In his latest post Gary Angel focused on how the platforms we use to measure with also constrain us , I suggest reading his Semphonic blog post in full.  The main point of his post is the constructed metric of “online social mentions” doesn’t  make sense and social platforms provided metrics like this one, only because it made sense to them (but turns out to be utterly misleading and ultimately meaningless to most users).

We need to understand that the measurement of consumer sentiment and PR effectiveness (and Influencer sentiment) are two fundamentally different tasks that need almost completely differentiated samples. The fact that our tools give us counts across these things (and across other categories that we don’t care about), shouldn’t lure us into believing those counts mean something.

I’ve often remarked how similar is the current experience of Social Media Measurement with the early days of Web analytics that I remember. We are all making so many of the same mistakes – Semphonic included. But here’s where our deep experience in digital measurement is actually bearing some fruit and proving to be a real advantage. Because this time around, we are learning much faster. In Web analytics, it took us years to learn the metrics to ignore and the metrics with real meaning. It’s taken even longer to understand many (if not all) of the ways our tools both help and hinder us in our task. But we’ve learned that just because a tool reports a metric, that doesn’t make it meaningful.

One of the points I want to add, while most of the social listening platforms evolved out of glorified news clipping services (as Gary points out in his post), to fit mostly MARCOM needs, those needs have morphed towards something more hybrid and misleading, a form of pseudo market research and opinion analysis for unwitting clients that is fundamentally flawed and unsound, delivered using listening platforms that can not support the analysis, in order to support a market need (but perhaps in a poorly adapted manner).

Perhaps this Social Media Analytics in the Marcom space is  just one more bubble waiting to pop (and I’ll have more to say about that in my Predictions for 2012  that I will release later in December); and that has been my suspicion for some time.  But it also tells me that platform vendors have been busy trying to give audiences and markets what they thought it wanted, without ever truly understanding what it needed and truly wanted, and “social mentions” is just one example of it.

Web Journal

Mike White, a UK PR professional wrote a nice review of my book which tells me my ideas are spreading to people who might, in other circumstances, not have seen or been as receptive to them, had the  book not appeared.  While Mike is not the first to point out parts of the book that are platform and vendor specific may need to be rewritten in a few years (which I’m totally up for), I think most of the book will still be fully applicable for a long time, and the parts that really are vendor and technology specific, as late as 2014. By that time, a second edition, I’m sure, will be out.

Read a good post on how to track complaints using Google Analytics - the approach was fairly straight forward and it works because the form being used lends itself to being captured (using a script), but it also reminds me that to capture business processes digitally, they need to be encoded (arranged)  in a way that lends to that capture – and too often, that’s not done.  So, if you want to capture a business process, sometimes you need to change the process so it can be captured (by the analytics tools and platforms at your disposal).

A report by IBM suggests that Business Analytics Leads the Way, according to the IBM Tech Trends Report 2011 and that “automation”, which is another way of saying “scaling business analytics” was the top focus.

“…. Automation and streamlining processes help to deliver analytics more efficiently saving man hours and money. Automation also assists in the elimination of human errors which can be critical in business intelligence reporting.”

But not everything is scalable, or capable of being automated, and a lot of thought needs to be put into thinking about what parts of a process can be streamlined, and what can’t – and how much effort or cost it takes to do so (and if it’s worth it).  Earlier this month I gave a webinar on this very subject for Internet Evolution, an IBM sponsored community, focusing specifically on the Costs and Benefits of Business Analytics (that outlined when it was profitable to invest in streamlining business processes via Analytics, and when it wasn’t, and my presentation was well received.

It just so happens that I am doing another lecture on Applying Social Analytics for Internet Evolution this Friday, December 2nd, at 2PM.  Here’s a short description of what I’ll speak about.

Applying Social Analytics

Join us on Friday, December 2, at 2:00 p.m. EST.

Deploying the technology necessary in order to communicate with customers is only one step toward becoming a social business. The bigger piece is being able to analyze those communications, unlock the insights of your customers, and turn their signals into applicable information. Our expert will discuss the importance of social analytics and what pitfalls to avoid when investing in enterprise analytics tools.

Happy with the presentation and look forward to sharing it with the Internet Evolution community on Friday (your free to join, just sign up to be a member at Internetevolution.com).

Read an interesting post in Scientific American that says people are often fooled by evidence but that people can often absorb a truth more forcefully, if they can arrive at it one step at a time than if they get it thrown at them all at once. That would seem like common sense – but it’s interesting how the finding is demonstrated.

Imagine, for example, that you are in a library (assuming people still do such things), and you’ve become lost. Are you in the Science Fiction or the Fantasy section? Of course, you could wander the shelves until you find a helpful sign, but it’s faster to simply look at the books on the shelf next to you. You see:

Book 1: Piers Anthony’s Blue Adept: The Apprentice Adept
Book 2: J. K. Rowling’s Harry Potter
Book 3: J. R. R. Tolkien’s The Hobbit

You’re not sure how to categorize Book 1, so it’s not good evidence for either Science Fiction or Fantasy. Books 2 and 3, however, have wizards or elves on their covers, and you might firmly classify them as Fantasy. By now, you’ve weighed the evidence and concluded you’re in the Fantasy section.

Here’s where things get interesting. If someone had simply handed all three books to you at the same time, you might feel that it’s somewhat likely you are in the Fantasy section. But if someone handed the books to you one at a time, you might conclude very strongly that you’re in the Fantasy section. Even though the books are the same, you would weigh the strength of the evidence more heavily when you processed them in turn, rather than all at once.

This finding seems to demonstrative of a general principle – that it is best to chunk out information, and give it out gradually, allowing people to gain more confidence (over repeated exposures), though if readers have additional ideas of what it means, feel free to share them here.

Finally, one of my friends shared a post with me on Facebook on Why Digital Talent Doesn’t Want To Work At Your Company from Fast Company that totally supports my point of view that many companies, despite the lip service are not able to  provide them the right opportunities.

That’s about it for this post – Thanksgiving was enjoyable and spent with friends, and I shut down for a change, and found I could not write much, decided to give into it, and just go with it.