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SocialCRM Data – Let’s get the conversation going

Given Paul Greenberg’s profound and accurate ‘stake in the ground‘ – it is now time to move forward and focus on making it all work, not on what it is called! The data (type, quality, quantity, immediacy) is a crucial element to making it all work (work = offers significant business value), and the issue has been nagging at me for most of the week.  I typically take a logical, business value focused and pragmatic approach to operational systems. But this data question is taking more thought. Social Data does not always – ok, barely ever – fits into the standard patterns we have defined, the reason is actually simple, data in the ‘Social’ realm encapsulates emotions, and emotions are complex (ie, they do not usually fit into rows and columns).

A very brief, review to catch people up to my thinking

Most business analysts and consultants, when talking about customer data, draw diagrams or charts. Within the charts the data elements are grouped into bins. Examples of the bins are: Demographic Data, Transactional Data, Service History Data, etc.,… In the new SocialCRM or Web 2.0 world, we have more (new?) bins; Clickstream (Google Analytics type of output)  Social Media (Youtube, FaceBook, LinkedIn, Jigsaw, Twitter to name a few). Then we typically start trying to put the data bins into one of two buckets – Operational or Analytical.  Traditionally (don’t beat me up on this), Operational data is readily available, and Analytical takes a little time (days at least). This is where the old world and new world collide – In the realm of SocialCRM, what used to be in the realm of Analytical, now is important day-to-day. Not only is it important day to day, but some suggest that it should be available offline. Offline means = I am at my computer, and it is as if someone turned off the Internet. (I will tackle my thoughts on that another day).

Actionable data – Sales and Service

There are some really smart people who spend time thinking about data analysis, (Radian6 for example) for the Analytical bucket I described above. Marketers love the data, and lots can be learned when the data is ‘sliced and diced’. Since I am not a pure marketer, the focus of my thinking is in the area of 1 to 1. What can one sales person do with the data, or what can one Customer Support person do with the data? I also know there is a sub-topic of taking marketing type data and using it to offer 1 to 1 advice – I am not going there either (just yet).

Taking a look at the ends of the spectrum:

Twitter – “@mjayliebs I want to buy your product, it is awesome” – Well, that seems pretty obvious; figure out who wrote it, route it to a sales person and sell them something. (Pure Operational)
Twitter – @mjayliebs “Check out my [6 minute] video about how great your company is [by a nearly broke college student] (Er Ah, Um…not so obvious what to do with it).

What about a couple more middle of the road:

Twitter – “@mjayliebs – One of my clients is thinking about your product, but it is way too expensive, lower the price” Operational or Analytical? Actionable? Or, not?

Twitter – “@mjayliebs – I like parts of your product, but there are issues, check out my blog review”

Yes, I focused on Twitter, but tried to incorporate some others Social Media channels as well.  I am also sure that people could offer many examples the run the spectrum from useful to useless. The question is what processes do you have in place to organize the Social data to make it actionable? I know that there are products and services available, and more coming soon. But, what about for small business? Can sentiment (or sentiment analysis) be made useful and/or actionable to the Support folks? What about to the Sales folks?

One could easily argue that first defining the types of data we are talking about is a more important first step, but hey, it is a Saturday, it is sunny and I am at the keyboard (I am outside) – my prerogative!

Comments on this entry are closed.

  • scorpfromhell August 2, 2009, 11:35 AM

    Awesome post Mitch! And timely too! I have felt social data to be an area that has been neglected for the most part. And I do not have much insights into this area as I am not a DW/BI guy. :(

    IIRC, Anthony Lye of Oracle calls it the social metadata. Not sure, may be was referring to the stars, ratings, tags, likes, etc. that can still be put into a database. Nevertheless, the real deal is with all the unstructured data out there on the social intarwebs!

    I have responded in a bit more detail on my blog, since my “comment” was getting a bit too long! 😉 I guess my post is more a prelude to your post than a response! 😀

    BTW, Mitch, I love the way you tone down the complexities of any deep topic with a very few words, where I tend to write tomes about that to make it understandable! My wife always chides me about that defect in me. :(