they are cooking up on a regular basis.

AdAge has an excellent review of PeekAnalytics by BL Ochman - I won’t repeat it here and would rather focus on what forward thinking applications of this new platform.

Currently, PeekAnalytics uses the Social Data from the 60 sites and services it pulls information from to enhance Twitter Analytics – but I think eventually, the platform will expand past it’s starting point (Twitter).   Since PeekAnalytics is evolving, as are many of the emerging I think we need to look as this data as more accurate than what we could get before; after all, absolute accuracy, doesn’t yet exist (and may never exist, for all I know, in Social Analytics, but the data is still extremely valuable when properly collected and used).

For me, the best uses of PeekAnalytics come out of defining certain goals and their corresponding metrics.

For example, if we want to reach followers of an influencer what have what is termed “high social use” (spend a lot of time on blogs, messages boards and twitter, etc) who also have an “Ivy League” education and a beyond average interest in Hospitality, PeekAnalytics is capable of finding such individuals, with a much higher accuracy level than what we’ve been accustomed to, up till now.

To get multidimensional comparisons (such as the one, above)  you will probably want to use the PeekAnalytics API, which is an interface PeekYou offers to developers.

I think “Social Pull” is a good metric to use (there are no standards in Social Analytics, platforms are constantly innovating here) when you want to decide who to cultivate based on the potential for an individual to spread a message.

To be honest, @Collectual followers are very similar to my own, and in some sense, what we’re really looking at here is the who we’re trying to reach – and how an individual is a nexus or pathway for reaching an audience.  The more we can, with a reasonable amount of confidence, make distinctions in so far as Twitter followers  interests, industries and affinities, the more we can tie Key Performance Indicators to reaching specific individuals, who are the target of a marketing campaign or other type of outreach.

As I have regularly provide input to PeekYou, I will continue to guide them in how they evolve this platform, which I think, is a measured step forward for Audience Measurement using Social Media.

And to end this post, I want to leave readers with a thought – that in this space of Social Analytics, there is so much that is quickly evolving, much of it that seems to look similar, that it is often hard to make meaningful distinctions between what the various existing and emerging platforms and technologies offer.

For one thing, the data in PeekAnalytics is based on much more than Twitter -though it may be expressed via Twitter, the actual information comes from several sources outside of Twitter -(which is aggregated, and cleaned)  that’s an very important distinction that helps to establish much more trust in this data, than what you get out of your average Twitter Analytics platform.  There are also several dimensions of data you can pull with PeekAnalytics that you typically, can’t find elsewhere.

The closest comparison might be Quantcast, but Quantcast works on brand websites, not individuals and their social accounts – so while two platforms have some similarities, they are really very different.

I think we’re just beginning to see what PeekAnalytics is capable of  and it’s definitely analytics I plan to be using often on my projects.