Brandtology is starting a new Social Media Analytics Academy – was just notified about it today and wanted to share the news with my readers (press release)- esp those in Asia.  Right now I haven’t seen a course offering – it will be all hands on and in person training, though.

Within the various courses offered by Brandtology, participants would be able to learn about the Social Media landscape in the Asia Pacific Region, with focus on the unique characteristics of each market.

For instance, although Twitter is wildly popular in most countries, it is banned in China, which has its own version called Sina Weibo, while Taiwanese prefer a micro-blog with a timeline by the name of Plurk.

More importantly, the courses would also touch on the measurement and evaluation of Social Media Success, and the use of data analysis tools and services for identifying what creates viral effects online, as well as determining top influencers and key engagement channels.
“Data without analysis is meaningless.

What’s more important is to be able to go beyond simplistic statistics such as buzz, views and re-tweets to find out the driving factors of internet word of mouth, and the overarching concerns of netizens about a brand and its products,” Dorothy Poon, Programme Director of Brandtology Academy, opined. “Extracting actionable insights and using social media analytics to create an effective feedback loop is more important than merely finding out what’s being said and not doing anything about it.”

At the end of the course, participants will be required to undergo a rigorous certification process and demonstrate sound understanding of the key concepts taught in the course.

The first two runs of the Social Media Analytics courses in September are already fully booked and the third run will commence in October. For inquiries, please email academy@brandtology.com or visit http://www.brandtology.com/academy

I spoke with Dorothy Poon a few weeks ago over lunch and dinner where she was visiting New York for Brandtology meetings – the Academy was a hush rumor then – it may have been alluded to in our conversations, but not actually discussed.   I was also speaking with Jay Vasudevan who who introduced me to  Brandtology  and is my primary contact.

According to Jay,  Brandtology Academy will provide sessions in September and they  will be in person,  open for anyone who is interested in learning about Social Media – analytics, monitoring etc.

It’s tempting to see parallels between Brandtology Academy and Omniture’s Certified Professional Program or even the Web Analytics Association Certification for Web Analytics that recently got underway (though it was discussed when I was still part of the WAA Board).    On the Pro side, for certification, there is so much material and disinformation about Social Media  out there that a professional training program with certification, what Brandtology and the WAA offer, is appealing both to applicants and employers.

On the other hand, there are those who feel social media is too young a field to have certification – one being TheBrandBuilder – since it’s not clear what best practices are in many cases.   More often, I’m at odds with TheBrandBuilder (actually, we agree on most things, to be honest) – and I’m with him on this but his emphasis on existing organizations such as the AMA and PRSA instead of the vendors differ with with the approach Brandtology has embarked on.

On the other hand, one could say the same thing of Omniture’s Certification, or before it, Novell’s CNE – these are all vendor created programs – the certifications have not tended to carry beyond the institutions that created them.

Olivier Blanchard argues certification and accreditation is a given, it’s more how it’s done who is doing the accreditation.

Will Brandtology Academy be one of several new Social Media Analytics training centers?

Only time will tell – perhaps we’ll be seeing several academies in 2011.  However, in this case, I’m for the Brandtology Academy as it not only proposes to give a good foundation for Social Media Analytics but it focuses on Asia – an area that rich and thriving but where not much attention has been paid by monitoring vendors – even though the market for social monitoring and social media, I believe, is exploding in Asia Pacific.

So many things going on for me that it’s sometimes hard to focus – often I look “outside” to see what is going on in Social Media that’s interesting ( my Web Journals); other times, like this one, I feel the need to touch the data personally in a different way – that’s the substance of this blog – touching the data and look at it differently (hopefully, than anyone else does).

If you read this post all the way through I promise you’ll get methods you can use to improve the information your gathering from Social Media Monitoring and Organic Search (but you don’t have to stop there, Site Search would work just as well under this model, etc).

Note: I haven’t worked close enough with Text Analytics platforms like Lexalytics and Clarabridge - it’s possible they might supply aspects of this functionality – just to be sure – check them out in case they do offer it (though I doubt they offer it in the way I’m presenting it here).

I started with my own Organic Search Traffic from Google this month (you can download the entire spreadsheet here).  My Search traffic now comprises 40% of all the traffic to WebMetricsGuru.com and seems to be going up more and more – almost all of it is “long tail” – and how does one make sense of it?

Along with the Search Query I sorted by City as the secondary dimension and the report became a lot more usable to me all of a sudden.  It’s as if, by sorting by city, I could not see a pattern in the information that wasn’t as clear before – and it became the takeoff for this long, and I hope, rewarding post for you to read.

Here’s a chart I created around two subjects I found in my search logs – Restaurants and Social Media.  I could have picked far more – could have spent days on this – but that’s not the point – the point is to evolve a way of working with data – if you want to spend days working your data – or mine, be my guest.

As I looked at my own search logs for this month – I saw patterns (the artist in me) – it’s as if the data was speaking to me – people were asking about weather there was a net promoter score for restaurants, or if I was doing any more comparisons between social monitoring platforms, or even if I had a quick and easy Social Media Scorecard to share.

I saw patterns, such as Social Media + “how to”  and Social Media + ROI, etc.  Sure, there were only a few people asking those questions (in some cases, they spent hours on my blog looking for the answers, just look at the excel spreadsheet in full and you’ll see the most engaged reader was looking for (based ib time spent in a single session).

As I pulled this data it looked strangely familiar – no I’m not speaking about Radian6 Word Maps (they are limited by a single word and are not capable of what I did in my first slide – grouping by concept – at least, not with considerable amount of tagging – something most people don’t want to deal with).   Rather, I’m speaking of Google’s own Wonder Wheel.

Speaking for myself only, the Wonder Wheel is a “Wonderful Experiment” or Tool created by Google Engineers to create some sort of order out of searches that people are making on Google – it’s also there to help give you ideas when you want to come up with keywords for ads you might want to run in AdWords.     But the Wonder Wheel doesn’t work with your own data - unless Google, or someone else, were to adapt it and use it to process Search Query Referral Traffic, Site Search Queries (when site search is being used on a site) and SOCIAL MEDIA MONITORING platforms like Radian6, Sysomos, BrandWatch, etc, at el.

The Wonder Wheel makes sense, in other words if you want to operate on other peoples data - but not much help if you want to understand your own – if your monitoring your own logs, if your running your own query in Radian6, if your pulling your own data – if your a brand and you want to know what people said about you when they visited your properties – nothing like the Wonder Wheel exists at the very moment, that I know off, offhand, for your own data.

That’s the data you care about the most – your own – not Google’s.

I suppose Google could have used the Wonder Wheel with Google Analytics and Google WebMasterTools – after all – it’s all their platforms – we absolutely know Google haven’t used the Wonder Wheel technology at all for Google Analytics – but did they use it for WebMasterTools?   No, they didn’t – but there is useful information – just not the semantic breakdown I’m talking about today.

Undoubtedly , the Wonder Wheel would be very useful in Google Analytics but it’s also fair to point out that such analysis is left out of every web analytics tools I’ve ever used – none of them have that information nor were they built for it.    So while I could see the benefit of Google adding Wonder Wheel to Google Analytics, I’m not sure they ever would – and as far as Web Master Tools – they certainly could add it – if they wanted to – and it would make a lot of sense if they did.

Using a “Wonder Wheel” for Social Media Monitoring

What if he had something like the Wonder Wheel for Social Media Monitoring? – How much better do you think the intelligence would be?    Again, you might think Lexalytics or Clarabridge, if you upload your monitoring data to those platforms – but I don’t think they’re going exactly the same place I’m going with this).

Besides, many of the monitoring platforms already use Lexalytics on their backend for sentiment analysis scoring and aren’t providing anything like what I’m focusing on today - so why would Lexalytics provide it on their own?  Wouldn’t these platforms have done it already if it was so easy for them?

I just happen to have handy a downloaded log of Havana Central’s interactions from Radian6 on hand for the first half of this month to use as a test(see  Aug 1-15th all).  As mentioned before, I’m working with the this restaurant chain and have done a case study on them – as well as set up monitors and alerts on some of their competitors -the very same thing I suggested Roger Smith Hotel try, recently……

…though the action we take from alerts is open to debate - while we should monitor competitors – I know we have to be very careful how we actually engage with them – Brian Solis has that pegged down better than I do and perhaps I ought to read his book so I understand the full implications of monitoring being set up and how you’d use it to engage with your customers – or just listen, if that’s all want to do.

The first thing I’d do is sort by content alphabetically – to try to simulate the Wonder Wheel type of map that Radian6 can’t today provide (see below- but who knows,  in the future – maybe they’ll read this post and add it as a feature next year sometime, along with additional interesting technologies I know they’re working on merging).

You can certainly click on the words you care about like “Havana”- but there’s no real semantic grouping – nothing that does what I put out as my first slide in this post.  Wonder Wheel could eat up Radian6′s logs, digest them and give you something that actually helps you answer what people are looking for or saying.

Could have gone a bit deeper but there wasn’t that much really to summarize here – and honestly – the messaging is more uni-directional than bi-directional – which is what you need it to be for effective Social Media Outreach.

If the Wonder Wheel type technology had a crack at these logs you could click on them and it would keep bringing up more information – except the information would be coming from your data – not what Google wants you to create ads for, or what others on Google searched for – but instead, what you need to understand about the people who are coming to you asking questions -  questions we all should be answering.

And with that – my next post will attempt to answer  a few questions my readers have asked me – based on this post and my own data from Google Analytics.

Reading Gary Angel’s post on Social Media Dashboarding – Q& (I missed the webinar on it) got me thinking about my own issues with various monitoring platforms I’ve tried.   The first point is in order to get interesting data to dashboard you almost always have to categorize data differently than what the listening platform provides by default and it’s a considerable amount of work to set up accounts, pull the data, classify it and then dashboard it.  And, while most clients seem to want sentiment analysis – the recommendations are not to include it for a variety of reasons.

…to get interesting dashboard metrics, you need to classify and trend the basic metrics in interesting ways. Hitwise, for example, provides a list of up-stream and down-stream sites. But only by classifying the sites and then aggregating and trending the data can those reports be turned into interesting dashboard metrics.

…. Most of these tools are fairly restrictive in the way they let you collect and produce information. So you can’t usually setup a single profile/account and then aggregate the data in the ways you decide are interesting. You have to collect much of the data based on the way you intend to use it.

….Another issue that drew quite a bit of attention was our discussion of sentiment analysis. Sentiment analysis is so interesting and contextual that our clients nearly always demand that we include it in dashboards. But we often push-back since the data can be problematic. Neil Beam from AT&T added this comment:

“At AT&T, we are moving away showing automated sentiment at the exec level. We only show manual scoring at the exec level. Our engagement team uses sentiment to determine the queue for responses.”

To me, this is best practice all the way around and it’s what I’d like our clients to do more consistently.

I think the biggest bombshell from Gary’s post on Dashboarding was a point he made at the end – that most listening platforms  are not designed for Measurement – they were designed to Monitor conversations – the measurement overlay is often difficult to apply… especially when what we’re asking for is, in fact, accurate measurement.

…  tools (like Radian6, BuzzMetrics, and SM2) that are used for social measurement started life as tools dedicated to social monitoring and are still used that way much of the time. Like web logs, the “river of news” used to help PR and Customer Support professionals track and respond to conversations wasn’t originally intended for measurement.

…there is a tendency to just use the setup create by the PR folks when it comes to measurement. This is a bad idea – not only is the setup unlikely to be clean, but it won’t capture many of the classifications that actually turn out to be interesting.

We might need to go back to the drawing board if we really want Social Listening Platforms that are geared to measurement (maybe the SAS tool is more along those lines) instead of Listening, mainly.   My guess is that is already beginning to happen.

In other news Share This is now sharing Reach and Social Scoring data – see ShareThis Adds Social Media Analytics but I haven’t had a chance to try it yet on my own blog – for some reason the Share This widget isn’t giving me the information (and I just upgraded it) – I’m sure it will be sorted out soon.

According to ShareThis’ website, the new analytics will also deliver numbers related to the type of audience that is sharing your links and it will compare your blog to others in the category to see if you’re doing better or worse than your competition.

To show the impact of their new tool, ShareThis has provided an infograph made from information collected across the 850,000 publishers in their system.

What’s interesting to note here is that Twitter isn’t very effective when it comes to social reach. Only 8% of people are clicking on what they’re sent, while the return on both email and Facebook are nearly equal. Many people have been warning marketers not to give up on email and this graphic shows why.

Interestingly – the Social Reach metrics also seems to fit into the Dashboarding theme of my post today.  And EConsultancy also has a study on Engagement: why social media numbers don’t matter yesterday that says engagement is different than actually using a site – and a workable  definition of engagement does not exist yet.

…. Social media isn’t about groups of people, or market segments, or demographics, it’s about taking the time to really get to know your customers, about taking time to review individual cases and respond accordingly.

You can measure a thousand different metrics and still fail at social media, because you’re ignoring the hundreds of different methods involved. If you want to create true engagement, then you’ll need to drop any preconceptions you might have about market behaviour and take time to speak personally to each customer.

Sounds like a lot of work right?

Yep.

Oh well – so much for dashboarding … ha!  Then again, Almost 50% of Marketers Don’t Measure Social Media Campaigns anyway- I got that post from Web Analytics World.